JP6513005B2 - Fatigue meter - Google Patents

Description

  The present invention relates to a fatigue meter.

  Fatigue, along with pain and fever, is said to be one of the three major health alarms that the body emits. For example, grasping the level of fatigue in daily life, grasping the state of recovery from fatigue in the morning or at rest, improving work efficiency and health management of companies, and using in types of work where fatigue such as driving and brain labor causes serious consequences There is a demand to know the degree of fatigue for the application.

  Fatigue is roughly divided into brain fatigue and physical fatigue. Brain fatigue is central fatigue (mental fatigue), and is known to be correlated with fluctuations in cardiac radio wave or pulse wave intervals (heart rate intervals). Specifically, it is known that the heartbeat interval fluctuates when there is no brain fatigue, but the fluctuation of the heartbeat interval disappears when there is brain fatigue. Also, physical fatigue is peripheral fatigue (muscle fatigue) and is known to be correlated with changes in heart rate or pulse rate. Specifically, it is known that the heart rate is relatively low when there is no physical fatigue, but when there is physical fatigue, the heart rate increases because a lot of blood is fed to muscles.

  Regarding fatigue measurement, many have been proposed to determine brain fatigue (mental fatigue, mental stress) from information of cardiac radio waves or pulse waves. For example, Patent Document 1 describes a diagnostic device that digitizes a pulse waveform and / or an electrocardiogram waveform, creates a chaotic attractor from the discrete data by mathematical operation, and calculates its Lyapunov exponent. Further, in Patent Document 2, acceleration pulse wave data of a subject obtained using a pulsimeter or an electrocardiograph is analyzed by the maximum entropy method, and an LF value which is a low frequency component in a frequency domain and an HF which is a high frequency component. A system has been described that separates into values and determines the degree of fatigue of a subject based on the LF / HF values obtained from those values. In the system of Patent Document 2, the degree of brain fatigue (mental stress) is measured by the LF / HF value, and combined with the factor analysis value obtained from the subject's interview data, the overall degree of fatigue including the degree of physical fatigue is determined Do.

  Further, Patent Document 3 describes a fatigue analysis device for obtaining a degree of fatigue closer to a sensory evaluation value in consideration of compensation due to sympathetic nerve activity. This apparatus determines first fatigue level calculating means for determining the reference fatigue level, second fatigue level calculating means for determining the corrected fatigue level using the maximum Lyapunov index, and the presence or absence of compensation for fatigue caused by sympathetic nerve activity. In a time zone in which the accumulated fatigue level output unit is determined to have not compensated for fatigue due to sympathetic nerve activity, the cumulative sum of the reference fatigue levels obtained by the first fatigue level calculation unit is provided. In the time zone determined to be a state where compensation for fatigue due to sympathetic nerve activity is determined, the cumulative sum of the corrected fatigue degree obtained by the second fatigue degree calculation means is obtained and output.

  In addition, with regard to physical fatigue, the average heart rate at rest can be grasped by measuring the heart rate daily using a heart rate monitor, for example, the heart rate at the time of measurement is about 5 to 10 beats more than that. When it gets high, it is judged that it is fatigued. Alternatively, for example, 3 to 10 minutes after lying on the back, measure the heart rate for 1 minute, then measure the heart rate for 1 minute 15 seconds after standing up, and the standing heart rate and supine There is also known a method of judging the degree of physical fatigue from the magnitude of the difference between the heart rate and the heart rate. This is a method based on the principle that the heart rate is lowest since muscles are the least used condition, and the higher the degree of physical fatigue, the more the heart rate at standing deviates from the heart rate at lying.

Japanese Examined Patent Publication No. 06-009546 Patent No. 5491749 gazette JP, 2009-195384, A

  Originally, "fatigue" is a combination of brain fatigue and physical fatigue. However, in many conventional techniques, judgment methods and judgment scales of brain fatigue and physical fatigue are different, and brain fatigue and physical fatigue are combined because the indicators of brain fatigue and physical fatigue do not have commonality. It is difficult to understand the overall degree of fatigue.

  For example, in the system of Patent Document 2, although the overall degree of fatigue is determined, the actual measurement is only brain fatigue, and physical fatigue is only estimated from the interview data. The method of judging the degree of fatigue from the response of the subject, such as a medical interview, has the disadvantage of lack of objectivity because the response can be falsified by the intention of the person. For this reason, it is desirable to quantify the degree of fatigue from objective measurement data without using the response of the subject.

  Further, the system of Patent Document 2 is expensive for medical use, and the apparatus of Patent Document 3 also requires a PC for realization. There is no general-purpose product that can quantitatively measure the degree of fatigue, and a small and inexpensive apparatus is required.

  Therefore, the object of the present invention is to provide a fatigue meter that quantifies the degree of brain fatigue and physical fatigue of the subject from objective data obtained by simple measurement, and presents both results as one index. It is to be.

  Correspondence between the detection unit that detects the biological signal of the person to be measured regarding the circulatory system, the fluctuation degree of the heart rate interval, the heart rate difference at standing position with respect to the supine position, and the common index for the brain fatigue degree and the physical fatigue degree The subject's brain fatigue with reference to the correspondence relationship based on the storage unit to be stored, the first calculation unit that calculates the fluctuation of the heart rate interval of the subject from the detected biological signal, and the calculated fluctuation. Based on the calculated heart rate difference, and a second calculation unit that calculates a heart rate difference between the subject's prone position and the measurement time from the detected biological signal; The second acquisition unit for acquiring the physical fatigue degree of the subject represented by the commonness index with the brain fatigue level with reference to the correspondence relationship, and the comprehensive of the subject based on the brain fatigue level and the physical fatigue level A determination unit that determines the appropriate degree of fatigue, and outputs information on the overall degree of fatigue Fatigue meter is provided, characterized in that it comprises a part.

Preferably, the first calculator and the second calculator calculate the fluctuation degree and the heart rate difference respectively from the same biological signal detected by the detection unit.
The storage unit preferably stores, as the correspondence relationship, the correspondence between the fluctuation degree of the heart rate interval and the heart rate difference at standing with respect to the supine position and the Borg scale indicating the subjective exercise intensity.
The storage unit stores the heart rate at the time of supination of the subject, and the second calculation unit stores the heart rate at the time of reclining stored in the storage unit and the time of measurement obtained from the detected biological signal Preferably, the heart rate difference is calculated using the heart rate.

The detection unit is preferably a set of electrodes for detecting a cardiac radio wave as a biological signal.
The detection unit is preferably a pulse wave sensor for detecting a pulse wave as a biological signal.
Preferably, the first calculation unit calculates, as the fluctuation degree, the maximum Lyapunov exponent of time-series data of heartbeat intervals obtained from the detected biological signal.

  According to the above-described fatigue meter, it is possible to quantify the degree of brain fatigue and the degree of physical fatigue of a subject from objective data obtained by simple measurement, and present the results of both as one index.

FIG. 2 is a schematic view showing an appearance of a fatigue meter 1; It is a figure which shows the left view of the fatigue meter 1, right view, and a usage form. 5 is a block diagram of a fatigue meter 1. FIG. 5 is an explanatory view of an electrocardiogram waveform 40 detected by a detection unit 14. FIG. It is a figure which shows the example of the fluctuation | variation of RR space | interval. It is a graph which shows the time change of the heart rate by standing up operation. It is a figure which shows the relationship between Borg scale and the determination division of the fatigue degree of the fatigue meter 1. FIG. It is a graph which shows the relationship between the fluctuation degree of RR interval, and a brain fatigue degree. It is a graph which shows the relationship between the heart rate difference and the physical fatigue degree at the time of supine and standing. It is a figure which shows the example of a display of fatigue degree. It is a figure which shows the other display example of a fatigue degree. 5 is a flowchart showing an operation example of an initial setting mode of the fatigue meter 1; It is a flow chart which shows an operation example of measurement mode of fatigue meter 1. It is a graph which shows the heart rate change immediately after exercise. It is a graph which shows the heart rate change by emotion. 5 is a block diagram of a fatigue meter 2. FIG. It is a figure for demonstrating the data of the heart rate which the abnormality determination part 27 uses. It is a graph for demonstrating estimation of the stop time by the stop control part 28. FIG. FIG. 6 is a diagram showing an example of a warning message displayed on the display unit 13; It is a figure which shows the example of a display at the time of the guidance by the deep breathing induction | guidance | derivation part 29. FIG. It is a flow chart which shows an operation example of measurement mode of fatigue meter 2. 5 is a block diagram of a fatigue meter 3. FIG. 5 is a block diagram of a fatigue meter 4. FIG. It is sectional drawing which shows schematic structure of other detection part 14A, 14B.

