ES2943486B2 - Triage method and system to care for victims affected by an emergency or catastrophe - Google Patents

Description

DESCRIPTION

Triage method and system to care for victims affected by an emergency or catastrophe

field of invention

The present invention relates to the field of medicine, in particular to the field of triage to care for victims affected by an emergency or catastrophe. In particular, the present invention relates to monitoring and guidance to assist in the classification and cataloging of triage, as well as in monitoring the distribution and location of patients according to the urgency of their care, in emergency situations. or catastrophe.

Background to the invention

Triage (also known as threshing or screening) is a protocol or intervention method that works to select and classify patients or victims of emergencies and disasters according to their medical needs. The World Health Organization (WHO) defines triage as a system that allows patients to be classified into health care priority groups according to their health status and available resources. These care classification and prioritization systems allow maximizing the number of lives saved with available resources. It applies to all patients who go to the emergency department of hospitals or health centers, but also in situations of emergencies and catastrophes (for example, accidents or disasters).

In emergency and disaster situations, care for victims falls to various teams and professionals who do not always have the knowledge, tools and time to evaluate the condition of the victims and prioritize their evacuation and care. This lack of evaluation of the status of the victims means that on numerous occasions they are referred to centers where there is a saturation of victims, or where they do not have the necessary infrastructure to care for this type of victims. For example, in situations in which health care teams are not the first to arrive, but rather other groups - firefighters, police - are the ones who initially make contact with the victims, in many cases their interaction with them being very delicate, since it can mean both saving lives thanks to quick action, and causing consequences due to poor mobilization or action due to lack of knowledge and resources.

Another key factor in the proper management of emergency and disaster situations is the location, communication and evaluation of victims, especially those with functional diversity. The difficulty in establishing communication channels with victims makes event management and evaluation difficult, increasing the number of resources and time needed for evacuation. According to the WHO, in an emergency situation, people (victims) with disabilities are more vulnerable when an emergency or conflict occurs and the impact that these situations can have on their health is much greater than in people (victims) without disabilities. . Since 2013, the WHO, through different forums such as “People with disabilities and disasters, a conversation that is not so obvious”, has been claiming that emergency preparedness systems are not designed so that people with disabilities can survive a disaster when they are victims of it. In a study carried out by the United Nations Office for Disaster Risk Reduction (UNISDR), it is concluded that the problems in an emergency process for victims with disabilities are difficulty hearing (39%), for see (54%), to communicate (45%); and lack of help from other people to follow the appropriate evacuation route (13%).

Furthermore, many triage methods do not take into account the environmental conditions typically found in emergency or disaster areas (such as the presence of smoke, limited visibility, obstructions to escape exits). These environmental conditions may affect the logistics of the triage method that must be implemented (for example, the route used to evacuate a given victim and transfer him or her to the nearest health center from the place where the emergency or disaster occurred).

All of these factors can affect the survival of each victim (or at least worsen their prognosis), in addition to entailing high socioeconomic costs for medical services.

Thus, the problem of the present invention is to provide a triage method and system that evaluates the care priorities of each victim, prioritizing their chances of survival, according to their therapeutic needs (for example, their disability status) and the available resources. Furthermore, the problem of the invention is to provide a triage method and system that is easy to implement, which has no adverse effects for the victims, and which allows:

- anticipate the seriousness of the situation before doctors, nurses and paramedics arrive at the emergency or disaster area;

- distribute doctors, nurses and paramedics to different places in the emergency or disaster zone, according to their medical knowledge and according to the number and physiological status of the victims, in addition to the environmental conditions, so as not to put doctors, nurses and paramedics in danger, and ensure that the medical response is proportional to the needs at all locations in the emergency or disaster area; - assign victims to health centers in the most efficient way, according to the number and physiological status of each victim, the number and specialty of doctors, and the resources available in each health center.

Brief description of the invention

In a first aspect, the present invention refers to an automated triage method to care for victims affected by an emergency or catastrophe, characterized by consisting of the following stages:

(a) place and activate in at least one victim affected by the emergency or catastrophe, a personal device (DATi) that has at least one module that sends, in real time, at least one signal to a central control device (DATc ), where each signal encodes a value of a physiological parameter of said victim,

(b) activate said central control device (DATc) in the area of the emergency or disaster, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device (DATi) , placed and activated according to step (a), and storing, in real time, said value of the physiological parameter encoded by said signal within a data set of said database,

(c) calculating and updating in real time, a V value for said victim by said central control device (DATc), based on a multivariate classification model generated from said value of at least one physiological parameter of said victim, stored in said database, where said multivariate classification model is capable of assigning each victim to one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster,

(d) determine, and update in real time, the medical specialty required by said victim by the central control device (DATc), using the V value calculated by the multivariate classification model of step (c), where the medical specialty required by a given victim, with a value V is given when said value V of the victim falls within:

- of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5.

Furthermore, in said first aspect, the present invention also refers to an automated triage system to care for victims affected by an emergency or catastrophe, characterized by consisting of:

(a) means for placing and activating in at least one victim affected by the emergency or catastrophe, a personal device (DATi) that has at least one module that sends, in real time, at least one signal to a central control device (DATc), where each signal encodes a value of a physiological parameter of said victim,

(b) means for activating said central control device (DATc) in the area of the emergency or catastrophe, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device ( DATi), placed and activated according to step (a), and store, in real time, said value of the physiological parameter encoded by said signal within a data set of said database,

(c) means for calculating and updating in real time, a V value for said victim by said central control device (DATc), based on a multivariate classification model generated from said value of at least one physiological parameter of said victim , stored in said database, where said multivariate classification model is capable of assigning each victim to one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster,

(d) means to determine, and update in real time, the medical specialty required by said victim by the central control device (DATc), using the V value calculated by the multivariate classification model of step (c), where the medical specialty required by a given victim with a V value is given when the victim's V value falls within:

- of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5.

In a second aspect, the present invention also refers to an automated triage method to care for victims affected by an emergency or catastrophe, which allows the assignment to the health center of said victims affected by said emergency or catastrophe, characterized by consisting of the following stages:

(a) place and activate in at least one victim affected by the emergency or catastrophe, a personal device (DATi) that has at least one module that sends, in real time, at least one signal to a central control device (DATc ), where each signal encodes:

- a value of a physiological parameter of said victim;

- information about the geolocation of said victim; either

- a value of an environmental parameter;

(b) activate said central control device (DATc) in the area of the emergency or disaster, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device (DATi) , placed and activated according to step (a), and store, in real time:

- said value of the physiological parameter encoded by said signal;

- said geolocation information encoded by said signal; or - said value of an environmental parameter encoded by said signal,

within a set of data from said database,

(c) calculating and updating in real time, a V value for said victim by said central control device (DATc), based on a multivariate classification model generated from a value of at least one physiological parameter and/or at least an environmental parameter of said victim, stored in said database, where said multivariate classification model is capable of assigning each victim to one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster,

(d) determine, and update in real time, the medical specialty required by said victim by the central control device (DATc), using the V value calculated by the multivariate classification model of step (c), where the medical specialty required by a given victim with a value V is given when said value V of the victim falls within:

- of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5.

(e) update, in real time, emergency occupancy according to the medical specialty of each health center within a radius of Geographic coverage of each health center capable of treating a given medical specialty is determined, for a given instant of time, by a Voronoi diagram, according to the time zone of said area of the emergency or catastrophe, using the Euclidean distance,

where for each victim affected by the emergency or catastrophe for whom step (a) has been carried out, the following step is carried out:

(f) determine, by the central control device, the geolocation of said victim based on the information on his geolocation, and assign him the health center registered in the database that is capable of treating the medical specialty determined as required by said victim. victim in step (d), where said health center is one that has a geographic coverage area within which the geolocation of said victim falls, at the instant of time of assigning said victim to a health center.

In said second aspect, the present invention additionally refers to an automated triage system to care for victims affected by an emergency or catastrophe, which allows the assignment to the health center of said victims affected by said emergency or catastrophe, characterized by consisting of:

(a) means for placing and activating in at least one victim affected by the emergency or catastrophe, a personal device (DATi) that has at least one module that sends, in real time, at least one signal to a central control device (DATc), where each signal encodes:

- a value of a physiological parameter of said victim;

- information about the geolocation of said victim; either

- a value of an environmental parameter;

(b) means for activating said central control device (DATc) in the area of the emergency or catastrophe, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device ( DATi), placed and activated according to step (a), and store, in real time:

- said value of the physiological parameter encoded by said signal;

- said geolocation information encoded by said signal; or - said value of an environmental parameter encoded by said signal,

within a set of data from said database,

(c) means for calculating and updating in real time, a V value for said victim by said central control device (DATc), based on a multivariate classification model generated from a value of at least one physiological parameter and/or at least one environmental parameter of said victim, stored in said database, where said multivariate classification model is capable of assigning each victim to one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster,

(d) means to determine, and update in real time, the medical specialty required by said victim by the central control device (DATc), using the V value calculated by the multivariate classification model of step (c), where the medical specialty required by a given victim with a V value is given when the victim's V value falls within:

- of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5.

