JP4059867B2 - Sleep analysis apparatus and program for providing sleep analysis function to computer - Google Patents

Description

The present invention relates to a sleep analysis apparatus and a program for giving a sleep analysis function to a computer.

  Conventionally, sleep analysis is generally performed with reference to a sleep depth graph shown in FIG.

The graph of the figure is data of the sleep state of the subject's day, the horizontal axis is the elapsed time after entering the floor, and the vertical axis is the sleep depth. As the sleep depth, for example, as shown in the drawing, in addition to the awake state (W) and the REM (Round Eye Moving) state (R), four stages of sleep depths are set according to the sleep depth. The data in the figure is usually calculated by mounting a measuring device on a subject, measuring brain waves, heart rate, respiration, skin temperature, etc., and processing the measurement data using an existing polygraph method. In addition, if the method of the following patent document 1 which the applicant applied jointly with the school corporation Ritsumeikan is adopted, the sleep depth of the subject can be estimated without restriction and with high accuracy.
Japanese Patent Application No. 2002-251394

  In the graph generated by the conventional method, since the sleep depth is expressed by a qualitative variable, the sleep state of the subject cannot be properly analyzed and evaluated unless a specialist such as a doctor is used.

  However, in recent years, the number of people who suffer from sleep has increased rapidly with the progress of an aging and high-stress society. Under such circumstances, sleep is relatively reliable without relying on specialists such as doctors. Realization of an apparatus and system that can perform analysis quickly and easily is desired. However, since the sleep depth is expressed as a qualitative variable in the above graph, if a computer or sleep analysis device is used to execute sleep analysis using this, a doctor or the like when analyzing and evaluating the qualitative variable Therefore, an enormous knowledge database corresponding to the analysis method and an arithmetic processing program using the same are required, and simple and quick analysis evaluation cannot be realized. In addition, from the graphs expressed by qualitative variables, various evaluation factors such as “sleep rhythm”, “head rest”, “body rest”, and “good sleep” are quantitatively analyzed and evaluated. It is extremely difficult.

Therefore, the present invention aims to solve such a problem and provide a new sleep analysis method capable of easily and quickly performing sleep analysis with relatively high reliability while using the graph data of the sleep depth. To do.

  The present invention generates data on the appearance ratio of sleep depth (quantitative variable) from the data on the sleep depth plotted on the time axis (qualitative variable), processes the data on the appearance ratio, Analytical evaluation is performed on evaluation elements such as “rhythm”, “head rest”, “body rest”, and “good sleep”. In other words, by converting the sleep depth, which was a qualitative variable, into the appearance ratio of the sleep depth, which is a quantitative variable, “sleep rhythm”, “head rest”, “body rest”, “sleep comfort” Thus, it is possible to quantitatively evaluate various evaluation elements such as the above, and it is possible to realize sleep analysis with relatively high reliability while simplifying the processing.

  The features of the invention according to each claim are as follows.

The invention according to claim 1 is a data generation means for calculating an appearance ratio of a sleep depth of a predetermined level or more for each predetermined time unit from data on sleep depth plotted on the time axis, and fluctuation of the appearance ratio on the time axis. A storage unit for storing an evaluation rule for evaluating a sleep rhythm based on a cycle time of the cycle; and a cycle time of the variation cycle is detected from the appearance ratio calculated for each predetermined time unit by the data generation unit, and the cycle An evaluation result calculating means for evaluating time according to the evaluation rule and calculating an evaluation result of the sleep rhythm in the sleep .

The invention of claim 2 is the sleep analyzer according to claim 1 , wherein the storage means stores a score set according to a length of one cycle time of the fluctuation cycle as the evaluation rule , The evaluation result calculation means calculates the score of the sleep rhythm from the total score obtained by obtaining the scores for all fluctuation cycles detected for the sleep based on the score information stored in the storage means. It is characterized by.

According to a third aspect of the present invention, data generation means for calculating an appearance ratio of a sleep depth of a predetermined level or more from data on sleep depth plotted on the time axis, and evaluation of head rest during sleep based on the appearance ratio An evaluation result that evaluates the appearance ratio calculated by the data generation unit according to the evaluation rule stored in the storage unit and calculates an evaluation result of head rest in the sleep A sleep analyzer characterized by comprising a calculating means .