  Hereinafter, the fatigue meter will be described in detail with reference to the attached drawings. However, it should be understood that the present invention is not limited to the embodiments described in the drawings or below.

  FIG. 1 is a schematic view showing the appearance of the fatigue meter 1. FIGS. 2A to 2C are a left side view, a right side view, and a usage pattern of the fatigue meter 1, respectively. FIG. 3 is a block diagram of the fatigue meter 1.

  The fatigue meter 1 is a device that measures and outputs the degree of brain fatigue and the degree of physical fatigue of the subject from the information of the same cardiac radio wave detected by the electrodes. From the heart rate information (heart rate and its fluctuation) of the subject, the fatigue meter 1 obtains brain fatigue and physical fatigue using different indexes, and converts the values of those indexes into common indexes. By integrating, a comprehensive degree of fatigue is determined and notified to the subject.

  The fatigue meter 1 includes a body case 10, a main power switch 11, an operation unit 12, a display unit 13, a detection unit 14, a storage unit 15, and a control unit 16. As shown in FIGS. 1 to 2C, the main body case 10 is rectangular when viewed from the front, and has a size and thickness suitable for a person to hold with both hands. As an example, the main power switch 11 is provided on the side surface of the upper main body case 10 as viewed from the front. The fatigue meter 1 operates with power from, for example, a battery power source or an AC power source.

  The operation unit 12 includes a measurement button 12A, a setting button 12B, and a selection button 12C, and in the illustrated example, is provided on the lower front side of the main body case 10. The measurement button 12A is a button for starting measurement of the degree of fatigue. The setting button 12B is a button for shifting to an initial setting mode for inputting information necessary for measurement of the degree of fatigue. The selection button 12C is, for example, a button used by the user to select an input item in the initial setting mode, and is configured of a + button and a − button.

  The display unit 13 is an example of an output unit, and includes, for example, a liquid crystal display panel (LCD). The display unit 13 displays measurement results of the degree of fatigue, a progress bar indicating the progress of detection of cardiac radio waves, and various messages for prompting the user to perform an operation. Further, on the upper part of the display unit 13 in the main body case 10, a classification display 13A of the degree of fatigue is described. In the fatigue meter 1, as an example, the degree of fatigue of the subject is determined in four stages of "rest", "normal", "light fatigue" and "fatigue". In the illustrated example, when the degree of fatigue is measured, a mark is lit on the liquid crystal display panel of the display unit 13 at a position below the division corresponding to the measurement result in the division display 13A. The division display 13A may be displayed on the liquid crystal display panel only when necessary, unlike the illustrated example.

  The detection unit 14 is a pair of electrodes for detecting cardiac radio waves as biological signals of a person to be measured related to a circulator, and the electrodes 14R provided on the right side of the main body case 10 and the left side surface of the main body case 10 And the provided electrode 14L. As shown in FIG. 2C, while the subject holds the main body case 10 with both hands and the right hand 70R and the left hand 70L touch the electrodes 14R and 14L, respectively, the detection unit 14 detects the heart of the subject. Detect radio waves continuously.

  Further, the detection unit 14 detects a signal input from the electrodes 14R and 14L, an A / D converter 14D which converts the detected biological signal into a digital signal, and AC noise (from the biological signal) And a filter 14E for removing hum noise. Since there are two frequencies of 50 Hz and 60 Hz in the frequency of the commercial power source, the detection unit 14 switches between the filter 14E that removes the 50 Hz frequency component and the filter that removes the 60 Hz frequency component according to the setting. use.

FIGS. 4A and 4B are explanatory diagrams of the electrocardiogram waveform 40 detected by the detection unit 14. The peak indicated by symbol R in the electrocardiogram waveform 40 of FIG. 4A corresponds to the R wave generated when blood is pumped from the left ventricle to the aorta. The time interval from one R wave peak (R point) to the next R wave peak (R point) is called "RR interval (RRI)". FIG. 4B shows two consecutive R points R _n and R _{n + 1} and their RR intervals d _n . The fatigue meter 1 uses the RR interval as a heartbeat interval, and measures the degree of fatigue of the subject based on the fluctuation degree and the heart rate calculated from the RR interval.

  The storage unit 15 is, for example, a non-volatile memory such as an EEP-ROM, and stores information necessary for the operation of the fatigue meter 1. Although the details will be described later, the storage unit 15 stores the correspondence between the index related to the heartbeat and the index related to the degree of fatigue.

  The control unit 16 is configured as a control circuit of a microcomputer including a CPU, a RAM, a ROM, and the like, and controls the operation of the fatigue meter 1.

  Here, the measurement principle of the fatigue meter 1 will be described. For brain fatigue analysis, the fatigue meter 1 uses a chaotic Lyapunov index method. The chaotic Lyapunov exponent method is a method in which time series data of RR interval is regarded as an orbit of a chaotic dynamical system, and the divergence of the orbit is evaluated by the Lyapunov exponent.

FIG. 5A and FIG. 5B show an example of fluctuation of the RR interval. FIG. 5 (A) shows an example when there is no brain fatigue (at normal time), and FIG. 5 (B) shows an example when there is brain fatigue (at fatigue). In these figures, for each of a plurality of RR intervals extracted as time series data from an electrocardiogram waveform, the size of the focused RR interval is x-coordinate, and the size of the RR interval immediately before that is y-coordinate It is a plot and is called Lorentz plot. The horizontal axis of each figure is the current RR interval d _n , and the vertical axis is the immediately preceding RR interval d _{n -1} , both in units of milliseconds.

  As can be seen by comparing FIG. 5 (A) and FIG. 5 (B), in FIG. 5 (A) where there is no brain fatigue, the RR interval irregularly changes with time and is complicatedly shaken. On the other hand, in FIG. 5B in the case where there is brain fatigue, each point is concentrated in almost the same region, so there is almost no fluctuation in the RR interval, or the RR interval shifts with regular fluctuation. ing. If the set of plotted points is regarded as the trajectory of a dynamical system in each of the cases of FIGS. 5A and 5B, the dynamical system of FIG. 5A has chaos. The dynamical system of (B) is not chaotic. It is known that the maximum Lyapunov index is an index indicating the orbital divergence of a dynamical system, and the maximum Lyapunov index is positive if it is a chaotic dynamical system, and negative if it is not a chaotic dynamical system.

ここで、Ｍは時系列データの総サンプル時間、ｄは時系列データの時刻ｋと時刻ｋ−１のパターン間の距離（ローレンツプロットにおける２次元平面上の距離）である。λ_１＞０であることが観測されれば、周期性のないカオス状態に入っていると言える。そこで、疲労度計１は、ＲＲ間隔の時系列データからＷｏｌｆ法に従って最大リアプノフ指数λ_１を算出し、その符号および大きさを調べることによりＲＲ間隔の揺らぎ度を定量化して、脳疲労度を判定する。 Furthermore, the maximum Lyapunov exponent λ ₁ can be simplified by the following equation using the Wolf method (Alan Wolf, “DETERMINING LYAPUNOV EXPONENTS FROM A TIME SERIES”, Physica 16D (1985), pp. 285-317, North-Holland, Amsterdam) It is known that it can be calculated.