(e) means to update, in real time, emergency occupancy according to the medical specialty of each health center within a radius of X km from the emergency or disaster area, where X is a number between 1 and 50 and where The geographical area of coverage of each health center capable of treating a given medical specialty is determined, for a given instant of time, by a Voronoi diagram, according to the time zone of said area of the emergency or catastrophe using the Euclidean distance, where for each victim affected by the emergency or catastrophe for whom step (a) has been performed, the following are used:

(f) means to determine, by the central control device, the geolocation of said victim based on the information about his geolocation, and assign him the health center registered in the database that is capable of treating the medical specialty determined as required by said victim in step (d), where said health center is one that has a geographic coverage area within which the geolocation of said victim falls, at the instant of time of assigning said victim to a health center.

Preferably, said multivariate classification model of said second aspect is developed by taking into account different population cohorts according to sex and age by: (i) performing step (a) for each person of:

- a population of people in need of resuscitation;

- a population of people who need medical attention within 1 hour of the emergency or disaster;

- a population of people who need medical attention within 1 to 2 hours of an emergency or disaster;

- a population of people who need medical attention within 2 to 4 hours of an emergency or disaster; and

- a population of people who do not need medical attention within 4 hours of the emergency or disaster;

(ii) calculate a multivariate classification model of at least two values where each value is either a value of a physiological parameter or a value of an environmental parameter stored in said database, and where said multivariate classification model assigns each person of a given population to that population.

Description of the figures

Fig. 1. General block diagram of the triage and guidance procedure.

Fig. 2. Shows a representation of the deployment of the system to implement the method of the present invention in an open and diaphanous square space (exterior), of the different individual devices (DATi) deployed in the area and installed on the victims, as well as the central control device (DATc) with battery connection or connected to an outpatient ICU to have continuous power. Within this area, the beacons are detected with intensities configured between 60 and 80 intensity points for locating users in an outdoor space, which is equivalent to between 1 to 2 meters of precision (10 to 15 meters from the beacon). In addition, the areas delimited by curves indicate the range of visibility or coverage of each beacon, that is, it is the area from which a user can be located by the beacon.

Fig. 3. Shows a representation of the deployment of the system to implement the method of the present invention in an open and diaphanous square space (interior), of the different individual devices (DATi) deployed in the area and installed on the victims, as well as the central control device (DATc) connected to the electrical network. Within this area, the beacons are detected with intensities configured between 60 and 80 intensity points for locating users inside the building, which is equivalent to centimeters of precision (12 to 16 cm). In addition, the areas delimited by curves indicate the range of visibility or coverage of each beacon, that is, it is the area from which a user can be located by the beacon.

Fig. 4. Shows an embodiment of the central control device (DATc, 1) of the invention, which has a power supply means (2), which has an energy storage system (3) and a charging system ( 4), a means of communication (5), a means of control (6), a means of signaling and identification (7), a means of physiological acquisition (8), a means of environmental acquisition (9), means for movement monitoring (10) and a learning system that will allow the automatic classification of information to aid decision making based on the rest of the elements (11). The device (1) is connected to an electrical power line.

Fig. 5. Description of the modules of an embodiment of the individual device (DATi 21) of the invention, which has an ultra-low consumption power supply (22), which has an energy storage system (23) and a charging system (24), a communication means (25), a physiological acquisition means (26) and an environmental acquisition means (27). The device (21) will be connected to individuals in a non-invasive way, using a bracelet with electrodes as a sticker.

Detailed description of the invention

The present invention relates to an automated triage method to care for victims affected by an emergency or catastrophe. Furthermore, the present invention relates to an automated triage system to care for victims affected by an emergency or catastrophe. Thus, the method and system of the present invention offers real-time tracking and monitoring to help (support, support, assist) the classification of victims in an emergency. This classification is carried out in real time based on the triage protocol and the monitoring of physiological variables, being applicable to post-emergency monitoring of both patients and the intervention teams themselves, who have been exposed to vulnerabilities due to the emergency situation itself. . This invention is fundamentally aimed at managing emergency situations in an accessible manner, non-discriminatory, autonomous and transparent use, and also solves the problem explained above through a network of devices with intelligence and wireless and non-invasive communications capacity, called Auto-Device. Triage (DAT).

For the purposes of the present invention, the term "victim" refers to a human being located in the area of an emergency or catastrophe when it has occurred. In contrast, the term "person" refers to a human being who could be , but is not necessarily, the victim of said emergency or disaster (for example, a person on a first responder who could become a victim by inhaling smoke in the area of said emergency or disaster). The term "people" is used to group human beings from a given population according to the medical specialty required by each person in that population. Thus, for example, a person can be a person from the population of people who needed resuscitation used to develop a multivariate classification model, and a victim can be classified into said population of people (or rather, the sub-population of victims of said population).

Said method of the present invention consists of a step (a) of placing and activating in at least one victim (preferably each victim) affected by the emergency or catastrophe, a personal device (DATi). Thus, said system of the present invention comprises means for carrying out step (a). Said DATi has at least one module that sends, in real time, at least one signal to a central control device (DATc), where each signal encodes a value of a physiological parameter of said victim. In a preferred embodiment of the present invention, each signal encodes:

- a value of a physiological parameter; either

- information about the geolocation of said victim.

In a more preferred embodiment of the present invention, each signal encodes:

- a value of a physiological parameter;

- information about the geolocation of said victim; either

- a value of an environmental parameter;

Physiological parameters:

The value of a physiological parameter (or physiological variable) comprises physiological information measured and updated in real time. In a preferred embodiment of the method and system of the present invention, each physiological parameter is selected from the group consisting of: physiological parameters determined by measuring bioimpedance, physiological parameters determined by measuring heart rate, and physiological parameters determined by measuring movements. In a more preferred embodiment of the method and system of the present invention, the physiological parameters are selected from the group consisting of: the oxygen saturation in the blood of the victim, the state of the circulatory system of the victim, the arterial blood gas level and venous pressure of the victim, the body temperature of the victim, the heart rate of the victim, the breathing rate of the victim, the sweating of the victim and the onset of seizures of the victim.

To measure each physiological parameter (or physiological variable) the following is preferably used:

- bioimpedance measurement techniques (means);

- techniques (means) for measuring heart rate; I

- techniques (means) for monitoring movement.

More preferably, to measure each physiological parameter (or physiological variable) the following is used:

- bioimpedance measurement techniques (means) (including heart rate measurement techniques); I

- techniques (means) for monitoring movement.

Monitoring of physiological variables using bioimpedance techniques:

Knowledge of the electrical properties of tissues is of great interest in a wide range of biomedical applications. Specifically, these electrical properties determine the type of tissue, its physiological state or, in clinical practice, allow the evaluation of the possible therapeutic effect of treatments or the issuance of a diagnosis. The characterization of the passive electrical behavior of a tissue can be carried out by measuring its impedance (bioimpedance), that is, the opposition it presents to the passage of alternating electric current in a range of frequencies of interest. Within the frequency dispersion p (kHz to MHz) you can observe the charge/discharge mechanism of the cell membranes (which have capacitive behavior), through the intracellular and extracellular media (with resistive behavior - they are electrolyte solutions -). The magnitude of the impedance of a biological system varies with frequency (as the frequency increases, an increase in conductivity and a decrease in permittivity are observed. These mechanisms reflect structural changes in the membranes, which may be of clinical relevance since They provide valuable information related to the composition or structure of the biological system under study. Therefore, knowledge of the electrical properties of biological systems allows us to determine the type of tissue, its physiological state or, in clinical practice, evaluate the possible effect of. therapeutic treatments. In conclusion, the use of the potential of bioimpedance, bioelectricity and movement measurement techniques is identified to meet this requirement.

Unlike conventional "sensing" systems, bioimpedance techniques are preferably used in the present invention to allow real-time monitoring of physiological variables in a non-invasive manner and without the need for specialized knowledge (i.e. without the need to have doctors, nurses or paramedics on site). Certainly, through circuit theory it is possible to propose electrical schemes that represent the measured electrical properties and/or physiological changes in a biological system, quickly and accurately. In the context of the method and system of the present invention, said techniques are capable of measuring critical physiological parameters (related to the anatomy, physiology and pathology of the victim), such as blood oxygen saturation (by means of spectroscopy). of impedance, EIS), the state of circulation (by means of impedance plethysmography, IPG) or toxicity levels and body temperature (by means of bioelectrical impedance, BIA). Even the reconstruction of medical images based on the electrical properties of biological systems, by means of electrical impedance tomography (EIT), would be useful in anatomical visualization, physiological activity and diagnosis.

Monitoring of parameters related to heart rate.

Bioimpedance measurements also allow heart rate to be monitored, being a variable of special interest in extremely serious cases. This technique, called cardiographic bioimpedance (CGI) or transthoracic electrical impedance plethysmography, is based on calculating changes in blood volume in the transthoracic region (transthoracic impedance). In the human body, body impedance is modified due to variations in blood circulation, in turn induced by alterations in heart rhythm. In fact, transthoracic impedance is influenced by respirations, circulation, and blood volume in the transthoracic region. Therefore, by analyzing the transthoracic impedance value, the health or condition of the heart can be evaluated along a number of dynamic parameters in the context of triage methods and systems.

Finally, the use of motion sensors makes it possible to monitor the breathing rate or the triggering of seizures. Filtering the ECG signal would require pre-processing of the signal to remove the baseline, motion artifacts and power grid (in the event that any device will be connected using this mode) using Baseline morphological filtering and a filtering (Filt or FLIR). For the detection of QRS complexes, there are Modified Holsinger algorithms, as well as Pan and Tompkins algorithms for real-time detection. Finally, for feature extraction, the Independent Component Analysis (PCA) technique is used to define the characteristics of the model for the subsequent use of Artificial Intelligence algorithms. PCA cannot be done in real time a priori, but it can be done on data already recorded to feed the machine learning system so that the system detects or queries those components directly.