According to a fourth aspect of the present invention, in the sleep analyzer according to the third aspect , the data generation means calculates an appearance ratio of a sleep depth of a predetermined level or more for each predetermined time unit, and the storage means is on a time axis. The score set according to which level the upper limit of the appearance ratio reaches during one cycle period of the appearance ratio fluctuation cycle is stored as the evaluation rule, and the evaluation result calculation means The score for all the fluctuation cycles detected for is obtained based on the score information stored in the storage means, and the rank of the head rest is calculated from the total score obtained by totalizing the scores.

The invention according to claim 5 is a data generation means for calculating an appearance ratio of the sleep depth at the REM level from the data regarding the sleep depth plotted on the time axis, and evaluates the rest of the body during sleep based on the appearance ratio. storage means for storing the evaluation rule, calculates the data generation means and evaluated according to the evaluation rules stored the occurrence ratio calculated in the storage means by calculating the evaluation results of the rest of the body in the sleep evaluation results A sleep analyzer characterized by comprising: means.

According to a sixth aspect of the present invention, in the sleep analysis device according to the fifth aspect , the data generation means calculates an appearance ratio of sleep depth at the REM level for each predetermined time unit, and the storage means is on the time axis. The score set according to which level the upper limit of the appearance ratio reaches during one cycle period of the appearance ratio fluctuation cycle is stored as an evaluation rule, and the evaluation result calculation means detects the sleep The scores for all the fluctuating cycles are obtained based on the score information stored in the storage means, and the rest rank of the body is calculated from the total score obtained by totalizing the scores.

According to a seventh aspect of the present invention, there is provided data generating means for generating an appearance ratio of a sleep depth of a predetermined level or more for each predetermined time unit from data relating to sleep depth plotted on the time axis, and the appearance ratio on the time axis. From the appearance ratio calculated for each predetermined time unit by the storage means for storing an evaluation rule for evaluating the goodness of sleep based on the time until the appearance ratio first rises when plotting detecting the time until the appearance ratio initially rises on the time axis, the evaluation result calculated to calculate the evaluation results of the goodness of falling asleep in the sleep and evaluated according to the evaluation rules, this time stored in said storage means A sleep analyzer characterized by comprising: means.

The invention of claim 8 is the storage device according to claim 7 , wherein the storage means stores, as the evaluation rule, a score set in accordance with a length of time until the appearance ratio first rises. The calculating means is characterized in that a score for the time to stand up detected for the sleep is obtained based on the score information stored in the storage means, and the sleepiness rank is calculated from the score.

The invention according to claim 9 is a data generation means for calculating an appearance ratio of a sleep depth equal to or higher than a predetermined level from data on sleep depth plotted on the time axis for each predetermined time unit, and plots the appearance ratio on the time axis. Storage means for storing an evaluation rule for evaluating the awakening based on the slope at which the appearance ratio last falls, and the appearance ratio calculated for each predetermined time unit by the data generation means appearance ratio detects the inclination when falling at the end on the time axis, the evaluation result calculated to calculate the evaluation results of the goodness of awakening in the sleep and evaluated according to the evaluation rules stored the inclination in the storage means A sleep analyzer characterized by comprising: means.

According to a tenth aspect of the present invention, in the sleep analyzer according to the ninth aspect , the storage means stores a score set according to a slope when the appearance ratio falls last as the evaluation rule. The evaluation result calculation means obtains a score for the inclination detected for the sleep based on the score information stored in the storage means, and calculates the rank of the awakening from the score. .

The inventive concepts described in claims 1 to 10 can be grasped as a program for providing a sleep analysis function to a computer, as described in claims 11 to 20 .

Of the above claims, claims 1 and 2 show a configuration for analyzing and evaluating “sleep rhythm”, and claims 3 and 4 have a configuration for analyzing and evaluating “head rest”. Claims 5 and 6 show the structure for analyzing and evaluating "body rest", and Claims 7 and 8 show the structure for analyzing and evaluating "good sleep", and claim 9 Although 10 and 10 show the structure when evaluating and analyzing “good awakening”, the invention of each claim is only when the sleep analyzer executes only one of these evaluation elements. In addition, even when all or a part of these evaluation elements are combined and executed as appropriate, and when the means for analyzing other evaluation elements are further combined, the corresponding evaluation is performed. Suitable as an element evaluation and evaluation tool It is those that can be.

Similarly, the inventions according to claims 11 to 20 not only provide a computer with a function of executing only one of the above evaluation elements, but also appropriately combine all or a part of these evaluation elements. The present invention can be applied to a case where a function to be executed is given to a computer, and to a case where a function that analyzes other evaluation elements is further given to a computer.

  The features of the present invention will become more apparent from the following description of embodiments.

However, the following embodiment is merely one embodiment of the present invention, and the meaning of the term of the present invention or each constituent element is not limited to that described in the following embodiment. Absent.