Here, M is the total sample time of time series data, and d is the distance between the time k and time k-1 patterns of time series data (distance on a two-dimensional plane in Lorentz plot). If it is observed that λ ₁ > 0, it can be said that it is in a non-periodic chaotic state. Therefore, the fatigue meter 1 calculates the maximum Lyapunov exponent λ ₁ from the time series data of the RR interval according to the Wolf method, examines the sign and the size thereof, and quantifies the fluctuation degree of the RR interval to calculate the brain fatigue degree. judge.

  Also, for physical fatigue analysis, the fatigue meter 1 uses a standing position comparison method. The standing position comparison method is based on the difference between the resting heart rate measured when the subject turns on and the standing heart rate measured when the subject stands. , Is a method of estimating the degree of physical fatigue.

  FIG. 6 is a graph showing the time change of the heart rate due to the standing operation. The horizontal axis of FIG. 6 indicates the elapsed time t, and the unit is seconds. The vertical axis represents heart rate HR, and the unit is bpm (beats / minute). The graph of FIG. 6 is obtained by superimposing and plotting a plurality of results obtained by measuring the time change of the heart rate when the physical fatigue degree is different for one subject. A curve group indicated by reference numeral 41 is a heart rate in a normal state (without physical fatigue), and a curve group indicated by reference numeral 42 is a heart rate during fatigue (when there is physical fatigue). The subject was in a state of lying on his back at t = -5, rose at t = 0, and continued standing up at t> 0.

  As can be seen from the graph of FIG. 6, in the supine state (-5 ≦ t <0), there is no significant difference due to the physical fatigue degree except when the physical condition is different particularly at the time of heating. On the other hand, the heart rate rises immediately after standing up (0 <t <20), and when 30 seconds or more (t> 30) elapses after standing up, the fatigue time shown by code 42 is higher than the normal heart rate shown by code 41 Heart rate is higher, and differences in heart rate can be seen depending on the degree of physical fatigue. Therefore, the fatigue meter 1 stores in advance in the storage unit 15 the heart rate when the person to be measured turns over, and after 30 seconds or more have passed since the person to be measured stood up, the heart rate is calculated. Measure and determine the degree of physical fatigue based on the heart rate difference. In addition, since the heart rate of 40 corresponds to about 30 seconds, the fatigue meter 1 measures, for example, an RR interval for 40 beats, and uses the last data to measure the heart rate at 30 seconds or more after standing up. Calculate the number.

  The fatigue meter 1 quantifies both brain fatigue and physical fatigue by converting it to the same index of RPE. The RPE (Rate of Perceived Exertion) was originally expressed in the 5 to 20 (6 to 20 in some documents) stages of fatigue during exercise and was originally conceived by a person named Bolg. From, also called Borg scale. Brain fatigue mainly based on the autonomic nervous system evaluation and physical fatigue based on sports medicine are different in the evaluation scale and difficult to compare as they are. For this reason, the fatigue meter 1 unifies the numerical values of the brain fatigue degree and the physical fatigue degree obtained by the above method into RPE according to the correlation function between the brain fatigue degree and the physical fatigue degree and the RPE value.

  FIG. 7 is a view showing the relationship between the Borg scale and the determination class of the degree of fatigue of the fatigue meter 1. As shown in FIG. The fatigue meter 1 unifies the index of the degree of fatigue to RPE, and then determines the degree of fatigue of the person to be measured in four categories according to the magnitude. For example, when the RPE is 7 or less, the fatigue meter 1 means "rest" which means no fatigue, and when 8-11, it means "normal" which means the normal range during activity. In the case of -14, it is judged as "light fatigue" which means that it is a little fatigue, and when it is 15 or more, it is determined as "fatigue" which means that it is a perfect fatigue condition. Note that this classification determination is an example, and the number of classifications may be 5 or more or 3 or less, and the correspondence between the value of RPE and the classification may be appropriately determined.

FIG. 8 is a graph showing the relationship between the fluctuation of the RR interval and the degree of brain fatigue. FIG. 9 is a graph showing the relationship between heart rate difference and physical fatigue when lying down and standing. The horizontal axis of FIG. 8 is a RPE values shown in FIG. 7, the vertical axis is the value of the maximum Lyapunov exponent lambda ₁ regarding time-series data of the RR interval. The horizontal axis in FIG. 9 is the RPE value shown in FIG. 7, and the vertical axis is the difference ΔHR (bpm) between the standing heart rate and the lying heart rate. Each graph for five subjects, when each of various fatigue, by measuring the maximum Lyapunov exponent lambda ₁ and heart rate difference ΔHR above, is a plot of the data obtained. When the maximum Lyapunov index and the heart rate difference were measured from the heart rate information, and the RPE at that time was determined and plotted, it was found that there is a correlation as shown in FIG. 8 and FIG. Therefore, fatigue meter 1 refers to the data in these graphs, the measured value of the maximum Lyapunov exponent lambda ₁ and heart rate difference Hr, and RPE value which is an index of brain fatigue of the subject, physical fatigue Obtain an RPE value that is an index of degree.

Based on the above principle, the storage unit 15 stores the fluctuation degree of the heartbeat interval and the correspondence relationship between the heart rate difference at standing time with respect to the supine position and the Borg scale indicating the subjective exercise intensity. More specifically, storage unit 15 shows data indicating the correspondence between maximum Lyapunov exponent λ ₁ and RPE value in relation to time series data of RR interval shown in FIG. 8 and standing for the recumbent position shown in FIG. It stores data indicating the correspondence between the heart rate difference and the RPE value. In addition, the storage unit 15 stores, for one or more persons to be measured, the heart rate at the time of their recumbency.

  The control unit 16 includes, as functional blocks realized by the CPU, the RR interval extraction unit 21, the fluctuation degree calculation unit 22, the brain fatigue degree acquisition unit 23, the heart rate calculation unit 24, the physical fatigue degree acquisition unit 25, and the integration determination unit 26. Have. Below, these functional blocks are explained.

  The RR interval extraction unit 21 creates time series data of the RR interval from the cardiac radio waves (biosignals) detected by the detection unit 14. At this time, the RR interval extraction unit 21 obtains, among the electrocardiogram waveforms, the position having the maximum value for each region exceeding the detection threshold predetermined for the amplitude, and RR the time interval of each position. Extract as an interval. The detection threshold (sensitivity) of the cardiac radio wave (R wave) used by the RR interval extraction unit 21 may be adjustable by the user via the operation unit 12 in the initial setting mode.

The fluctuation degree calculation unit 22 is an example of a first calculation unit, and calculates the fluctuation degree of the heart rate interval of the subject from the electrocardiogram waveform detected by the detection unit 14. At that time, the fluctuation calculation section 22, as fluctuations of, from the time-series data of the RR interval extracted by the RR interval extracting section 21 (beat-to-beat), and calculates the maximum Lyapunov exponent lambda ₁ eg according Wolf method.

The brain fatigue degree acquiring unit 23 is an example of a first acquiring unit and a fatigue degree judging unit, and based on the maximum Lyapunov exponent λ ₁ (the fluctuation degree of the heart rate interval) calculated by the fluctuation degree calculating unit 22, The degree of brain fatigue of the person to be measured is acquired with reference to the correspondence relationship of FIG. 8 stored in FIG. For example, from the fatigue level classification in FIG. 7 and the correspondence in FIG. 8, the brain fatigue level acquiring unit 23 has brain fatigue level (RPE) = 5 when λ ₁ = 1.3, and the category is “rest”. It is determined that Further, the brain fatigue degree acquisition unit 23 determines that the brain fatigue degree (RPE) = 19 when λ ₁ = −1.5, and that the classification is “fatigue”. If λ ₁ is smaller than −0.1 (see the arrow in FIG. 8), the brain fatigue degree acquiring unit 23 has a brain fatigue degree (RPE) of 12 or more, and the classification is “light fatigue” or “fatigue”. Determine that there is.