Monitoring breathing and seizures using movement monitoring techniques:

The use of accelerometry makes it possible to monitor the breathing rate or the triggering of seizures. Accelerometers placed on the torso have been shown to measure inclination and angular changes during breathing, estimating respiratory rate using digital signal processing technologies.

Within this principle, several methods for respiration estimation have been published using various configurations and signal processing methods: biaxial accelerometers or hybrid principal component analysis methods to estimate respiratory rate during static positions. On the other hand, multicenter studies have demonstrated the ability of accelerometry to detect tonic-clonic seizures with high sensitivity (90%) and a low false alarm rate.

Thus, in the preferred embodiment of the method and system of the present invention where each physiological parameter is selected from the group consisting of: physiological parameters determined by measuring bioimpedance, physiological parameters determined by measuring heart rate, and physiological parameters determined by measuring movements , preferably measured:

- bioimpedance by means of impedance spectroscopy (EIS), impedance plethysmography (IPG) or bioelectrical impedance (BIA);

- cardiac rhythm by means of cardiographic bioimpedance (ICG) or transthoracic electrical impedance plethysmography (transthoracic impedance).

Furthermore, in the most preferred embodiment of the method and system of the present invention where the physiological parameters are selected from the group consisting of: the oxygen saturation in the blood of the victim, the state of the circulatory system of the victim, the level of the victim's arterial and venous blood gases, the victim's body temperature, the victim's heart rate, the victim's respiratory rate, the victim's sweating, and the victim's seizure triggering, preferably measuring:

- oxygen saturation in the victim's blood by means of impedance spectroscopy (EIS);

- the state of the victim's circulatory system by means of impedance plethysmography (IPG);

- the level of arterial and venous blood gases of the victim, the body temperature of the victim, also the sweating of the victim, by means of bioelectrical impedance (BIA);

- cardiac rhythm by means of cardiographic bioimpedance (ICG) or transthoracic electrical impedance plethysmography (transthoracic impedance);

- the respiratory rate of the victim, in addition to the triggering of seizures of the victim, by means of accelerometry.

Geolocation:

Each DATi determines the geolocation of the victim who is placed in the emergency zone. Information on the geolocation of said victim includes the geographic coordinates (latitude, longitude) of the victim, preferably obtained through satellites and GPS/GNSS receivers, or the triangulation coordinates of the victim, preferably obtained through a beacon system that can be ride in the area of the emergency or disaster. Thus, in a preferred embodiment of the method and system of the present invention, the geolocation of each victim affected by the emergency or catastrophe, for whom step (a) has been carried out, is carried out by:

- a GPS/GNSS system; I

- a beacon system.

In the event that the emergency or catastrophe occurs outdoors (i.e., not within a space confined by walls/ceilings) said information preferably comprises geographic coordinates, and in the event that the emergency or catastrophe occurs indoors said information preferably it comprises triangulation coordinates. Such information makes it possible to locate the location of each victim placed with a DATi and, therefore, create accessible routes to said victims. This functionality is very useful in low visibility spaces. The location of the victims will also allow us to know their location in the emergency or disaster area with respect to possible environmental dangers (for example, fire or smoke), and thus identify the situation of the most vulnerable victims with respect to their environment in the triage state. , either due to their physiological state or their auditory, visual or motor condition.

In the case of using a beacon system, the beacons must be placed in the emergency zone so that each DATi and the DATc could receive signals from at least two beacons. Preferably, the beacons are located so that each DATi or DATc is located within 20 meters, more preferably 15 or 10 meters of at least two beacons. Preferably, location beacons are implemented with wireless technologies such as Bluetooth, LORAWAN or UWB (Ultra Wide Band). This localization can be implemented in two ways:

- Beacons are deployed with any of the wireless technologies mentioned above; either

- through the DATi's own beacons, the communication module is used to measure the RSSI signal and serve to obtain a location by approach. Each of these devices will have a unique identifier on the network

Environmental parameters:

The value of an environmental parameter comprises information measured and updated in real time about the environment of the victim in the emergency or disaster zone or even about the environment of the emergency or disaster zone. These environmental parameters are very influential on the physical and mental state of the victim. In this sense, for the management of intelligent environments based on the recording of environmental parameters, air toxicity, temperature or humidity stand out as priority measures. Preferably each environmental parameter is selected from the group consisting of: air toxicity, nuclear, biological or chemical (NBC) toxic agents, smoke, ambient temperature, referral from healthcare units, and intensive care units (ICU). available (numbers, and their location/proximity). In a preferred embodiment of the method and system of the present invention, each environmental parameter is selected from the group consisting of: the toxicity of the air, the presence of a nuclear, biological or chemical toxic agent, the presence of smoke and the ambient temperature.

Environmental parameters and their management are usually based on IoT (Internet of Things). In fact, there are commercial devices such as the Drager X-am® 8000 for the acquisition/detection of toxic and flammable gases, as well as vapors and oxygen. These solutions have not been defined for triage, but they are useful for sending these parameters in platform supervision and control operations. Thus, in the preferred embodiment of the method and system of the present invention where each environmental parameter is selected from the group consisting of: the toxicity of the air, the presence of a nuclear, biological or chemical toxic agent (NBQ), the presence of smoke and the ambient temperature, preferably measured:

- air toxicity, the presence of a nuclear, biological or chemical toxic agent (NBQ), the presence of smoke through a commercial device such as Drager X-am® 8000; and

- The ambient temperature was measured by a thermometer.

In a preferable embodiment, DATi devices are placed and activated on patients non-invasively using adhesives or bracelets on emergency victims, as well as on the intervention teams themselves, on the wrist or trunk. Preferably, DATi devices are placed on patients through surface adhesive electrodes (included in bioimpedance measurement, heart rate measurement, or movement monitoring techniques) with the following configuration. At one end of the arm the electrodes are placed like a transmitter bracelet, on the chest, and the distal parts of the four extremities are placed with motion sensors based on accelerometry and surface adhesive electrodes for monitoring biopotentials, partial oxygen saturation , body temperature and sweating, and at the other end of the arm, as well as on the lower extremities, 3 electrode stickers that will perform the acquisition of muscle mobility values using bioimpedance measurements. This technique allows the application of methodologies related to its application basis such as plethysmography, cardiography and tomography, which are useful in anatomical visualization, physiological activity and diagnosis. This allows for non-invasive detection of changes in oxygen, heart rate or toxicity levels.

Each DATi device interacts to send signals that encode information to the DATc device while in the emergency area. When users are moved, DATis will send information to a cloud processing server with DATi-compatible connectivity. This communication protocol allows interaction with the infrastructure and with users and managers, in an automated and transparent manner, to locate, guide and warn of possible alarms and give precise and adapted instructions to act in the different possible emergency situations. Through a conceptual map it will allow the victims of the emergency to be located, as well as the intervention operators. Its use is universal and non-discriminatory, also valid for people (victims) with functional diversity.

Furthermore, with the aim of facilitating communication and the possible lack of coverage between user devices located in a certain building, the system allows through the users' mobile application and wireless communication, either short or long range, from the same user devices can be used, if the users have it activated, to forward the information and the evacuation route between the users of the building, and that this information can reach the staff security and self-protection.

Said method of the present invention also consists of a step (b) of activating said central control device (DATc) in the area of the emergency or catastrophe, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device (DATi) placed and activated according to step (a), and store, in real time, said value of the physiological parameter encoded by said signal within a set of data of said database. Preferably said DATc is activated within a radius of Z m of at least one of the victims (and therefore, said DATc is activated within a radius of Z m of at least one DATi), where Z is a value chosen between 1 and 500 meters, more preferably between 1 and 200 m. Thus, said system of the present invention also comprises means for carrying out step (b).

Furthermore, said method of the present invention consists of a step (c) of calculating and updating in real time, a V value for said victim, by said central control device (DATc), based on a multivariate classification model generated of a value of at least one physiological parameter of said victim stored in said database, where said multivariate classification model is capable of assigning each victim into one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster.

Thus, said system of the present invention also comprises means for carrying out step (c).

Likewise, said method of the present invention consists of a step (d) of determining, and updating in real time, the medical specialty required by said victim by the central control device (DATc) using the V value calculated by the multivariate classification from step (c), where the medical specialty required by a given victim with a value V is given when said value V of the victim falls within:

- of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5.

Thus, said system of the present invention also consists of means for carrying out step (d).

If data is not received from a DATi placed and activated, the victim in which said DATi is placed is assumed to be in a state of vital emergency, and will thus be classified as R1.

Thus, said central control device (DATc) comprises at least:

- a module that receives each signal sent in real time by each personal device (DATi) placed and activated according to step (a);

- a database that stores in real time the information/value encoded by said signal,

- at least one computer program product for at least:

(i) calculate and update in real time, a V value for said victim based on a multivariate classification model; and

(ii) determine, and update in real time, the medical specialty required by said victim using said V value.