According to the present invention, sleep depth data that is a qualitative variable is converted into data relating to the appearance ratio of sleep depth that is a quantitative variable, and each evaluation element is analyzed and evaluated using the converted data. Therefore, various evaluation factors such as “sleep rhythm”, “head rest”, “body rest”, “good sleep”, etc. can be quantitatively evaluated. It is possible to simultaneously provide a highly reliable sleep analysis result.

  Embodiments of the present invention will be described below with reference to the drawings.

  First, FIG. 1 shows a configuration of a sleep analysis system according to the embodiment. As shown in the figure, the sleep analysis system processes a biological information measuring device for measuring biological information (heart rate, respiratory rate, body movement, etc.) and data (measurement values) supplied from the biological information measuring device. And a sleep analyzer that performs sleep analysis.

  Here, the biological information measuring apparatus processes, for example, a measurement instrument (pad, etc.) worn by the subject and a signal from the measurement instrument, and the biological information of the subject (electroencephalogram, heart rate, respiration, skin temperature, etc.) ). The sleep analyzer is configured by installing sleep analysis software (program, database) in a general-purpose personal computer or the like, for example. In addition, the sleep analysis device can be configured as a device in which software (program, database) for executing functions necessary for the CPU is mounted in advance in a built-in ROM (Read Only Memory) or the like.

  FIG. 2 shows a configuration example in the case where software for sleep analysis is installed in a general-purpose personal computer. When a disk (such as a CD-ROM) holding sleep analysis software is loaded into the disk drive, the software is read from the disk and stored in the hard disk. When this software is activated, a corresponding program and database are expanded from a hard disk onto a RAM (Random Access Memory), and a function corresponding to the program is executed by a CPU (Central Processing Unit).

  FIG. 3 shows the functions executed by the sleep analyzer as function blocks. As illustrated, the sleep analyzer includes a sleep depth estimation processing unit 101, a RAM 102, an appearance ratio conversion processing unit 103, an evaluation result calculation processing unit 104, an evaluation rule storage unit 105, and a sleep type classification processing unit 106. The functional block consisting of Note that the RAM 102 illustrates an area used as a work RAM at the time of sleep analysis in the RAM shown in FIG. 2 for convenience.

  The sleep depth estimation processing unit 101 performs an arithmetic process on the sleep state data of the subject measured by the ecological information measurement device in a processing step according to the above polygraph method, for example, and the sleep depth as shown in FIG. Calculate the data. The RAM 102 temporarily stores the processing results of each unit.

  The appearance ratio conversion processing unit 103 calculates a movement appearance ratio n-M.A.R. (S, t) every n minutes from the sleep depth data calculated by the sleep depth estimation processing unit 101. Here, the movement appearance ratio n-M.A.R. (S, t) is calculated according to the following equation.

  Here, the epoch number is a division number when the n minutes are divided every T minutes. Therefore, SS (s, t) = T when the sleep depth Stage (t) at the timing of the epoch number t is at the set value s, and SS (s, t) = 0 when other than the set value s. The above equation (1) adds SS (s, t) in all epoch numbers, and from the ratio of the added value in the n minutes, the movement appearance ratio n-MAR (s, t) in the n minutes is calculated. calculate.

  A specific calculation example of the movement appearance ratio n-M.A.R. (S, t) will be exemplified later in the description of the operation of the sleep analyzer.

  The evaluation result calculation processing unit 104 processes the moving appearance ratio data calculated by the appearance ratio conversion processing unit 103 according to the evaluation rules held in the evaluation rule storage unit 105, and performs “sleep rhythm” and “head rest”. ”,“ Body rest ”,“ Good sleep ”, and“ Good awakening ”evaluation results are calculated. In addition, the sleep depth data calculated by the sleep depth estimation processing unit 101 is processed according to the evaluation rule held in the evaluation rule storage unit 105 to calculate an evaluation result for the evaluation element of “halfway awakening”.

  The evaluation rule storage unit 105 is an evaluation rule (database) for the evaluation elements of “sleep rhythm”, “head rest”, “body rest”, “good sleep”, “good awakening”, and “midway awakening”. Holding. In addition, score tables A to F for reference in each evaluation rule are held. In addition, about the specific example of an evaluation rule and a score table, it illustrates in operation | movement description of a sleep analyzer later on.