  The heart rate calculation unit 24 is an example of a second calculation unit, and calculates time series data of the heart rate of the subject from the electrocardiogram waveform detected by the detection unit 14, and further, when the subject is in recumbent position Calculate the heart rate difference between and the time of measurement. At this time, the heart rate calculation unit 24 divides, for example, RR interval data for 40 beats measured immediately after standing up and extracted by the RR interval extraction unit 21 into eight blocks, and RR of the last or last two blocks The average heart rate is determined from the interval, and is used as the heart rate at the time of measurement of the subject. Since the heart rate of 40 beats corresponds to about 30 seconds, the calculated heart rate will be the heart rate after 30 seconds from the standing. Then, the heart rate calculation unit 24 uses the heart rate at the time of lying down of the person to be measured stored in the storage unit 15 and the heart rate at the time of measurement of the person to be measured calculated as described above. The number difference ΔHR is calculated.

  The physical fatigue degree acquisition unit 25 is an example of a second acquisition unit and a fatigue degree determination unit, and is stored in the storage unit 15 based on the heart rate difference ΔHR calculated by the heart rate calculation unit 24 as shown in FIG. With reference to the correspondence relationship, the degree of physical fatigue of the subject represented by the brain fatigue degree and the common index is obtained. For example, the physical fatigue degree acquiring unit 25 determines that the physical fatigue degree (RPE) = 10 when ΔHR = 5 and the classification is “normal” from the fatigue degree classification in FIG. 7 and the correspondence in FIG. 9. judge. Further, the physical fatigue degree acquiring unit 25 determines that the physical fatigue degree (RPE) = 14 when ΔHR = 20, and that the classification is “light fatigue”. If ΔHR is greater than 12 (see the arrow in FIG. 9), the physical fatigue degree acquiring unit 25 determines that the physical fatigue degree (RPE) is 12 or more and the classification is “light fatigue” or “fatigue”. .

  The integrated determination unit 26 is an example of the determination unit, and based on the brain fatigue degree acquired by the brain fatigue degree acquisition unit 23 and the physical fatigue degree acquired by the physical fatigue degree acquisition unit 25, Determine the degree of fatigue. Generally, since the human feels the higher one of brain fatigue and physical fatigue as fatigue, the integrated judgment unit 26 comprehensively sets the higher of the RPE values of the brain fatigue degree and the physical fatigue degree acquired as described above. The RPE value of the fatigue level is determined, and the classification is judged as the classification of the comprehensive fatigue level. For example, if the degree of brain fatigue is "rest" and the degree of physical fatigue is "light fatigue", the integrated determination unit 26 determines that the comprehensive degree of fatigue is "light fatigue", and the degree of brain fatigue is "fatigue" If the physical fatigue degree is "normal work", the overall fatigue degree is determined to be "fatigue".

  The determination results by the brain fatigue degree acquiring unit 23, the physical fatigue degree acquiring unit 25, and the integration determination unit 26 are displayed on the display unit 13. The information displayed on the display unit 13 may be either the value of fatigue degree (brain fatigue degree, physical fatigue degree or overall fatigue degree) or classification, but if both of them are displayed, the person to be measured Easy to understand. Moreover, the output method of the determination (measurement) result by the fatigue meter 1 may be other forms such as output of a voice message, alarm ringing according to the classification of the degree of fatigue, and data output to an external device.

Incidentally, the heart rate calculation section 24, the fluctuation calculation section 22 is the same electrocardiographic waveform as that used for calculating the maximum Lyapunov exponent lambda _1, and calculates the heart rate difference Hr. That is, it is not necessary to measure the electrocardiographic waveform twice to determine the degree of brain fatigue and the degree of physical fatigue in the fatigue meter 1, and for the subject, the degree of brain fatigue and the degree of physical fatigue in one measurement. And we can grasp the integrated fatigue level that integrated them.

  FIG. 10 is a diagram showing a display example of the degree of fatigue. FIG. 10 shows an example where the degree of brain fatigue is "light fatigue" and the degree of physical fatigue is "normal". In this case, “light fatigue” having a physical fatigue degree higher than the brain fatigue degree is displayed as a comprehensive fatigue degree of the subject, for example, by a combination of the division indication 13A and the mark 13B as a determination result by the integrated determination unit 26 Ru. Also, for example, below the mark 13B, a bar graph 13C of RPE values indicating the degree of brain fatigue and a bar graph 13D of RPE values indicating the degree of physical fatigue are displayed.

  FIG. 11 is a view showing another display example of the degree of fatigue. FIG. 11 also shows an example where the degree of brain fatigue is “light fatigue” and the degree of physical fatigue is “normal”. As shown in FIG. 11, the bar graph 13E of the RPE value indicating the brain fatigue degree and the bar graph 13F of the RPE value indicating the physical fatigue degree may be separately displayed without displaying the comprehensive fatigue degree. . In this case, for example, the bar graph 13E of the brain fatigue degree and the bar graph 13F of the physical fatigue degree may be alternately displayed every two seconds.

  Hereinafter, the operation flow of the fatigue meter 1 will be described. The operation flow shown in FIGS. 12 and 13 is executed by the CPU of the control unit 16 in accordance with a program stored in advance in the ROM of the control unit 16.

  FIG. 12 is a flowchart showing an operation example of the initial setting mode of the fatigue meter 1. The initial setting mode is a mode for storing, in the storage unit 15, the heart rate at the time of lying of the subject. The heart rate in lying position is accurate if it is measured every time the subject uses the fatigue meter 1, but the process shown in FIG. 12 may be performed at least once, for example, when the fatigue meter 1 starts to be used. For example, when the subject (user) presses the setting button 12B, the flow of FIG. 12 starts.

  First, the control unit 16 receives an input of the use area (Kanto / Kansai) (step S11). Further, the control unit 16 receives an input of a detection threshold value of cardiac radio waves (R wave) used by the RR interval extraction unit 21 (step S12). At that time, the user (the subject) selects the input value with the selection button 12C, and presses the setting button 12B to determine. In response to the setting in step S11, the detection unit 14 switches the 50 Hz and 60 Hz filters used as the filter 14E for removing AC noise (hum noise).

  Then, the control unit 16 receives the selection of the input method of the heart rate when lying down (at rest) (step S13). As this input method, the fatigue meter 1 allows the user to select either direct input or supine actual measurement. Therefore, when the user grasps his / her supine heart rate and selects the direct input, the control unit 16 receives the direct input of the supine heart rate (step S14).

  On the other hand, when the user has not grasped his / her supine heart rate and selects the supine measurement, the control unit 16 measures the supine heart rate (step S15). At this time, when the user is in the supine position and presses the measurement button 12A to grasp the electrodes 14R and 14L, the heart rate is measured. Then, the control unit 16 causes the display unit 13 to display the heart rate in supine position input in step S14 or measured in step S15, and stores the heart rate in the storage unit 15 (step S16). This is the end of the operation of the initial setting mode of the fatigue meter 1.

  FIG. 13 is a flowchart showing an operation example of the measurement mode of the fatigue meter 1. The measurement mode is a mode for measuring the degree of fatigue of the subject. After completion of the standing up operation, when the subject depresses the measurement button 12A and grips the electrodes 14R and 14L, the flow of FIG. 13 starts.

  When a heart radio wave is detected, first, the RR interval extraction unit 21 detects an R wave (step S31). For example, if an R wave is detected twice within 4 seconds (Yes in step S31), the RR interval extraction unit 21 measures the RR interval continuously for 40 beats (about 30 seconds), and stores the data in the storage unit It is stored in 15 (step S32). In particular, in the chaotic Lyapunov exponent method, since the number of data of the power of 2 is required, the RR interval extraction unit 21 measures the RR interval of 32 beats or more.

Subsequently, brain fatigue analysis is performed in steps S33 to S35. At that time, the fluctuation calculation section 22, from the time-series data of the stored RR interval in Step S32, calculating the maximum Lyapunov exponent lambda ₁ according Wolf method (step S33). The brain fatigue acquisition unit 23 refers to the correspondence relation storage unit 15 FIG. 8 that is stored in, the value of the maximum Lyapunov exponent lambda ₁ calculated in step S33 is converted into RPE value (Step S34 ). Furthermore, the brain fatigue degree acquiring unit 23 determines to which fatigue degree category the RPE value obtained in step S34 belongs (step S35).