In a preferred embodiment, the automatic triage device (DATc) used in the method and system of the present invention comprises a power supply means, a communication means, a control means, a signaling and identification means, a acquisition (module that receives the signals sent by each DATi), and a machine learning system means (which comprises said database), in addition to said computer program product mentioned above (which additionally controls the rest of the DATc components), which are described below:

a) an energy supply means, which in normal situations provides the device with the energy necessary for its operation and for the charging and maintenance of the alternative power supply, which would provide energy to the device in the event of a power failure and which Respect the autonomy of operation in order to comply with the regulations for devices or appliances for emergency situations. In a preferred embodiment of the invention, this alternative system comprises an energy storage system and its charging system. This storage system consists of one or more batteries. Any battery technology, including solid state or thin film and energy storage in supercapacitors or ultracapacitors, is applicable to the device. In another preferred embodiment, additional means of charging the storage system independent of the electrical network may be available, such as solar panels, energy collectors from electromagnetic radiation, movement, thermal energy or any other means called " energy harvesting".

b) a communication means by which the DATc device communicates with the other similar devices (DATi and, in a preferred embodiment, at least one other DATc) that form the system network, with the users of the place where it is deployed, with emergency, security and civil protection services. In a preferred embodiment of the invention, the communication medium may be short and long range wireless communication media such as Bluetooth, ZigBee, Wi-Fi, NFC, RFID, 3G, 4G, 5G, etc., dedicated wired communication media or well means of communication by carrier through the electrical network itself. The communication of the DATc with the users (end user, manager, security or self-protection units and emergency services, security and civil protection) can be carried out through any type of device or mobile terminal that has wireless communications and any operating system, ( smartphones, tablets, telephones, “technological glasses”, “watches with wireless communication systems”, etc.) or with any device equipped with dedicated wired communication means, including carrier communication means through the electrical network itself.

c) a control means responsible for managing the modes of operation or states and the information provided in each of these modes, depending on the signals and commands or instructions it receives, and which in accordance with the particular embodiments of the invention can be a microcontroller, a microprocessor, an FPGA, a DSP and/or ASIC. The possible operating modes are normal situation, emergency situation and device out of service. In a preferred embodiment of the invention, the information provided corresponds to the presence or absence of power from the electrical network, the measured load level of the alternative power supply and the operating mode of the device out of service. This information will be indicated both by means of light signals incorporated into the device, LED type or similar, and by information sent to the monitoring and management system, through the communication medium. In addition, the devices provide information about their layout and location, based on the place where they are located (building), floor, geographic coordinates (longitude, latitude) or triangulation (X,Y,Z) relative to their location and operating mode or status (normal/emergency/out of service).

d) a means of signaling and identification, focused on the one hand on compliance with current regulations for devices for use in emergency situations and, on the other hand, focused on maintenance tasks and management of the deployment of devices on site. In a preferred embodiment of the invention, this means comprises wireless identification, and also, radio frequency labels, type RFID and NFC, in any of the active and passive modalities, barcodes and two-dimensional codes, type QR-Code, which They allow you to identify and manage the functionality of each device. The information through light signals provided by the control means and described in the previous point can also be considered as signaling. The casing or envelope will ensure the visibility of the device in the dark or in low light conditions, using fluorescent or similar materials.

e) an acquisition means (module that receives the signals sent by each DATi) of the values of the environmental and physiological parameters received by the DATis. In a preferred embodiment of the invention, this means will be aimed at acquiring the parameters mentioned above. The casing or envelope of the DATi will ensure the measurement of these parameters. The system will be scalable and configurable, with the possibility of including new sensors that allow measuring other parameters that may be relevant. f) a means of machine learning system. The machine learning system will have as its knowledge base a dataset (long set of data) of patient measurements annotated by a clinical expert, using the existing database of values of physiological parameters and values of all those variables relevant to the diagnosis in triage. In a preferred embodiment, the input parameters include the pathologies that can be measured in triage: cardiac, respiratory and mobility pathologies. Each of these instances will be evaluated manually by a clinical expert, noting the triage phase in which it is located. This dataset (long set of data) will be built prior to the development of the machine learning system and will be used both to train and evaluate the learning model. In addition, this dataset will serve to objectively evaluate the performance of the system and be able to debug its functions. The dataset (long set of data) will also be continually fed with new instances that appear in the future and the learning model refined with the aim of obtaining continuous improvement and an increasingly effective system. When the machine learning system has been developed, it will be able to analyze new instances of a patient at a given time and will be able to classify which phase of triage they are in.

The DATi device has the same design and implementation as the DATc but does not include the learning system media or the control module. The environmental and physiological acquisition medium is where the relevant signals are acquired and where that information is processed to be sent to the DATc. This medium is described in greater depth below:

a) Means of acquiring values of physiological parameters and, in a preferred embodiment, values of environmental parameters (including those of available health care units). In a preferred embodiment, the physiological parameters recorded for each individual are: electrocardiogram, upper extremity mobility, lower extremity mobility, oxygen saturation and body temperature, and the environmental parameters are: air toxicity, toxic agents derived from NBC, smoke , ambient temperature, referral to healthcare units, available ICUs (number, location/proximity).

For filtering the ECG signal, signal preprocessing is used to eliminate the baseline, motion artifacts and the electrical network, which could be done through Baseline morphological filtering and FiltFilt filtering. However, since the entire signal is not available and we want it to be in real time, an IIR filter is used that offers acceptable results for the context of this patent with minimal phase distortions. For the detection of QRS complexes, the Modified Holsinger and Pan and Tompkins algorithms are used for real-time detection. For feature extraction, the Independent Component Analysis (PCA) technique is used to define the characteristics of the model for the subsequent use of Artificial Intelligence algorithms. PCA cannot be done in real time a priori, but it can be done on data already recorded to feed the machine learning system so that the system detects or queries those components directly.

To filter the oxygen saturation, a low-pass filter is made to eliminate the noise introduced by the sensor.

Finally, every evacuation and emergency device must meet basic requirements for autonomy and load signaling. Therefore, the proposed central node device (DATc) is powered from the electrical grid and with an alternative power supply that works in the event of a power grid failure, similar to what is indicated in the regulations related to emergency lighting, Instruction Low Voltage Complementary Technique 28 (ITC_BT_28) of the Low Voltage Electrotechnical Regulation (REBT, Royal Decree 842/2002, of August 2).

This system and its devices will be ultra-low consumption with great autonomy capacity, minimum 15 days.

In steps (c) and (d) of the method of the present invention, calculations are performed. In step (c), a V value is calculated for the victim using a multivariate classification model generated from said value of at least one physiological parameter of said victim, stored in said database. In a more preferred embodiment, said V value generated by said multivariate classification model is a normalized value.

Said multivariate classification model is capable of assigning a victim to one of the groups R1 to R5, depending on the range of values within which the V value falls. In particular, said multivariate classification model is capable of assigning each victim to one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster.

Thus, in step (d), the medical specialty required by said victim is determined and updated in real time by the central control device (DATc), using the V value calculated by the multivariate classification model in step (c). ), where the medical specialty required by a given victim, with a value V is given when said V value of the victim falls within:

- of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5.

Preferably, said multivariate classification model is generated from at least two values, where each value is a value of a physiological parameter of said victim stored in said database. Thus, in a preferred embodiment of the method and system of the present invention, said multivariate classification model is developed by taking into account different population cohorts, according to sex and age, by:

(i) perform step (a) for each person of:

- a population of people in need of resuscitation;

- a population of people who need medical attention within 1 hour of the emergency or disaster;

- a population of people who need medical attention within 1 to 2 hours of an emergency or disaster;

- a population of people who need medical attention within 2 to 4 hours of an emergency or disaster; and

- a population of people who do not need medical attention within 4 hours of the emergency or disaster;

(ii) calculate a multivariate classification model of at least two values, where each value is a value of a physiological parameter of said victim stored in said database, and where said multivariate classification model assigns each person of a given population to said population.

In another preferred embodiment of the method and system of the present invention,

(I) each signal sent by said module to the central control device (DATc), in real time in step (a) and saved in said database, encodes:

- a value of a physiological parameter;

- information about the geolocation of said victim; either

- a value of an environmental parameter;

(II) the central control device, in real time in step (b), stores:

- said value of the physiological parameter encoded by said signal;

- said geolocation information encoded by said signal; or - said value of an environmental parameter encoded by said signal;

(III) the multivariate classification model assigns a victim to a given population of victims according to the environmental and/or physiological parameters stored in said database. In such circumstances, said multivariate classification model is generated from at least two values, where each value is either a value of a physiological parameter or a value of an environmental parameter of said victim stored in said database. Thus, in a more preferred embodiment of the method and system of the present invention, said multivariate classification model is developed by taking into account different population cohorts according to sex and age by:

(i) perform step (a) for each person of:

- a population of people in need of resuscitation;

- a population of people who need medical attention within 1 hour of the emergency or disaster;

- a population of people who need medical attention within 1 to 2 hours of an emergency or disaster;

- a population of people who need medical attention within 2 to 4 hours of an emergency or disaster; and

- a population of people who do not need medical attention within 4 hours of the emergency or disaster;

(ii) calculate a multivariate classification model of at least two values where each value is either a value of a physiological parameter or a value of an environmental parameter of said victim stored in said database, and where said multivariate classification model assigns each person in a given population to that population.