  The sleep type analysis processing unit 106 generates and outputs information related to the sleep type of the subject from the calculation data from the evaluation result calculation processing unit 104. In other words, the evaluation results for the evaluation factors of “sleep rhythm”, “head rest”, “body rest”, “good sleep”, “good awakening” and “halfway awakening” are expressed as gender, age, Correction and normalization are performed based on personal information such as height and weight, and environmental information such as season, entry time, and wake-up time, and information on the rank of each evaluation element is output.

  Next, the operation of the sleep analyzer will be described with reference to FIG.

  Upon receiving measurement data (for one day) of the subject, the sleep depth estimation processing unit 101 generates sleep depth data from the measurement data and stores it in the RAM 102 (S101). After that, the evaluation result calculation processing unit 104 reads the stored sleep depth data from the RAM 102, processes this according to the evaluation rule of “midway awakening” in the evaluation rule storage unit 105, and calculates an evaluation score for the evaluation element. This is stored in the RAM 102 (S102).

  Here, the evaluation rule of “halfway awakening” is 100 points when the number of sleep depths = W (wakefulness) in all measurement periods (that is, the number of overnight awakenings) is 0, and the sleep depth = W (wakefulness). ) Is specified to decrease as the number of times increases. In addition, since it is said that there is a risk of insomnia when 6 or more awakenings occur overnight, the score when the number of times of sleep depth = W (wakening) is 6 or more is 0 points. You may prescribe to do.

  Further, the sleep time may be divided into the first half and the second half, or more finely, and the points may be weighted according to which time zone awakens. For example, because people who experience awakening tend to increase in waking with the passage of time, awakening during the first half of sleep has a relatively high degree of insomnia, and awakening during the second half of sleep is an insomnia It can be judged that the degree is relatively light. Therefore, the score when the number of awakenings is the same may be made smaller in the first half and larger in the second half.

  In S102, the evaluation result calculation processing unit 104 first detects the number of times of sleep depth = W (wakefulness) from the sleep depth data. For example, in the example illustrated in FIG. 10, the number of times of sleep depth = W (wakefulness) is two. Then, the detection result is processed according to the above-described evaluation rule to calculate an evaluation score for “halfway awakening” and stored in the RAM 102.

  Next, the appearance ratio conversion processing unit 103 reads the sleep depth data stored in the RAM 102, and the movement appearance ratio n− of the set value S ≧ 2 (deep sleep: SWS) of the sleep depth according to the above equation (1). MAR is calculated and stored in the RAM 102 (S103).

  5 and 6 show calculation examples when n = 10 minutes and T = 0.5 minutes. Here, FIG. 5 shows a graph when the sleep depth data and the movement appearance ratio data are plotted on the time axis, and FIG. 6 shows a graph when only the movement appearance ratio data is plotted on the time axis. .

  Thereafter, the evaluation result calculation processing unit 104 reads the stored movement appearance ratio data of the SWS from the RAM 102, processes the data according to the “sleep rhythm” evaluation rule in the evaluation rule storage unit 105, and evaluates the evaluation element. A point is calculated and stored in the RAM 102 (S104).

  Here, the evaluation rule of “sleep rhythm” is defined as follows.

(1) Cycle setting After the SWS movement appearance ratio n-MAR rises from 0%, exceeds a predetermined threshold level S1 (for example, 40%) and becomes 0% again, the period until the next rise is 1 cycle. And

(2) Score for each cycle When the cycle time is within the predetermined time range R1, the score is 100 points, and the score is reduced as the distance from the range R1 increases. For example, since the period from the start of non-REM sleep to the end of the subsequent REM sleep is appropriate from 90 minutes to 100 minutes (see, for example, “Science of Sleep” P34, published by Asakura Shoten in 1984), 90 minutes ≦ R1 ≦ 100 minutes. Also, the range of 30 minutes before and after this time range R1 is divided stepwise, and the score is set so that the score of each division becomes smaller as it moves away from R1 (if it exceeds 30 minutes before and after time range R1) 0 points).

(3) “Sleeping Rhythm” Score The sum of the scores in each cycle is the “sleep rhythm” score.

  In step S104, the evaluation result calculation processing unit 104 first detects the cycle and cycle time from the movement appearance ratio n-M.A.R. Of the SWS. For example, in the example shown in FIG. 6, there are five such cycles. Then, the detection result is processed according to the evaluation rule to calculate an evaluation score for “sleep rhythm”, and this is stored in the RAM 102.

  Next, the evaluation result calculation processing unit 104 processes the movement appearance ratio data of the SWS in accordance with the “head rest” evaluation rule in the evaluation rule storage unit 105 to calculate an evaluation score for the evaluation element. The data is stored in the RAM 102 (S105).