  In addition, physical fatigue analysis is performed in steps S36 to S38. At this time, the heart rate calculation unit 24 calculates the heart rate at the time of measurement of the subject from, for example, data for the last 10 beats among the time series data of the RR interval stored in step S32, The difference with the heart rate at the time of supination of the person to be measured, which is stored in advance in the storage unit 15, is calculated (step S36). Then, the physical fatigue degree acquiring unit 25 converts the heart rate difference calculated in step S36 into an RPE value with reference to the correspondence in FIG. 9 stored in the storage unit 15 (step S37). Furthermore, the physical fatigue degree acquiring unit 25 determines to which fatigue degree category the RPE value obtained in step S37 belongs (step S38).

  After that, the integrated determination unit 26 determines the higher one of the RPE value of the brain fatigue degree obtained in step S34 and the RPE value of the physical fatigue degree obtained in step S37, the overall fatigue of the subject. It is determined that the degree is the RPE value of the degree, and the division is determined as the division of the overall degree of fatigue (step S39). Then, the integrated determination unit 26 causes the display unit 13 to display the RPE values of the brain fatigue degree, the physical fatigue degree, and the comprehensive fatigue degree obtained as described above and the classification thereof as a determination result (step S40). This is the end of the operation of the measurement mode of the fatigue meter 1.

  As described above, the fatigue meter 1 calculates the index value reflecting the brain fatigue degree and the index value reflecting the physical fatigue degree from the information of the same cardiac radio waves detected by the detection unit 14 and respectively Is converted to a common index RPE value. Then, the fatigue degree meter 1 digitizes the brain fatigue degree and the physical fatigue degree with the RPE value, and notifies the subject of a comprehensive fatigue degree obtained by integrating them. In the measurement of the degree of fatigue meter 1, there is no part dependent on the inquiry, so that an objective result that is not dependent on the subjectivity of the subject can be obtained. In addition, in the fatigue meter 1, the measurement time of the brain fatigue degree can be as short as about 30 seconds by using the chaotic Lyapunov index method, and therefore it is the same as the physical fatigue degree together with the measurement of the physical fatigue degree. The final result is obtained at the measurement time. In particular, the measurement method of the fatigue meter 1 is suitable for application to general-purpose products because the Wolf method can be implemented at the microcomputer level.

  In addition to the chaotic Lyapunov exponent method, for example, the LF / HF method may be used to analyze the fluctuation of the RR interval in the brain fatigue analysis. The LF / HF method analyzes the frequency components of the RR interval time series and calculates the LF / HF value by summing up the spectral powers in the sections of LF = 0.04 to 0.15 Hz and HF = 0.15 to 0.40 Hz. And how to evaluate that value. There are three methods of frequency analysis in the LF / HF method, for example, a fast Fourier transform (FFT) method, a maximum entropy method (MEM) and a CD (Complex Demodulation) method.

  The fast Fourier transform method is a method of treating time series data as a synthesized wave of trigonometric functions and decomposing it into frequency components. The fast Fourier transform method requires more data than the chaotic Lyapunov exponent method, and requires 5 minutes or more of measurement time, so it is suitable for implementation on a PC. The maximum entropy method is a method of stochastically obtaining a spectrum by creating a simultaneous equation from an autoregressive model and autoregressive coefficients. Although the maximum entropy method can be performed with less data and shorter measurement time (about 2 to 3 minutes) than the fast Fourier transform method, it is suitable for implementation on a PC because the processing is complicated and the operation load is large. The CD method is a method of adding a predetermined frequency to a time series and obtaining a spectrum from a generated modulation component as in a wireless heterodyne method. Although the CD method can execute the maximum entropy method with an even shorter measurement time, such as several seconds, the maximum entropy method is more suitable for implementation on a PC because it is more computationally intensive.

In addition, the CVRR method may be used to analyze the fluctuation of the RR interval in the brain fatigue analysis. The CVRR method is a method of evaluating the fluctuation degree of the RR interval by the following equation.
CVRR = (standard deviation of RR interval / average value of RR interval) x 100 (%)

  Even when the LF / HF method or the CVRR method is used, the brain fatigue degree can be quantified by converting the obtained index value into the RPE value as in the case of the chaotic Lyapunov index method. However, in the LF / HF method, a large number of data is required to perform frequency resolution, and the measurement time is long. Although the CVRR method is a simple method, it has a drawback that it is susceptible to the fluctuation of the RR interval due to breathing or the like. On the other hand, the chaotic Lyapunov exponent method does not require frequency decomposition, so measurement can be performed in a short time as compared to the LF / HF method, and results that are more reasonable than the CD method or CVRR method are obtained. For this reason, for practical use, it is preferable to use the chaotic Lyapunov index method for brain fatigue analysis.

Also, in the physical fatigue analysis, the heart rate may be determined from the heart rate exercise intensity according to the carbonen method as in the following equation.
Exercise intensity = (current heart rate-resting heart rate) / (maximum heart rate-resting heart rate)
Maximum heart rate = 220-age However, in the case of the carbonen method, it is necessary for the subject to know the resting heart rate. On the other hand, in the lying position standing position comparison method, even if the user does not know the resting heart rate, it can be implemented by measuring the heart rate on the back, which is easy to apply to products. For this reason, in practical use, it is preferable to use a standing position comparison method for physical fatigue analysis.

  By the way, for example, when measurement is performed by the fatigue meter 1 immediately after exercise, or when an emotional change or a sudden movement occurs during measurement of the fatigue meter 1, fluctuations in the heart rate interval or the heart rate are those factors. Because of this, the reliability of the measured value may be reduced.

  FIG. 14 is a graph showing heart rate changes immediately after exercise. The horizontal axis in FIG. 14 is time t (seconds), and the vertical axis is heart rate HR (bpm). The graph in FIG. 14 shows heart rate changes when the subject continues exercise at 0 <t <120 and stops at t = 120. Curves 43 to 46 are measurement results for four subjects having different initial values of heart rate. Although the heart rate is relatively high during exercise, when exercise is stopped, the heart rate decays towards the resting heart rate with a first-order delay. As described above, when the subject is exercising immediately before the measurement, the fluctuation of the heart rate interval and the heart rate change with time, which affects the measurement result of the degree of fatigue. It is also difficult for the subject to determine whether or not a measurement error has occurred because the subject does not know how long after exercise he should measure.

  FIG. 15 is a graph showing heart rate change due to emotion. The horizontal axis in FIG. 15 is time t (seconds), and the vertical axis is heart rate HR (bpm). The graph of FIG. 15 shows the heart rate change when the subject is suddenly spoken at around t = 70 while measuring the heart rate. As shown in FIG. 15, a person's heart rate rises sharply and greatly by being talked during measurement. For example, if the subject is surprised immediately before or during the measurement, moves largely during the measurement, or measures during the rising edge, the heart rate also sharply increases. Therefore, even when there is emotional change or sudden movement due to surprise, the fluctuation of the heart rate interval and the heart rate change, which affects the measurement result of the degree of fatigue.

  In addition, since the heart rate changes depending on the physical condition such as fever, for example, if the subject measures heart rate when lying down in a disease state with fever, then the person being measured in a state where the disease is cured It is possible that the heart rate at the time of measurement (at standing position) when using a fatigue meter may become lower than the heart rate at the time of storing. In this case, the measurement accuracy of the physical fatigue degree is lowered because the value of the heart rate at lying position which is the reference of the measurement of the physical fatigue degree is not accurate.

  Therefore, from the time-series data of the heart rate during measurement, the fatigue meter 2 described below determines whether or not a heart rate fluctuation that may affect the measurement result of the degree of fatigue has occurred during the measurement. If it is determined that the heart rate fluctuation as described above has occurred, the fatigue meter 2 warns the subject of that effect and urges the subject to perform re-measurement or the like.