Important is that each parameter (for example, physiological and/or environmental) whose value is obtained in step (a) to send encoded in a signal to the DATc, is the same used in step (c) to calculate the value (V ). In a particularly preferred embodiment, each parameter whose value is obtained in step (a) for a given victim is also a parameter whose value is obtained for all victims of the same emergency or catastrophe. Thus, if the value of the heart rate parameter is used to calculate the value (V) in step (c) for a given victim, it would be especially preferred that the value (V) of all victims of the same emergency or catastrophe also It is calculated using the value of the heart rate parameter particular to each victim.

In a preferred embodiment of the method of the present invention, said method is additionally for (that is, allows) the assignment, to the health center, of said victims affected by the emergency or catastrophe, where:

(A) each signal sent by said module to the central control device (DATc) in real time in step (a), encodes:

- a value of a physiological parameter; either

- information about the geolocation of said victim;

(B) The central control device, in real time in step (b), stores,

- said value of the physiological parameter encoded by said signal; or - said geolocation information encoded by said signal, within said data set of said database,

for which said method additionally includes the following steps:

(e) update, in real time, emergency occupancy according to the medical specialty of each health center within a radius of X km from the area of the emergency or disaster, where The geographical area of coverage of each health center capable of treating a given medical specialty is determined, for a given instant of time, by a Voronoi diagram, according to the time zone of said area of the emergency or catastrophe using the Euclidean distance, where for each victim affected by the emergency or catastrophe for whom step (a) has been carried out, the following step is carried out:

(f) determine, by the central control device, the geolocation of said victim based on the information on his geolocation, and assign him the health center registered in the database that is capable of treating the medical specialty determined as required by said victim. victim in step (d), where said health center is one that has a geographic coverage area within which the geolocation of said victim falls, at the instant of time of assigning said victim to a health center.

In a more preferred embodiment of the method of the present invention for the assignment to the health center of the victims affected by the emergency or catastrophe, the assignment of each victim, for whom step (d) has been carried out, to the nearest health center is established by solving a multi-criteria mathematical programming model, based on at least the following criteria:

- Distance to the hospital center;

- Area of specialization;

- Occupation of the emergency; and

- The medical specialty required by said victim, determined in step (d).

In an even more preferred embodiment of the method of the present invention for assigning the victims affected by the emergency or catastrophe to the health center, said method is additionally to transfer each victim to the health center to which it was assigned in step (f), where the route used to remove said victim from said emergency or catastrophe area is established by means of a triangulation algorithm that will determine the relative location with respect to the DATc, where average intensity of the signals of the beacons close to the beacons will be used. used for triangulation between DATi and DATc. In a much more preferred embodiment, the generation of the exit route (18) of each victim is carried out by applying a Dijkstra algorithm and intensity averages using MA (Moving Average) filters.

In one embodiment of the method of the present invention for assigning victims affected by the emergency or disaster to the healthcare facility, X is a number between 1 and 100. Preferably, 0.5 and 35.

In one embodiment of the system of the present invention, the means for carrying out the steps of the method of the present invention [for example, determining a value of a physiological parameter in step (a), or calculating and updating, in real time , a V value for said victim based on a multivariate classification model in step (c)], comprise at least one computer program product. That is, in one embodiment of the system of the present invention, the DATi comprises at least one computer program product. Similarly, in one embodiment of each of the systems of the present invention, the DATcs comprise at least one computer program product.

In the present invention, a computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions for causing a processor to carry out aspects of the present invention.

The computer-readable storage medium may be a physical device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium may include, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. . A non-exhaustive list of more specific examples of computer-readable storage medium includes the following: a laptop floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), a programmable read and erasable. only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory card, a floppy disk, an encoded device such as punched cards or embossed structures in a slot having instructions engraved thereon, and any suitable combination of the above.

The computer-readable program instructions described herein may be downloaded to the respective computing or processing devices from a computer-readable storage medium or to an external computer or external storage device over a network, e.g., the Internet, a local area network (LAN), a wide area network (WAN) and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and sends the computer-readable program instructions for storage on a computer-readable storage medium within the computing device. /respective processing.

The computer-readable program instructions for carrying out the operations or steps of the method of the present invention may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state configuration data, or source or object code. code written in any combination of one or more programming languages, including an object-oriented programming language such as Smalltalk, C+ or similar, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may be executed entirely on the DATi and/or DATc, as a stand-alone software package, partly on the DATi and/or DATc and partly on a remote computer or server, or completely on a remote computer or server. In the latter scenario, the remote computer or server may be connected to the DATi and/or DATc over any type of network, including a local area network (LAN) or wide area network (WAN), or the connection may be made to an external computer (for example, over the Internet using an Internet service provider). In some embodiments, electronic circuits including, for example, programmable logic circuits, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute computer-readable program instructions using state information from the instructions of the program. computer-readable programs to customize electronic circuits, in order to implement aspects of the present invention.

Aspects of the present invention are described herein with reference to flowchart illustrations (Fig. 1) and/or block diagrams (Fig. 4,5) of methods or systems in accordance with embodiments and/or steps of the invention. It will be understood that each square or diamond-shaped block in the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, may be implemented by measurement techniques. physiological parameters, geolocation techniques, and/or environmental parameter measurement techniques, or computer-readable program instructions, or combinations. of the same.

These computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, so that the instructions, which are executed by the processor of the computer or other programmable data processing apparatus, create means to implement the functions/acts specified in the flowchart and/or block or blocks of the block diagram. These computer-readable program instructions can also be stored on a computer-readable storage medium that can drive a computer, a programmable data processing application.

In the present invention, real time refers to time steps defined by a maximum duration. Preferably, said maximum duration is 60 seconds, more preferably 10 seconds, even more preferably 1 second, most preferably 0.1 second. For example, if real time refers to time steps defined for a maximum duration of 10 seconds, when the DATi module sends, in real time, a signal that encodes a value of a physiological parameter of said victim to the DATc, the Maximum time between successive emissions (sends) of said signal would be 10 seconds. If, between successive emissions of the signal, the value of said physiological parameter has changed (due, for example, to a change in the victim's medical condition), the information encoded in said signal is updated. Thus, by sending at least one signal in real time, said DATi updates each value or information that is sent encoded in each signal. It is noted that the actual time referred to in each step consists of time steps defined by a maximum duration that is preferably the same for all steps of the present invention. However, said maximum duration (of, for example, the actual time of sending the signal that encodes a value or information) may be different from the maximum duration of the time step between updates of said value or said information.

The following describes in an illustrative manner (with reference to Fig. 1 where relevant) the system and steps of the method of the invention that can be put into action when an emergency or catastrophe occurs.

Once the emergency situation occurs, the system switches to “emergency” operation. Different agents, local or external security agents, can intervene in activation so that the system immediately enters “emergency” mode.

First intervention teams will go to the emergency or catastrophe area, the scope of use of the invention. These teams will be distributed among the different victims or people affected by the emergency or catastrophe, placing the DATi (Fig. 1, point 4) and, if necessary, the beacon system (Fig. 1, point 3). This system begins to monitor the different users (victims and first responders/teams), as well as their location points (location relative to the site). The monitoring system for the supervision equipment activates the accessible guidance and emergency system, formed by the network of devices (Fig. 1, point 15).

The classifier system, called the Learning System, makes decisions about the status of each victim (whether it is local to the scene of the emergency or catastrophe, or an external agent such as a person from a first intervention team) based on physiological parameters and , optionally, environmental, and available healthcare capabilities.

The DATc is responsible for centralizing the information received by the DATi at the location of the emergency. At the scene of the emergency, or once the victims are transferred to the relevant health centers, they send the information through mobile communications (for example example, of their Smartphones) so that they have the history of the user's evolution. In this way, communication is established without the need to install additional infrastructure.

The parameters that are recorded in the database are shown, as an example, in the following Table 1. What the acronyms mean is described at the bottom. The table indicates the references between the sub-tables that exist in order to communicate the information. The NN parameters must be completed on a mandatory basis, while the rest can be completed on the scene of the emergency or catastrophe, using the present invention or from the health center.

Table 1: Examples of parameters that are recorded in the database

PI: Primary Key, NN: Parameter Not null.

Examples of how this data will preferably be collected are described below.

- Electrocardiogram, for example, using bioimpedance techniques.

- Breathing rate, for example, through accelerometers placed on the trunk. - Mobility of body segments, for example, through accelerometers placed on the wrist.

- Oxygen saturation, for example, through bioimpedance techniques.

- Body temperature, for example, through bioimpedance techniques.

- Sweating

Environmental parameters:

- Air toxicity, for example, using commercial sensors.

- Toxic agents derived from NBC, for example, through commercial sensors. - Ambient temperature, for example, through commercial sensors.

Healthcare infrastructures:

- numbers of available ICUs.

- Location/proximity of the ICUs.

Preferably, the method and system display recommendations for labeling people at the site, in particular victims of the emergency and the first responders themselves. The DATi help to identify the triage mark and send information about each person automatically thanks to the Learning System. In one embodiment, the SHORT algorithm technique is included [Emergencias(2005) 17:169-175], which allows the inclusion of direct observation information. The way to incorporate it would be instructions to the team that arrives to attend to the emergency - in case it is not sanitary - in such a way that at the same time as putting on the DATi bracelet, it evaluates, for example, the consciousness, which it enters into the bracelet interface to improve the assessment of patient status. In this way, it will be the clinician, or the security personnel of the intervention authorized to do so, who relies on this information offered by the system to identify the status of the triage phase. Therefore, the different triage phases that the system can recommend, and which have to be validated by a clinician, are:

- Phase 1: resuscitation/vital emergency

For victims who need resuscitation (=Group R1)

Description: Extreme health condition that threatens the patient's life.