  Here, the evaluation rule of “head rest” is defined as follows, since non-REM sleep is positioned as brain sleep (for example, see “Sleepology Handbook” P32 issued by Asakura Shoten in 1994). Yes.

(1) Cycle setting After the SWS movement appearance ratio n-MAR rises from 0%, exceeds a predetermined threshold level S1 (for example, 40%) and becomes 0% again, the period until the next rise is 1 cycle. And

(2) Score for each cycle When the peak of the SWS movement appearance ratio n-MAR reaches 100% within one cycle, the score is 100 points, and the score is decreased as the peak decreases from 100%. Since the peak of the movement appearance ratio n-MAR hardly reaches 100% as the sleep time progresses, the sleep time is divided into the first half part and the second half part or more finely, and the peak value threshold value is 100 points toward the second half. May be gradually reduced from 100%.

(3) “Head Rest” Score The sum of the scores in each cycle is the “Head Rest” score.

  In step S105, the evaluation result calculation processing unit 104 first detects the peak of the cycle and the movement appearance ratio n-M.A.R. In each cycle from the movement appearance ratio n-M.A.R. Of the SWS. For example, in the example shown in FIG. 6, there are five such cycles, and the peak reaches 100% in the first, second and fifth cycles. Then, the detection result is processed according to the evaluation rule to calculate an evaluation score for “head rest”, and this is stored in the RAM 102.

  Next, the evaluation result calculation processing unit 104 processes the movement appearance ratio data of the SWS in accordance with the evaluation rule of “good sleep” in the evaluation rule storage unit 105 to calculate an evaluation score for the evaluation element, Store in the RAM 102 (S106).

  Here, since “good sleep” can be evaluated from the time it takes to go to sleep after entering the floor, the evaluation rule for “good sleep” is that the SWS movement appearance ratio n-MAR rises from the entrance. It is prescribed by time. For example, when the time from the entrance to the movement appearance ratio n-MAR rises within 20 minutes is 100 points, 20 minutes to 60 minutes are divided every 10 minutes, and the score decreases as the distance from the 20 minutes increases. In this way, a score is set for each section (0 points if it exceeds 60 minutes).

  In step S106, the evaluation result calculation processing unit 104 first detects the time from the entrance to the rise of the SWS movement appearance ratio n-M.A.R. From the SWS movement appearance ratio n-M.A.R. Then, the detection result is processed according to the above-described evaluation rule to calculate an evaluation score for “good sleep”, and this is stored in the RAM 102.

  Next, the evaluation result calculation processing unit 104 processes the movement appearance ratio data of the SWS according to the evaluation rule of “good awakening” in the evaluation rule storage unit 105 to calculate an evaluation score for the evaluation element. The data is stored in the RAM 102 (S107).

  Here, since “good awakening” can be evaluated at the speed of awakening, the evaluation rule for “good awakening” is defined by the slope at which the movement appearance ratio n-MAR of the SWS falls last. Yes. For example, a value obtained by subtracting the SWS value at the timing immediately before n-M.A.R becomes 0% during the last slope period from 100% is set as the score of “awakening”.

  In step S107, the evaluation result calculation processing unit 104 first detects the slope at which the movement appearance ratio n-M.A.R. Of the SWS falls last from the movement appearance ratio n-M.A.R. Of the SWS. Then, the detection result is processed according to the evaluation rule to calculate an evaluation score for “good awakening”, and this is stored in the RAM 102.

  When the evaluation process using the SWS movement appearance ratio data is completed as described above, the appearance ratio conversion processing unit 103 then reads the sleep depth data stored in the RAM 102 again, according to the above equation (1). The movement appearance ratio n-MAR of the set value S = R (REM sleep: REM) of the sleep depth is calculated, and this is stored in the RAM 102 (S108).

  7 and 8 show calculation examples when n = 10 minutes and T = 0.5 minutes. Here, FIG. 7 shows a graph when the sleep depth data and the movement appearance ratio data are plotted on the time axis, and FIG. 8 shows a graph when only the movement appearance ratio data is plotted on the time axis.

  Thereafter, the evaluation result calculation processing unit 104 reads out the stored REM movement appearance ratio data from the RAM 102, processes the data according to the evaluation rule of “body rest” in the evaluation rule storage unit 105, and performs processing on the evaluation element. An evaluation score is calculated and stored in the RAM 102 (S109).

  Here, the evaluation rule of “body rest” is defined as follows because REM sleep is positioned as body sleep (for example, refer to P.32 “Sleepology Handbook” published by Asakura Shoten in 1994). Yes.