FIG. 16 is a block diagram of the fatigue meter 2.
The fatigue meter 2 is different from the fatigue meter 1 only in the functional block realized by the CPU of the control unit, and has the same configuration as the fatigue meter 1 in hardware. Therefore, in the following, with regard to the fatigue level meter 2, a function different from that of the fatigue level meter 1 will be mainly described, and the description of the parts overlapping with the fatigue level meter 1 will be omitted.

  The control unit 17 of the fatigue meter 2 includes, as functional blocks realized by the CPU, an RR interval extraction unit 21, a fluctuation degree calculation unit 22, a brain fatigue degree acquisition unit 23, a heart rate calculation unit 24, and a physical fatigue degree acquisition unit 25. , An integrated determination unit 26, an abnormality determination unit 27, a stop control unit 28, and a deep breathing guidance unit 29. Among these, functional blocks other than the abnormality determination unit 27, the stop control unit 28 and the deep breathing induction unit 29 are the same as those of the fatigue meter 1. Therefore, functional blocks that are not included in the control unit 16 of the fatigue meter 1 will be described below.

  The abnormality determination unit 27 determines whether or not the time-series data of the heart rate of the person to be measured indicates an abnormal fluctuation of a type predetermined as one that may influence the determination of the degree of fatigue.

  FIG. 17 is a diagram for explaining the heart rate data used by the abnormality determining unit 27. As shown in FIG. On the upper side of FIG. 17, data 01 to 05, 06 to 10, 11 to 15, 16 to 20, 21 to 25 of RR intervals (RRI) for 40 beats extracted from the electrocardiogram waveform by the RR interval extraction unit 21. , 26-30, 31-35, 36-40. The lower part of FIG. 17 shows data X01, X06, X11, X16, X21, X26, X31, X36 of the average heart rate (BPM) for each block calculated from the data of the RR interval by the heart rate calculation unit 24. . As shown in FIG. 17, the RR interval data for 40 beats is divided into 8 blocks of 5 beats each, and an average heart rate is calculated for each block. That is, X01 is calculated from the data of 01 to 05, X06 is calculated from the data of 06 to 10, and similarly, X36 is calculated from the data of 36 to 40. Among these, the heart rate calculation unit 24 calculates the heart rate at the time of measurement (at standing position) using the values of X31 and X36 indicated by broken lines, but the abnormality determination unit 27 calculates all of X01 to X36. Is used as time series data of average heart rate.

First, the abnormality determination unit 27 determines whether the average heart rate indicated by the time-series data X01 to X36 monotonously decreases with the passage of time. At that time, the abnormality determination unit 27 determines that the values of X01 to X36 are (1) X01>X06>X11>X16>X21>X21>X26>X31> X36
It is determined whether or not As described above, when the average heart rate gradually decreases with the passage of time, the abnormality determination unit 27 determines that the measurement has been performed immediately after the exercise. In this case, the abnormality determination unit 27 causes the display unit 13 to display a message to warn the subject that the reliability of the determination result of the degree of fatigue is low, which is considered to be measurement immediately after exercise.

Further, the abnormality determination unit 27 determines whether or not the average heart rate indicated by the time-series data X01 to X36 has increased by a predetermined level or more. At this time, the abnormality determination unit 27 determines that, for example, among X01 to X36, the first, middle, and last average heart rate values are (2)-D <(X01-X36) <D or-D <(X01-X21). ) <D
It is determined whether or not Here, D is an appropriately set threshold, such as 10 bpm. As described above, the abnormality determination unit 27 checks heart rate differences between the beginning and end of the measurement and between the beginning and end (or between the end and the middle), and if the difference is larger than the threshold value, It is determined that there has been a change in heart rate due to In this case, the abnormality determination unit 27 displays on the display unit 13 a message to warn the subject that the reliability of the determination result of the degree of fatigue is low because it is considered that the heart rate fluctuates due to emotion during the measurement. Let

Further, the abnormality determination unit 27 determines whether or not the average heart rate indicated by the time-series data X01 to X36 is lower than the heart rate at the time of supination. At that time, the abnormality determination unit 27 determines that the average heart rate Xn of any one of X01 to X36 is (3) (Xn-heart rate when lying down) <0
It is determined whether or not As described above, if the magnitude relationship between the heart beat rate for supination stored in the storage unit 15 and the heart rate for standing posture newly measured is reversed, the abnormality determination unit 27 determines that the heart beat during supination A message is displayed on the display unit 13 to warn the subject that the reliability of the number is low.

  When the abnormality determination unit 27 determines that the heart rate indicated by the time-series data X01 to X36 monotonously decreases with the passage of time, the stop control unit 28 uniformly detects the cardiac radio wave (biosignal) by the detection unit 14 Stop for a while. That is, when it is determined that the judgment formula of (1) is established and exercise is performed immediately before the measurement, the stop control unit 28 stops the measurement of the fatigue meter 2 for a certain time. At that time, it does not know when the subject has stopped exercising, and the time constant T of the human metabolic change after exercise is about 56 seconds (Hirosaki Univ., Koichi Sagawa "Measurement and Analysis of Human Motion" And from the application, published by Japan Techno Center, 2007), the stop control unit 28 estimates that the stop time until the heart rate converges is, for example, 4T = 4 × 56 seconds = 224 seconds. In addition, this presumption presupposes that the to-be-measured person is performing the measurement by the fatigue meter 2 at least in the state of rest. Then, the stop control unit 28 causes the display unit 13 to count down and display the estimated waiting time, thereby notifying the subject of how much time should be measured again.

  Alternatively, when the abnormality determination unit 27 determines that the heart rate indicated by the time-series data X01 to X36 monotonously decreases with the lapse of time, the stop control unit 28 determines the time according to the decrease degree of the heart rate The detection of cardiac radio waves by the detection unit 14 may be stopped. That is, the stop control unit 28 may change the measurement waiting time after exercise according to the declining tendency of the heart rate.

FIG. 18 is a graph for explaining the estimation of the stop time by the stop control unit 28. The horizontal axis in FIG. 18 is the elapsed time t, and the vertical axis is the heart rate HR. It is assumed that the subject performs exercise when t <0, the heart rate at that time is E, and the subject stops exercise when t = 0. Also, let Z be the heart rate of the subject in the supine position, and let ΔZ be the difference between the measured average heart rate X36 of the end block and the heart rate Z in the prone position (ΔZ = X36−Z). Then, since there is a correlation between the convergence line of the heart rate after exercise and the heart rate when lying down, the larger the ΔZ, the closer to t = 0 the slope of the heart rate attenuation curve is, ΔZ Is smaller, the slope of the heart rate attenuation curve is considered to be farther from t = 0. Therefore, when the above judgment formula (1) for the average heart rate is established, the stop control unit 28 calculates the value of ΔZ, and estimates the stop time (waiting time) by the value, for example, as follows. May be
When −1 <ΔZ <1, waiting time = 0 seconds When 1 ≦ ΔZ <10, waiting time = 56 seconds (= T)
When 10 ≦ ΔZ <20, the waiting time = 112 seconds (= 2T)
When 20 ≦ ΔZ <30, waiting time = 168 seconds (= 3T)
When 30 ≦ ΔZ, waiting time = 224 seconds (= 4T)

  The deep breath induction unit 29 measures the number of deep breaths according to the increase in the heart rate when the abnormality determination unit 27 determines that the heart rate indicated by the time-series data X01 to X36 has increased by a predetermined level or more. Induce people to do what they do. That is, when the judgment formula of (2) above is established and it is determined that there is a change in emotion during the measurement, the deep breathing guidance unit 29 causes the subject to perform deep breathing, thereby to realize a temporary heart rate. Eliminate the fluctuation of

In general, the number of deep breaths required varies depending on the magnitude of heart rate variability. For example, assuming that 5 deep breaths are required to return the heart rate to the original state when there is a variation of (X01-X36) = -13 bpm, a variation of (X01-X21) = -27 bpm If so, it takes 10 deep breaths to return the heart rate to its original state. Therefore, the deep breathing guidance unit 29 changes the number of deep breathings according to the magnitude of the heart rate fluctuation due to emotion. For example, the deep breathing guidance unit 29 may use the judgment formula (2) described above as
When the condition of 0 <D <10 is satisfied, the number of deep respirations is 5 times When the condition of 10 ≦ D <20 is satisfied, the number of deep respirations is 10 times When the conditions of 20 ≦ D <30 are satisfied, the number of deep respirations is 15 times 30 ≦ D <40 Alternatively, the number of deep breaths may be set to 20.