Treatment time: Requires immediate medical intervention.

- Phase 2: emergency

For victims who need medical attention within 1 hour of the emergency or disaster (=Group R2)

Description: High-risk situation that represents a potential threat to health status.

Time of care: You must receive medical attention within 1 hour of the emergency or disaster.

- Phase 3: urgency

For victims who need medical attention within 1 to 2 hours of the emergency or disaster (=Group R3)

Description: Acute, non-life threatening condition. Requires non-immediate medical consultation.

Time of care: You must receive medical attention within 1 to 2 hours of the emergency or disaster.

- Phase 4: minor urgency

For victims who need medical attention within 2 to 4 hours of the emergency or disaster (=Group R4)

Description: Health condition that may be acute, but does not compromise the patient's general condition and does not represent an obvious risk.

Time of care: You must receive medical attention within 2 to 4 hours of the emergency or disaster.

- Phase 5: not urgent

For victims who do not need medical attention within 4 hours of the emergency or disaster (=Group R5)

Description: Clinical condition related to acute or chronic problems without evidence of deterioration that compromises the patient's general condition. It does not represent an obvious risk to life.

Service time: Appointment for outpatient consultation.

The system is completed with a remote monitoring system that allows monitoring, updating of the information contained in the beacons and control, both in normal situations and in emergency situations. The system consists of a classifier to identify the status of each victim based on the information recorded by the DATi that follows the triage protocol and regulations:

- Phase 1 (resuscitation/vital emergency): red.

- Phase 2 (emergency): orange.

- Phase 3 (urgency): yellow.

- Phase 4 (minor urgency): green.

- Phase 5 (non-urgent): blue

In addition, the system informs the first intervention user interface of the geolocated points of each individual (victim and person, as first intervention personnel) through visualization techniques, preferably on wireless devices such as mobile phones or tablets, and GIS maps. These geolocated points for greater speed will preferably be displayed with different color codes, according to the colors assigned to Phases 1 to 5 of triage, above, so that the intervention personnel are guided by the system to the location of each victim according to your triage phase, by the closest available route. Each DATi determines the location of the victim it is placed in the emergency zone. In addition, it allows access to the information on the results of the Learning System in real time along with the information from the Acquisition System to facilitate your work, without problems of oral communications, language, etc. with the individual geolocated in the emergency area. That is, if we take the example of a citizen who does not speak the language of the intervention agent, for reasons of cognitive understanding or who cannot communicate due to their physical situation.

Therefore, once the user is located (Fig. 1, point 16), first responders are notified of the type of triage label suggested and all the information of interest related to said situation along with the evacuation/transport route. of the individual (Fig. 1, point 19). This notification is preferably made through your mobile device, which will receive and interpret the information appropriately, through a mobile application, or, if the user's wireless device does not have that mobile application, the system will send a complete information package to interpret and notify the user, and if necessary, install said application.

At that moment, in addition, this information is sent to an "emergency database" encrypted and respecting privacy regulations. This information may be used by entities interested in this type of situation (self-protection services, building security entities in which they are installed and emergency services, security and civil protection) to be able to monitor the position of users in an emergency situation, and if necessary, increase the number of aid personnel knowing the real-time information of their location.

Next, thanks to the information processed by the monitoring server, the system or method sends route instructions to the intervention personnel device to the closest clinical entity (health center) according to the type of triage evaluation. In a specific embodiment, different alternatives are offered to the nearest health center, but the system or method, respectively, will have knowledge at all times of the location of the user (victim) (Fig. 1, point 23), through detection techniques. location used in the same action as point 16 of Fig.1:

- If so, the position of the user's location point is updated (Fig. 1, point 23), and its location is also sent in parallel to the "emergency database".

- Otherwise, it is checked if the user deactivated their location (Fig. 1, point 27), in which case the procedure is stopped (Fig. 1, point 28). If you did not deactivate it, it has been lost, and therefore the new coordinate must be recalculated using the same location algorithm, and sending the information again as in point 19 of Fig. 1.

Finally, it is checked if the user has arrived at the clinical center or centers that the system has recommended, if the transfer to the pertinent clinical entity has been carried out, if it has been to another center the system will have to notify it so that the status is known. and the location of the victims at all times (Fig. 1, lowest decision box):

- If so, the user and the intervention personnel will be notified that the transfer process has ended (Fig. 1, points 26 and 28), and the physiological acquisition process using bioimpedance techniques would remain inactive, since the patient itself hospital will follow its own protocols.

- If not, it is checked again if you manually deactivated the localization (Fig. 1, point 27), in which case the procedure is stopped (Fig. 1, point 28). If I do not deactivate the route, it has been lost, and therefore the position must be recalculated using the same algorithm and sending the information again as in point 19 of Fig. 1.

Another point to note is that during the intervention and transfer of users (victims) the location or proximity of clinical units or centers that can care for the individual being transferred will be indicated in emergency mode. In addition, categorization and labeling will be carried out for the dataset, allowing us to obtain a corpus that does not exist today for triage classification models.

Examples

When an emergency or catastrophe occurs, the first assistance team without medical knowledge must first deploy the system of the invention that allows executing a method to locate, establish a rescue route and prioritize the movement of victims to the centers. appropriate care doctors to care for each victim, based on the categorization that the system assigns to each victim based on their physiological parameters and severity of their location.

The first steps of the victim triage procedure in the area where the emergency or catastrophe has occurred always include the placement and activation of two fundamental elements: a personal device (DATi) on each of the victims, and an automatic device central triage control (DATc), while the last steps always include the processing of the data obtained by the DATi and sent to said DATi. However, depending on whether the emergency or catastrophe occurs in an open space (exterior), without areas with walls or ceilings, or in a confined space, with walls or ceilings (building or other interior space), the geolocation of the victims is can be done differently, as shown with the following examples.

Example 1: Emergency or catastrophe produced in outer space

An emergency (earthquake) was simulated in an open, square and diaphanous space (exterior), without areas with walls or ceilings, where:

- each "victim" of said emergency was simulated by a mannequin, with a total of 50 victims;

- the intervention personnel listed 5 natural persons;

- the physiological parameters of each victim (mannequin), and the environmental parameters in the area closest to each victim were simulated, in particular by values of heart rate and limb mobility in the case of simulated physiological parameters, and by values of ambient temperature and air toxicity in the case of environmental parameters;

- each health center (5 in total, within a 35 km radius of the emergency) was simulated virtually; and

- the data on the geolocation, area of specialization and occupation of the emergency room of each health center were simulated.

Intervention staff placed the devices of the present intervention on each victim as follows. On the one hand, a part of the team placed and activated on each of the victims (who have been identified visually or by identifying signals emitted from terminals they carry), a personal device (DATi, Fig. 5), according to step (a) of the method of the present invention, which acquired physiological parameters, environmental parameters and information about its geolocation. As it is an emergency in an open (outdoor) space, the geolocation of each victim affected by said emergency could have been carried out through or complemented by a GPS/GNSS system. However, for consistency with Example 2, said geolocation was carried out with a beacon system (BAL) (Fig. 2) for localization through triangulation of the signals coming from the personal devices (DATi) and the central device (DATc). . In this example, said DATc (main DAT) was located <25 m from each DATi and each beacon.

The personal devices (DATi) that the emergency services placed on the victims were "activated" through an internal communications module (although in the event of an unsimulated emergency or catastrophe, they are activated as soon as they come into contact with the skin). of the victim), and through said internal communications module, signals are sent to the central control device (DATc), in real time (updated every 5 seconds). For a given victim, each signal encoded the following information:

- a value of a physiological parameter of said victim, as defined above.

- information about the geolocation of said victim; either

- a value of an environmental parameter, as defined above.

All of this encoded victim information was stored in datasets in the central control device (DATc) memory. That is, the DATc collected these signals and, therefore, said data, and centralized them.

The central control device (DATc, Fig. 4) had its own means of power supply, isolated from a low-voltage electrical network existing in the area, in addition to a storage system based on supercapacitors, which served as support against to failures of the energy supply itself. In addition to the above, the DATc device had a means of communication that allowed it to connect wirelessly with the DATi within the emergency zone (and, in the event of an unsimulated emergency or catastrophe, with the members of any emergency service, security, civil protection or medical care services), through a 4G wireless communication system that had coverage in the area where the emergency "happened."

Both the central control device (DATc) and the personal devices (DATi) had a means of signaling so that these devices were visible when conditions of low light or darkness existed. Additionally, both types of devices, central (DATc) and personal (DATi), had a proximity identification module through a wireless communication module, type RFID and NFC, in any of the active and passive modalities.

The central control device (DATc) used internally comprised an electronic system, mainly a microcontroller, integrating a database and a machine learning module that runs a computer program and a database. Once the first signals from at least one DATi were received, said computer program was responsible for carrying out in real time the control of steps (c) and (d) of the triage method of this invention, and fundamentally the execution of a model of multivariate classification to assign for each victim, in real time, a value of its severity, V, based on the physiological and/or environmental parameters in triage and, in real time, determine and update the medical specialty required for each victim using its value V. The database was responsible for storing all the necessary information and intermediate calculations.