(1) Cycle setting After the REM movement appearance ratio n-MAR rises from 0%, exceeds a predetermined threshold level S1 (for example, 40%) and becomes 0% again, the period until the next rise is 1 cycle. And

(2) Score for each cycle When the peak of the REM movement appearance ratio n-MAR reaches 100% within the period of one cycle, the score is 100 points, and the score is decreased as the peak decreases from 100%. Since the peak of the movement appearance ratio n-MAR hardly reaches 100% as the sleep time progresses, the sleep time is divided into the first half part and the second half part or more finely, and the peak value threshold value is 100 points toward the second half. May be lowered from 100%.

(3) “Body rest” score The total score in each cycle is the “Body rest” score.

  In step S109, the evaluation result calculation processing unit 104 first detects the peak of the cycle and the movement appearance ratio n-M.A.R. In each cycle from the movement appearance ratio n-M.A.R. Of the REM. For example, in the example shown in FIG. 8, there are four such cycles. Then, the detection result is processed according to the above evaluation rule to calculate an evaluation score for “body rest”, and this is stored in the RAM 102.

  As described above, the calculation process of the evaluation score for the evaluation elements of “medium awakening”, “sleep rhythm”, “head rest”, “good sleep”, “good awakening”, and “body rest” is completed. Then, the sleep type classification processing unit 106 reads out the evaluation score of each evaluation element stored in the RAM 102 from the RAM 102, corrects and normalizes it, and outputs information on the rank of each evaluation element (S110). Display examples (3 cases) when such rank information is displayed on the display device (monitor) are shown in FIGS. By referring to the display result, the user can immediately grasp the sleep type of the subject (or the user himself if the user is a subject).

  As described above, according to the sleep analysis apparatus according to the present embodiment, after the sleep depth data that is a qualitative variable is converted into the movement appearance ratio that is a quantitative variable, each evaluation element is analyzed and evaluated using this. Therefore, it becomes possible to quantitatively analyze and evaluate each evaluation element, and thus it is possible to provide a user with a comparatively reliable sleep analysis result while simplifying the processing.

  Needless to say, the present invention is not limited to the above-described embodiment, and various other modifications are possible.

  For example, in the above-described embodiment, the execution targets of the analysis evaluation using the movement appearance ratio are “sleep rhythm”, “head rest”, “good sleep”, “good awakening”, and “body rest”. However, the evaluation elements targeted by the present invention are not limited to these, and the present invention can be appropriately applied to other evaluation elements.

  Moreover, in the said embodiment, although the movement appearance ratio n-MAR of deep sleep SWS was calculated | required as the setting value S> = 2 of sleep depth, the setting value for calculating the movement appearance ratio n-MAR of deep sleep SWS S is not limited to this, and is appropriately set according to the experimental and statistical analysis results. At this time, the set value S may be changed for each evaluation element, and when the sleep depth level is changed from the above W, R, 1, 2, 3, and 4, the set value S is also changed accordingly. As appropriate. Similarly, the movement appearance ratio n-M.A.R. Of the REM sleep SWS is not limited to the above, and is appropriately set according to the experimental and statistical analysis results.

In addition, the embodiments of the present invention can be variously modified as appropriate within the scope of the technical idea of the present invention.

Configuration diagram of a sleep analysis system according to an embodiment Configuration diagram of sleep analyzer according to embodiment Functional block of sleep analyzer according to embodiment Operation flow chart of sleep analysis device according to embodiment The figure which shows the example of conversion from sleep depth data to SWS appearance ratio data The figure which shows the example of conversion from sleep depth data to SWS appearance ratio data The figure which shows the example of conversion from sleep depth data to REM appearance ratio data The figure which shows the example of conversion from sleep depth data to REM appearance ratio data The figure which shows the example of a display of the sleep type which concerns on embodiment Diagram showing an example of sleep depth data

Explanation of symbols

DESCRIPTION OF SYMBOLS 103 Appearance ratio conversion process part 104 Evaluation result calculation process part 105 Evaluation rule memory | storage part 106 Sleep type classification | category process part

Claims (20)