  Further, the deep respiration guiding unit 29 also determines that the result of determination by the integrated determination unit 26, that is, the result of determination by the brain fatigue degree acquiring unit 23 or the physical fatigue degree acquiring unit 25 is "light fatigue" or "fatigue". In order to stabilize the autonomic nerve, the subject is induced to take a deep breath. Even if it is judged that the subject is fatigued, if the subject re-measures after deep breathing and there is a tendency for improvement in the judgment result, the first judgment result is considered to be due to a temporary change in emotion. Be Therefore, when it is judged that fatigue is given, the first judgment result is a temporary emotional change depending on whether the subject takes a deep breath and re-measures and the result is improved. You can tell if it is due to real fatigue.

  FIG. 19A to FIG. 19D are diagrams showing examples of the warning message displayed on the display unit 13.

  FIG. 19A shows an example of the warning message (1) when the judgment formula of (1) is established and it is judged that the measurement is immediately after exercise. When it is determined that the fatigue degree meter 2 has just been exercised, the fatigue degree indicator 2 warns the subject of the fact and gives the subject a waiting time estimated based on the characteristics of the first-order lag shown in FIG. Prompt to re-measure. In this case, for example, the number of seconds of “re-measurement after 224 seconds” is counted down, and re-measurement becomes possible when 0 seconds later.

  FIG. 19 (B) is an example of the warning message (2) when it is determined that the judgment formula of (2) is satisfied and it is determined that emotional change, rapid movement and the like occur during measurement. When it is determined that there is a change in emotion or a sudden movement, the fatigue meter 2 warns the subject of the change. It is known that even if the heart rate rises due to temporary emotional changes etc., it will be lowered by deep breathing, which sucks and exhales slowly, so in this case, the fatigue meter 2 measures temporary emotional changes In order to reduce the influence of the subject, the subject is induced to take a deep breath.

  FIG. 19C is an example of the warning message (3) when it is determined that the degree of fatigue of the subject is “light fatigue” or “fatigue”. Also in this case, the fatigue meter 2 guides the subject to take a deep breath in order to distinguish whether the judgment result is a temporary emotional change or a real fatigue.

  FIG. 19D is an example of the warning message (4) in the case where it is determined that the reliability of the heart rate in supine position stored in the storage unit 15 is low when the determination expression of (3) is established. is there. If the fatigue degree meter 2 determines that the standing heart rate measured newly is smaller than the resting heart rate stored in the storage unit 15, it warns the subject of the determination. At the same time, encourage them to re-measure their heart rate in supine position.

  FIG. 20 is a view showing a display example at the time of guidance by the deep breathing guidance unit 29. As shown in FIG. After the warning message of FIG. 19 (B) or FIG. 19 (C), the deep breathing guidance unit 29 causes the display unit 13 to display the navigation of deep breathing described below. First, as shown by reference numerals 61 and 62, the "suck" icon 65 is lighted, and the bar 66 extends from the left end of the screen toward the right end of the screen, for example, in 2 seconds. Next, the display of the "Suck" icon 65 and the bar 66 disappears, and as shown by the reference numerals 63 and 64, the "Spit" icon 67 lights up, and the bar 68 takes, for example, six seconds from the left end of the screen to the right end extend. Thereafter, the display of the "spit" icon 67 and the bar 68 disappears, and the "suck" icon 65 and the bar 66 are displayed again. The deep breath induction unit 29 repeats the above display a plurality of times to induce the subject to take a deep breath.

  FIG. 21 is a flow chart showing an operation example of the measurement mode of the fatigue meter 2. The operation flow shown in FIG. 21 is executed by the CPU of the control unit 17 in accordance with a program stored in advance in the ROM of the control unit 17. When the user presses the measurement button 12A and grips the electrodes 14R and 14L, the flow of FIG. 21 starts.

  When a heart radio wave is detected, first, the RR interval extraction unit 21 detects an R wave (step S51). For example, if an R wave is detected twice within 4 seconds (Yes in step S51), the RR interval extraction unit 21 measures the RR interval continuously for 40 beats (about 30 seconds), and stores the data in the storage unit 15 (step S52). Then, the heart rate calculation unit 24 divides data of the RR interval for 40 beats into eight blocks, and calculates average heart rates X01 to X36 for each block (step S53).

  Here, the abnormality determination unit 27 determines whether the conditional expression (1) is established (step S54). When the conditional expression (1) is satisfied (Yes in S54), the abnormality determination unit 27 causes the display unit 13 to display the warning message (1) in FIG. 19A (Step S55). Thereafter, the stop control unit 28 estimates the waiting time, and causes the display unit 13 to count down and display the time (step S56).

  On the other hand, when the conditional expression (1) does not hold (No in S54), the abnormality determination unit 27 determines whether the conditional expression (2) holds (step S57). When the conditional expression (2) is satisfied (Yes in S57), the abnormality determination unit 27 causes the display unit 13 to display the warning message (2) in FIG. 19B (Step S58). After that, the deep breathing guidance unit 29 causes the display unit 13 to display the deep breathing guidance illustrated in FIG. 20 (step S59).

  On the other hand, when the conditional expression (2) does not hold (No in S57), the abnormality determination unit 27 determines whether the conditional expression (3) holds (step S60). When the conditional expression (3) is satisfied (Yes in S60), the abnormality determination unit 27 causes the display unit 13 to display the warning message (4) in FIG. 19D (Step S61).

  On the other hand, when the conditional expression (3) does not hold (No in S60), it is considered that there is no factor that affects the measurement of the degree of fatigue, so the degree of fatigue analysis is performed (step S62). This fatigue level analysis is the same as the brain fatigue level analysis, the physical fatigue level analysis, and the integrated determination of those results described for the fatigue level meter 1. Then, if the result of the fatigue level analysis is not "light fatigue" or "fatigue" (No in step S63), the control unit 17 causes the display unit 13 to display the result (step S64).

  On the other hand, when the result of the fatigue level analysis is "light fatigue" or "fatigue" (Yes in step S63), the control unit 17 displays the warning message (3) in FIG. 19C on the display unit 13. (Step S65). Thereafter, the deep breath induction unit 29 causes the display unit 13 to display the deep breath guidance illustrated in FIG. 20 (step S66). Thus, the operation of the measurement mode of the fatigue meter 2 ends.

  Then, when warning messages (1) to (4) are displayed in step S55, S58, S61 or S65, the subject again presses the measurement button 12A to perform re-measurement. Thereby, the operation flow of FIG. 21 is repeated again.

  As described above, the fatigue meter 2 determines the presence or absence of the heart rate fluctuation specific to the state immediately after exercise or when there is a change in emotion or a sudden movement from the information of the cardiac radio waves detected by the detection unit 14, If it is determined that they are present, the subject is warned to that effect. As a result, the subject can understand that a temporary factor that may affect the measurement result has occurred at the time of measurement, so that it is possible to improve the reliability of the measurement result by performing re-measurement. become.

  Note that the functions of the abnormality determination unit 27, the stop control unit 28, and the deep breathing induction unit 29 of the fatigue meter 2 can be applied even to a fatigue meter that measures only one of brain fatigue and physical fatigue. is there. Further, for example, when the function of the product is limited for the purpose of reducing the manufacturing cost, one or both of the stop control unit 28 and the deep breathing induction unit 29 may be omitted.

  FIG. 22 is a block diagram of the fatigue meter 3. The fatigue degree meter 3 measures only the brain fatigue degree without measuring the physical fatigue degree, and determines whether or not a temporary factor that may affect the measurement result has occurred at the time of measurement. Alert the subject. The fatigue meter 3 is different from the fatigue meters 1 and 2 only in the functional blocks realized by the CPU of the control unit, and has the same configuration as the fatigue meters 1 and 2 in hardware. Therefore, with regard to the fatigue level meter 3, only functions different from those of the fatigue level meters 1 and 2 will be described, and the description of the parts overlapping with the fatigue level meters 1 and 2 will be omitted.