The computer program classified each victim into one of the following groups:

- Group R1: victims who need resuscitation;

- Group R2: victims who need medical attention within 1 hour of the emergency or disaster;

- Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster;

- Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster;

- Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster,

The computer program also determined, in real time, the medical specialty required by said victim by the central control device (DATc) using the calculated V value, where the medical specialty required by a given victim with a V value falling within:

- of the range of V values calculated using said multivariate classification model for a population of people in need of resuscitation, was that of group R1;

- of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, was that of group R2;

- of the range of V values calculated using said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, was that of group R3;

- of the range of V values calculated using said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, was that of group R4; and

- of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, was that of group R5.

Finally, in real time, the central control device (DATc) will be responsible for assigning to each victim the health center registered in the DATc database, whose Euclidean distance to the victim was smaller and had an area of specialization and had emergency availability (factors indicative of having technicians to care for that type of victim).

The central control device (DATc) was responsible for representing, in real time, on the personal devices of the emergency team, whether medical or not, a diagram establishing the route to each victim and their evacuation route, also indicating the priority group in their care and the health center to which each of the victims of that emergency should be transferred.

Once the simulation has been repeated (with changes to the values of the physiological parameters, the environmental parameters, and the information on the geolocation of the victims, in addition to changes to the area of specialization and occupation of the emergency of each health center), the module automatic learning of the central control unit (DATc), using the real-time dataset received during the emergency (current dataset) and a dataset from previous emergencies (historical dataset), allowed the triage system to train and each time more effective to assign the severity value "V" to each victim, also improving the speed and accuracy of victim triage.

And finally, the central control device (DATc), was in charge, through its communications module, of sending all the information collected from the DATi to a remote server in the cloud, which would allow several DATc to work in a coordinated manner and Likewise, the historical emergency dataset can be used in the learning and execution process of any central control device (DATc) active at that moment.

Example 2: Emergency or catastrophe occurred in a building or other interior space

An emergency (earthquake) was simulated in a confined and open space (university building), with walls and ceilings, in the same way as in Example 1. Said space is a 1-story site, open space of 250 m2 in total, where:

- each floor would have a structure like the one represented in Figure 3.

- the space is separated into two wings: the right wing and the left wing of 125 m2 each, each with 2 emergency exits respecting the regulations in terms of distance and availability.

- Figure 3 corresponds to an example of installation of the present invention, and within the location and distributed the DATi, represented in Fig. 4, also in the right wing of the plant of the DATc device represented in Fig. 5.

However, since it was an emergency in an indoor space, the geolocation of each victim (in this example, each) affected by said emergency was carried out exclusively through a beacon system (BAL) for location through triangulation of the signals coming from the personal devices (DATi) and the central device (DATc). In addition, the central control device (DATc) was powered through the connection of the power module to the low voltage electrical network of the building or closed space.

Thus, while the intervention personnel placed the devices of the present intervention on each victim, they also installed the beacons in said building (see Fig. 3) so that each DATi and the DATc could receive signals from at least two beacons and thus establish the geolocation of each victim.

Although possible in the event of an unsimulated emergency or catastrophe, the quality of communications between the central control device (DATc) with external emergency, security, civil protection or medical care services could be attempted to improve through the wired networks of the building or closed space.

Example 3: Estimated automated triage time with DATc and DATi

Below is the calculation related to the time invested in evacuating a victim from the interior space defined in Example 2, following the evacuation route established therein for the evacuation of said victim.

Based on the above, the following formula was developed with the objective of obtaining the Evacuation Time (TE) and transfer of a victim from the emergency or catastrophe area:

TE = TD TA TC TDAT TPE TI (Equation 1)

where

- TD is the alarm detection time,

- TA is the alarm start time,

- TC is the confirmation time,

- TDAT is the classification time for the triage phase based on the data processed

- TPE is the evacuation time itself.

- TI is the uncertainty time related to loss of victims or exit block parameters,

Explanatory note of these parameters:

For TD, the following is the starting point: in an emergency or catastrophe situation, manual activation (non-medical security personnel, who must visually identify the situation) could take about 10 minutes. On the other hand, it could be 1'' or less if the building has an automated alarm center (not used when carrying out this example).

The TA measurement is subjective to the type of building and its security mechanism, and will be based on the protocol defined by the self-protection systems; in the example it has been defined as 15'', although said alarm was not used.

With respect to TC, a confirmation delay time of 15'' is considered.

The TDAT measurement is calculated to be automatic in less than 2.30'' .2'' of sampling, 15'' of processing, 15'' of sending a response to the interface of the head of the emergency intervention and simultaneous sending to the personnel with triage route visualization interfaces.

Both TPE and TI, which are explained in particular in the following paragraphs, vary depending on the user profile and the evacuation system installed.

2.1 Estimated time without the system of the present invention:

2.1.1 In the case of a victim without disabilities and without the system of the present invention, taking into account an alarm with an automated center (the best case), for the example location and using the formula of Equation (Equation 1), the TE value was:

- The speed traveled at any point of the location in Fig. 3 towards another point which is estimated to be: one meter per second and a vertical displacement of 8 stairs.

- Taking this speed into account, the meters that must be traveled from the furthest point in Fig. 3 until leaving the building and with the values TD=1', TA=15'' and TC=15'' explained above, The following estimate has been made for TE based on Equation (Equation 1):

TE = 1’ 15’’ 15’’ 2.01’’ 2.30’’+TI ^ TE = 5’36’’ TI

Regarding the TI value (Time of Uncertainty), it was taken into account that the TE value can be altered by TI if:

- The intervention personnel do not know the facility, if they suffer any type of crisis, or if there is any physical impediment during the tour.

- For example, considering that at least one exit may be blocked by the incident itself, the user must necessarily use another exit, even if this means a longer evacuation route. Even, in the worst case scenario, you may have decided to go to the nearest one and, therefore, have to retrace your path, adding to this time the path to the other available emergency exit.

- This would mean that it would have to take at least twice the estimated path TPE, leaving TI = 2*TPE. Thus TE was calculated in the following way:

TE = 1’ 15’’ 15’’ TPE TI,

TE = 1’ 15’’ 15’’ 2.30’’ TPE 2*TPE,

TE = 1’ 15’’ 15’’ 2.01’’ 2*2.01’’ 2.30’’ ^ TE = 9’63’’

Therefore, a victim without disabilities would take about 9'33'', more than double the recommended time to leave the location due to the IT, and would also be at the expense of public address information or security personnel to know the exit of the victim. emergency not locked.

2.1.2 In the case of a victim with a disability (physical, sensory or cognitive) and without the system of the present invention, taking into account an alarm with an automated center (the best case scenario), for the location and using the formula of Equation (Equation 1), based on the non-autonomy in systems outside the present invention, the TED value is identified as the TE value for victims with disabilities and will be:

TED = TE Time_Dr Time_External_Security_Services

where:

- TED is the time spent evacuating a disabled victim, - TE is the evacuation time without further attributes obtained from the equation in the previous example (TE=7'33'' in the worst case),

- Time_dr is the time spent in notifying the location of the disabled user (estimated minimum 30''-1' from the point of the person in charge of evacuation information to the furthest point in the example location),

- External_security_service_time is the time it may take for external evacuation services to arrive for a person who has orientation problems, due to their disability or reduced mobility, who has not received the information in a timely manner. It is estimated between 5-20 minutes to reach the user in question.

The result, in the worst case, therefore was:

TED = 7'33'' 1' 15' = 25' 33''.

2.2 Estimated time with the system of the present invention:

Explanatory note: The system of the present invention can be programmed to program the nearest emergency transfer route, in connection with the detection system.

For this approach we will use the variables: TEG1 as the TE time invested with the present system; while TEG2 is the TE time invested with the present location and monitoring system in triage for victims with disabilities.

2.2.1 In the case of a victim without disabilities and WITH the system of the present invention, taking into account an alarm with an automated center (the best case), for the building BUILDING_DII and using the formula of Equation (Equation 1 ), the TE value was:

TEG1 = 1' 15'' 15'' 2.01'', TEG = 3'36''

2.2.2 In the case of a victim WITH a disability and WITH the system of the present invention, taking into account an alarm with an automated center (the best case), for the building BUILDING_DII and using the formula of Equation (Equation 1 ), the TE value was:

TEG2 = TEG1

In summary, taking into account the monitoring and transfer time of Equation 1, analyzing the values obtained for TE, TED without the system of the present invention, it can be concluded that the present invention would allow, in a more autonomous way and with a time reduction of 84%, the evacuation and transfer to health centers of all victims affected by emergency or catastrophe situations.