Data generation means for calculating the appearance ratio of the sleep depth above a predetermined level from the data regarding the sleep depth plotted on the time axis for each predetermined time unit ;
Storage means for storing an evaluation rule for evaluating a sleep rhythm based on a cycle time of the fluctuation cycle of the appearance ratio on the time axis;
The cycle time of the fluctuating cycle is detected from the appearance ratio calculated every predetermined time unit by the data generation means, and the evaluation result of the sleep rhythm in the sleep is calculated by evaluating the cycle time according to the evaluation rule. An evaluation result calculation means;
A sleep analyzer characterized by comprising: In claim 1 ,
The storage means stores a score set according to the length of one cycle time of the fluctuation cycle as the evaluation rule ,
The evaluation result calculation means calculates the score of the sleep rhythm from the total score obtained by obtaining the scores for all the fluctuation cycles detected for the sleep based on the score information stored in the storage means,
A sleep analyzer characterized by that. Data generation means for calculating an appearance ratio of a sleep depth of a predetermined level or more from data on the sleep depth plotted on the time axis;
Storage means for storing an evaluation rule for evaluating head rest during sleep based on the appearance ratio ;
An evaluation result calculating means for evaluating the appearance ratio calculated by the data generating means according to the evaluation rule stored in the storage means and calculating an evaluation result of head rest in the sleep ;
A sleep analyzer characterized by comprising: In claim 3 ,
The data generation means calculates the appearance ratio of the sleep depth above a predetermined level for each predetermined time unit,
The storage means stores, as the evaluation rule, a score set according to which level the upper limit of the appearance ratio reaches during one cycle period of the change cycle of the appearance ratio on the time axis,
The evaluation result calculation means calculates scores for all fluctuation cycles detected for the sleep based on the score information stored in the storage means, and calculates the rank of the head rest from the total score obtained by totalizing the scores. ,
A sleep analyzer characterized by that. Data generation means for calculating the appearance ratio of sleep depth at the REM level from data on sleep depth plotted on the time axis;
Storage means for storing an evaluation rule for evaluating body rest during sleep based on the appearance ratio ;
And evaluation result calculation means for calculating an evaluation result of the body resting in the sleep and evaluated according to the evaluation rules stored the occurrence ratio calculated in said storage means by said data generating means,
A sleep analyzer characterized by comprising: In claim 5 ,
The data generation means calculates the appearance ratio of the sleep depth at the REM level for each predetermined time unit,
Said storage means stores the number which is set depending on whether the upper limit of the ratio of appearance in one cycle of the variation cycle of the ratio of appearance on the time axis reach any level as an evaluation rule,
The evaluation result calculation means calculates scores based on the score information stored in the storage means for all fluctuation cycles detected for the sleep, and calculates the rest rank of the body from the total score ,
A sleep analyzer characterized by that. A data generation means for generating, for each predetermined time unit, an appearance ratio of a sleep depth equal to or higher than a predetermined level from data on the sleep depth plotted on the time axis;
Storage means for storing an evaluation rule for evaluating the goodness of sleep based on the time until the appearance ratio first rises when the appearance ratio is plotted on the time axis;
The time until the appearance ratio first rises on the time axis is detected from the appearance ratio calculated every predetermined time unit by the data generation means, and this time is evaluated according to the evaluation rule stored in the storage means. Then, an evaluation result calculation means for calculating an evaluation result of good sleep in the sleep,
A sleep analyzer characterized by comprising:
In claim 7 ,
The storage means stores the score set according to the length of time until the appearance ratio first rises as the evaluation rule ,
The evaluation result calculation means obtains a score for the time to stand up detected for the sleep based on the score information stored in the storage means, and calculates the rank of good sleep from this score.
A sleep analyzer characterized by that. Data generation means for calculating the appearance ratio of the sleep depth above a predetermined level from the data regarding the sleep depth plotted on the time axis for each predetermined time unit;
Storage means for storing an evaluation rule for evaluating the awakening based on the slope at which the appearance ratio last falls when the appearance ratio is plotted on the time axis;
An inclination at the time when the appearance ratio falls last on the time axis is detected from the appearance ratio calculated for each predetermined time unit by the data generation means, and the inclination is determined according to the evaluation rule stored in the storage means. An evaluation result calculating means for evaluating and calculating an evaluation result of the awakening in the sleep;
A sleep analyzer characterized by comprising:
In claim 9 ,
The storage means stores, as the evaluation rule, a score set according to a slope when the appearance ratio falls last.
The evaluation result calculation means obtains a score for the inclination detected for the sleep based on the score information stored in the storage means, and calculates the rank of the awakening from this score.
A sleep analyzer characterized by that. A program for providing a sleep analysis function to a computer,
A data generation processing step of calculating the appearance ratio of the sleep depth of a predetermined level or more from the data regarding the sleep depth plotted on the time axis for each predetermined time unit ;