Claims (15)

1. An automated triage method to care for victims affected by an emergency or catastrophe, characterized by consisting of the following stages: (a) place and activate in at least one victim affected by the emergency or catastrophe, a personal device (DATi) that has at least one module that sends, in real time, at least one signal to a central control device (DATc ), where each signal encodes a value of a physiological parameter of said victim, (b) activate said central control device (DATc) in the area of the emergency or disaster, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device (DATi) , placed and activated according to step (a), and storing, in real time, said value of the physiological parameter encoded by said signal within a data set of said database, (c) calculating and updating in real time, a V value for said victim by said central control device (DATc), based on a multivariate classification model generated from a value of at least one physiological parameter of said victim, quantified by measuring impedance and/or by monitoring movement, in particular the presence of seizures, a value that is stored in said database, where said multivariate classification model is capable of assigning each victim to one of the following groups: - Group R1: victims who need resuscitation; - Group R2: victims who need medical attention within 1 hour of the emergency or disaster; - Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster; - Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster; - Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster, (d) determine, and update in real time, the medical specialty required by said victim by the central control device (DATc), using the V value calculated by the multivariate classification model of step (c), where the medical specialty required by a given victim with a value V is given when said value V of the victim falls within: - of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and - of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5. 2. The method according to claim 1, wherein said method additionally allows the assignment, to the health center, of said victims affected by the emergency or catastrophe, where: (A) each signal sent by said module to the central control device (DATc) in real time in step (a), encodes: - a value of a physiological parameter; either - information about the geolocation of said victim; (B) the central control device, in real time in step (b), stores, - said value of the physiological parameter encoded by said signal; or - said information on the geolocation encoded by said signal, within said set of data of said database, for which said method additionally comprises the following steps: (e) updating, in real time, the occupancy in emergencies according to the medical specialty of each health center within a radius of X km from the area of the emergency or disaster, where given medical condition, is determined, for a given instant of time, by a Voronoi diagram, according to the time zone of said area of the emergency or catastrophe, using the Euclidean distance, where for each victim affected by the emergency or catastrophe for whom has performed step (a), the next step is performed: (f) determine, by the central control device, the geolocation of said victim based on the information on his geolocation, and assign him the health center registered in the database that is capable of treating the medical specialty determined as required by said victim. victim in step (d), where said health center is one that has a geographic coverage area within which the geolocation of said victim falls, at the instant of time of assigning said victim to a health center. 3. The method according to claim 2, wherein the geolocation of each victim affected by the emergency or catastrophe, for whom step (a) has been performed, is performed by: - a GPS/GNSS system; I - a beacon system. 4. The method according to any of claims 1 to 3, wherein the physiological parameter is also determined by measuring the heart rate. 5. The method according to any of claims 1 to 4, wherein the physiological parameters are selected from the group consisting of: the oxygen saturation in the blood of the victim, the state of the circulatory system of the victim, the arterial blood gas level and venous pressure of the victim, the body temperature of the victim, the heart rate of the victim, the breathing rate of the victim, the sweating of the victim and the onset of seizures of the victim. 6. The method according to any of claims 1 to 5, wherein said multivariate classification model is developed by taking into account different population cohorts according to sex and age by: (i) perform step (a) for each person of: - a population of people in need of resuscitation; - a population of people who need medical attention within 1 hour of the emergency or disaster; - a population of people who need medical attention within 1 to 2 hours of an emergency or disaster; - a population of people who need medical attention within 2 to 4 hours of an emergency or disaster; and - a population of people who do not need medical attention within 4 hours of the emergency or disaster; (ii) calculate a multivariate classification model of at least two values, where each value is a value of a physiological parameter of said victim stored in said database, and where said multivariate classification model assigns each person of a given population to said population. 7. The method according to any of claims 1 to 6, where: (I) each signal sent by said module to the central control device (DATc), in real time in step (a) and saved in said database, encodes: - a value of a physiological parameter; - information about the geolocation of said victim; either - a value of an environmental parameter; (II) the central control device, in real time in step (b), stores: - said value of the physiological parameter encoded by said signal; - said geolocation information encoded by said signal; either - said value of an environmental parameter encoded by said signal; (III) the multivariate classification model assigns a victim to a given population of victims according to the environmental and/or physiological parameters stored in said database. 8. The method according to claim 7, wherein said multivariate classification model is developed by taking into account different population cohorts according to sex and age by: (i) perform step (a) for each person of: - a population of people in need of resuscitation; - a population of people who need medical attention within 1 hour of the emergency or disaster; - a population of people who need medical attention within 1 to 2 hours of an emergency or disaster; - a population of people who need medical attention within 2 to 4 hours of an emergency or disaster; and - a population of people who do not need medical attention within 4 hours of the emergency or disaster; (ii) calculate a multivariate classification model of at least two values where each value is either a value of a physiological parameter or a value of an environmental parameter of said victim stored in said database, and where said multivariate classification model assigns each person in a given population to that population. 9. The method according to any of claims 7 and 8, wherein each environmental parameter is selected from the group consisting of: the toxicity of the air, the presence of a nuclear, biological or chemical toxic agent, the presence of smoke and the ambient temperature . 10. The method according to any of claims 2 to 9, wherein the assignment of said victim, for whom step (d) has been carried out, to the nearest health center is established by solving a multi-criteria mathematical programming model, based on at least the following criteria: - Distance to the hospital center; - Area of specialization; - Occupation of the emergency; and - The medical specialty required by said victim, determined in step (d). 11. The method according to any of claims 2 to 10, which additionally is a method for transferring said victim to the health center to which it was assigned in step (f), where the route used to remove said victim from said emergency area or catastrophe is established through a triangulation algorithm that will determine the relative location with respect to the central control device (DATc), where average intensity of the signals of the beacons close to the beacons used for triangulation between personal devices will be used. (DATi) and the central control device (DATc). 12. The method according to any of claims 1 to 11, where X is a number between 1 and 100. 13. An automated triage system to care for victims affected by an emergency or catastrophe, characterized by consisting of: (a) means for placing and activating in at least one victim affected by the emergency or catastrophe, a personal device (DATi) that has at least one module that sends, in real time, at least one signal to a central control device (DATc), where each signal encodes a value of a physiological parameter of said victim, (b) means for activating said central control device (DATc) in the area of the emergency or catastrophe, where said central control device (DATc) comprises a database and a module that receives the signals sent by each personal device ( DATi), placed and activated according to step (a), and store, in real time, said value of the physiological parameter encoded by said signal within a data set of said database, (c) means for calculating and updating in real time, a V value for said victim by said central control device (DATc), based on a multivariate classification model generated from said value of at least one physiological parameter of said victim , quantified by a measurement of impedance and/or by monitoring movement, in particular the presence of seizures, a value that is stored in said database, where said multivariate classification model is capable of assigning each victim to one of the following groups: - Group R1: victims who need resuscitation; - Group R2: victims who need medical attention within 1 hour of the emergency or disaster; - Group R3: victims who need medical attention within 1 to 2 hours of the emergency or disaster; - Group R4: victims who need medical attention within 2 to 4 hours of the emergency or disaster; - Group R5: victims who do not need medical attention within 4 hours of the emergency or disaster, (d) means to determine, and update in real time, the medical specialty required by said victim by the central control device (DATc), using the V value calculated by the multivariate classification model of step (c), where the medical specialty required by a given victim with a V value is given when the victim's V value falls within: - of the range of V values calculated by said multivariate classification model for a population of people who need resuscitation, is that of group R1; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 hour of the emergency or catastrophe, is that of group R2; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 1 to 2 hours of the emergency or catastrophe, is that of group R3; - of the range of V values calculated by said multivariate classification model for a population of people who need medical attention within 2 to 4 hours of the emergency or catastrophe, is that of group R4; and - of the range of V values calculated using said multivariate classification model for a population of people who do not need medical attention within 4 hours of the emergency or catastrophe, is that of group R5. 14. The system according to claim 13, wherein said system additionally allows the assignment to the health center of said victims affected by the emergency or catastrophe, where: (A) each signal sent by said module to the central control device (DATc) in real time in step (a), encodes: - a value of a physiological parameter; either - information about the geolocation of said victim; (B) the central control device, in real time in step (b), stores, - said value of the physiological parameter encoded by said signal; or - said geolocation information encoded by said signal, within said data set of said database, for which said system additionally comprises: (e) means to update, in real time, emergency occupancy according to the medical specialty of each health center within a radius of X km from the area of the emergency or disaster, where X is a number between 0.5 and 1000 and where the geographical area of coverage of each health center capable of treating a given medical specialty is determined, for a given instant of time, by a Voronoi diagram, according to the time zone of said area of the emergency or catastrophe using the distance Euclidean, where for each victim affected by the emergency or catastrophe for whom step (a) has been performed, the following are used: (f) means to determine, by the central control device (DATc), the geolocation of said victim based on the information about his geolocation, and assign him the health center registered in the database that is capable of treating the medical specialty determined as required by said victim in step (d), where said health center is one that has a geographic coverage area within which the geolocation of said victim falls, at the instant of time of assigning said victim to a health center. 15. The system according to claims 13 and 14, where: (i) the means to - calculate and update in real time, a V value for said victim - determine, and update in real time, the medical specialty required by said victim comprise at least one computer program product that includes the use of Artificial Intelligence and machine learning algorithms; (ii) the means to place and activate a personal device (DATi) on at least one victim affected by the emergency or catastrophe include: - bioimpedance measurement means, selected, among others, from the group consisting of: impedance spectrometry (EIS), impedance plethysmography (IPG) and bioelectrical impedance (BIA); - means of measuring heart rate, selected, among others, from the group consisting of: cardiographic bioimpedance (ICG) and transthoracic electrical impedance plethysmography (transthoracic impedance); I - means of monitoring movement, preferably including the use of accelerometers placed on the victims' torso; (iii) the means for activating said central control device (DATc) in the area of the emergency or catastrophe, and storing, in real time, said value of the physiological parameter encoded by said signal, comprise: - a module that receives each signal; a database that stores in real time the value encoded by said signal.