A database that defines an evaluation rule for evaluating sleep rhythm based on the cycle time of the fluctuation cycle of the appearance ratio on the time axis;
A sleep rhythm in the sleep is detected by detecting a cycle time of the variable cycle from the appearance ratio calculated every predetermined time unit by the data generation processing step, and evaluating the cycle time according to the evaluation rule defined in the database. and evaluation result calculation processing step of calculating the evaluation results,
The program characterized by having. 12. The program of claim 11 , wherein
The database defines the score set according to the length of one cycle time of the variable cycle as the evaluation rule ,
The evaluation result calculation processing step calculates the score of the sleep rhythm from the total score obtained by obtaining the scores for all the fluctuation cycles detected for the sleep based on the score information defined in the database,
A program characterized by that. A program for providing a sleep analysis function to a computer,
A data generation processing step of calculating the appearance ratio of the sleep depth above a predetermined level from the data regarding the sleep depth plotted on the time axis;
A database that defines evaluation rules for evaluating head rest during sleep based on the appearance ratio ;
And evaluation result calculation processing step of calculating the evaluation results of the head rest in the sleep and evaluated according to the evaluation rules defined the occurrence ratio calculated in said database by said data generating step,
The program characterized by having. The program of claim 13 ,
The data generation processing step calculates the appearance ratio of the sleep depth above a predetermined level for each predetermined time unit,
The database defines, as the evaluation rule, a score set according to which level the upper limit of the appearance ratio reaches during one cycle period of the fluctuation cycle of the appearance ratio on the time axis,
In the evaluation result calculation processing step, scores for all fluctuation cycles detected for the sleep are obtained based on the score information defined in the database, and the head rest rank is calculated from the total score obtained by totalizing the scores. ,
A program characterized by that. A program for providing a sleep analysis function to a computer,
A data generation processing step of calculating an appearance ratio of the sleep depth at the REM level from the data regarding the sleep depth plotted on the time axis;
A database that defines evaluation rules for evaluating body rest during sleep based on the appearance ratio ;
And evaluation result calculation processing step of calculating the evaluation results of the rest of the body in the sleeping evaluating the occurrence ratio calculated by said data generation process according to a prescribed the evaluation rules in the database,
The program characterized by having. The program of claim 15 ,
The data generation processing step calculates an appearance ratio of sleep depth at the REM level for each predetermined time unit,
Said database is defined scores set according to whether the upper limit of the ratio of appearance in one cycle of the variation cycle of the ratio of appearance on the time axis reach any level as the evaluation rules,
In the evaluation result calculation processing step, scores for all the fluctuation cycles detected for the sleep are obtained based on the score information defined in the database, and the rest rank of the body is calculated from the total score obtained by summing the scores. ,
A program characterized by that. A program for providing a sleep analysis function to a computer,
A data generation processing step of calculating the appearance ratio of the sleep depth of a predetermined level or more from the data regarding the sleep depth plotted on the time axis for each predetermined time unit;
A database that defines an evaluation rule for evaluating good sleep based on the time until the appearance ratio first rises when the appearance ratio is plotted on the time axis;
The time until the appearance ratio first rises on the time axis is detected from the appearance ratio calculated every predetermined time unit by the data generation processing step, and this time is evaluated according to the evaluation rule defined in the database. Then, an evaluation result calculation processing step for calculating an evaluation result of good sleep in the sleep,
The program characterized by having.
The program of claim 17 ,
The database prescribes the score set according to the length of time until the appearance ratio first rises as the evaluation rule ,
The evaluation result calculation processing step obtains a score for the time to stand up detected for the sleep based on the score information defined in the database, and calculates the rank of good sleep from this score.
A program characterized by that. A program for providing a sleep analysis function to a computer,
A data generation processing step of calculating the appearance ratio of the sleep depth of a predetermined level or more from the data regarding the sleep depth plotted on the time axis for each predetermined time unit;
A database that defines an evaluation rule for evaluating the awakening based on the slope at which the appearance ratio falls last when the appearance ratio is plotted on the time axis;
Wherein the ratio of appearance of the appearance ratio calculated for each predetermined time unit by the data generation process detects the inclination when falling at the end on the time axis, in accordance with prescribed the evaluation rule this inclination in the database An evaluation result calculation processing step of evaluating and calculating an evaluation result of the awakening in the sleep;
The program characterized by having.
The program of claim 19 ,
The database defines as the evaluation rule a score set according to a slope when the appearance ratio falls last,
In the evaluation result calculation processing step, the score for the inclination detected for the sleep is obtained based on the score information defined in the database, and the rank of the awakening is calculated from the score.
A program characterized by that.

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