The control unit 18 of the fatigue meter 3 is a functional block realized by the CPU, the RR interval extraction unit 21, the fluctuation degree calculation unit 22, the brain fatigue degree acquisition unit 23, the heart rate calculation unit 24, the abnormality determination unit 27, and stop A control unit 28 and a deep breathing guidance unit 29 are provided. That is, the functional blocks of the fatigue meter 3 are the same as those of the fatigue meter 2 except that the physical fatigue degree acquiring unit 25 and the integrated judging unit 26 are not provided. The memory unit 15 of the fatigue meter 3 measures the maximum Lyapunov exponent λ ₁ and RPE values for the time series data of the RR interval shown in FIG. 8 as the correspondence between the fluctuation of the heart interval and the Borg scale indicating the subjective exercise intensity. Store data indicating the correspondence with. The brain fatigue acquiring unit 23, based on the maximum Lyapunov exponent lambda ₁ calculated by the fluctuation calculation section 22, by referring to the correspondence relation of FIG. 8 stored in the storage unit 15, of the subject brain The degree of fatigue and the classification thereof are determined, and the determination result is displayed on the display unit 13.

  FIG. 23 is a block diagram of the fatigue meter 4. The fatigue degree meter 4 measures only the physical fatigue degree without measuring the brain fatigue degree, and determines whether or not a temporary factor that may affect the measurement result has occurred at the time of measurement. Alert the subject. The fatigue meter 4 differs from the fatigue meters 1 and 2 only in the functional blocks realized by the CPU of the control unit, and has the same configuration as the fatigue meters 1 and 2 in hardware. Therefore, with regard to the fatigue level meter 4, only the functions different from those of the fatigue level meters 1 and 2 will be described, and the description of the parts overlapping with the fatigue level meters 1 and 2 will be omitted.

  The control unit 19 of the fatigue meter 4 includes, as functional blocks realized by the CPU, an RR interval extraction unit 21, a heart rate calculation unit 24, a physical fatigue degree acquisition unit 25, an abnormality determination unit 27, a stop control unit 28 and deep breathing guidance It has a part 29. That is, the functional blocks of the fatigue meter 4 are the same as those of the fatigue meter 2 except that the fluctuation degree calculating unit 22, the brain fatigue degree acquiring unit 23, and the integrated determination unit 26 are not provided. The memory unit 15 of the fatigue meter 4 has a heart rate at the standing position at the standing position shown in FIG. 9 as a correspondence between the heart rate difference at the standing position with respect to the standing position and the Borg scale indicating the subjective exercise intensity. Data indicating the correspondence between the number difference and the RPE value is stored. Then, based on the heart rate difference ΔHR calculated by the heart rate calculation unit 24, the physical fatigue degree acquisition unit 25 refers to the correspondence in FIG. 9 stored in the storage unit 15, and calculates physical fatigue of the person to be measured. The degree and the division thereof are determined, and the determination result is displayed on the display unit 13.

  In addition, although the fatigue meter 1 shown in FIG. 1 is of a type that measures cardiac radio waves with a palm, the detection unit of the fatigue meter is attached to, for example, a finger or neck of a person to be measured to detect cardiac radio waves. It may be Alternatively, the fatigue meter may measure the pulse wave of the subject instead of the cardiac radio wave, extract the data of the heart rate interval from the pulse wave waveform, and use it. That is, the detection unit of the fatigue meter may be a pulse wave sensor for detecting a pulse wave as a biological signal. Therefore, finally, an example of a detection unit that detects a pulse wave will be described.

  FIGS. 24A and 24B are cross-sectional views showing schematic configurations of the other detection units 14A and 14B, respectively.

  A detection unit 14A illustrated in FIG. 24A is a photoelectric sensor that detects a pulse wave, and includes a light emitting element 51, a light receiving element 52, and a light shielding member 53. The light emitting element 51 emits light to the living body 54 of the subject, and the light receiving element 52 receives the light scattered, reflected or transmitted by the living body 54. The light shielding member 53 is disposed between the light emitting element 51 and the light receiving element 52, and shields light from the light emitting element 51 so as not to be directly incident on the light receiving element 52. The light emitted from the light emitting element 51 to the living body 54 is scattered by the tissue in the living body 54 and the blood in the blood vessel 55 and emitted out of the living body 54 again. Since the intensity of light emitted from the living body 54 fluctuates according to the blood flow, the detection unit 14A detects the pulse wave of the person to be measured based on the fluctuation of the intensity of the received light.

  The detection unit 14B illustrated in FIG. 24B is a sensor that is attached in contact with the surface of the skin 56 of the measurement subject, and detects a pulse wave by detecting the vibration generated from the living body 54 of the measurement subject. . The blood vessel 55 of the artery in the living body 54 vibrates in synchronization with the pulse in response to the fluctuation of the blood flow, and the vibration is propagated as vibration wave 57 in the living body 54. For example, a pressure sensor or a vibration sensor is used for the detection unit 14B, and the detection unit 14B detects the vibration wave 57 as a pressure change or a vibration change.

  Even when the detection unit 14A or the detection unit 14B is used instead of the detection unit 14, only the biosignal for obtaining the heart rate interval (RR interval) changes from the heart radio wave to the pulse wave, and the subsequent measurement of the fatigue meter The control is the same as that of the fatigue meters 1-4.

  Since pulse waves are generated by blood flow synchronized with cardiac radio waves, they are originally considered to correspond one-to-one with cardiac radio waves, but since pulse waves are measured at the periphery, it is necessary to It is possible that a difference arises and that the cardiac radio waves and the pulse waves do not correspond one to one. For this reason, it is considered that the accuracy of the measurement value is higher if cardiac radio waves are used rather than pulse waves. On the other hand, if the detection units 14A and 14B detect a pulse wave, they may be attached to, for example, a finger tip, a wrist or an earlobe of a measurement subject even if the measurement subject does not grasp the electrodes 14R and 14L with both hands As it can, it is advantageous in terms of convenience.

1, 2, 3, 4 fatigue meter 10 body case 11 main power switch 12 operation unit 13 display unit 14, 14A, 14B detection unit 15 storage unit 16, 17, 18, 19 control unit 21 RR interval extraction unit 22 fluctuation degree Calculation unit 23 Brain fatigue degree acquisition unit 24 Heart rate calculation unit 25 Physical fatigue degree acquisition unit 26 Integrated judgment unit 27 Abnormality judgment unit 28 Stop control unit 29 Deep breathing guidance unit

Claims (7)

A detection unit that detects a biological signal of a person to be measured related to a circulatory organ;
A memory unit for storing the correspondence between the fluctuation degree of the heart rate interval and the heart rate difference at standing with respect to the supine position and the common index regarding the brain fatigue degree and the physical fatigue degree;
A first calculation unit that calculates a fluctuation degree of a heartbeat interval of a subject from the detected biological signal;
A first acquisition unit that acquires the degree of brain fatigue of the subject by referring to the correspondence based on the calculated degree of fluctuation;
A second calculator configured to calculate a heart rate difference between the prone position of the subject and the time of measurement from the detected biological signal;
A second acquisition unit that acquires the degree of physical fatigue of the person to be measured, which is represented by the common indicator of brain fatigue, with reference to the correspondence relationship based on the calculated heart rate difference;
A determination unit that determines an overall fatigue level of the subject based on the brain fatigue level and the physical fatigue level;
An output unit that outputs information on the overall degree of fatigue;
A fatigue meter characterized by having.   The fatigue degree meter according to claim 1, wherein the first calculation unit and the second calculation unit respectively calculate the fluctuation degree and the heart rate difference from the same biological signal detected by the detection unit.   3. The memory according to claim 1, wherein the memory stores, as the correspondence relationship, the correspondence between the fluctuation degree of the heart rate interval and the heart rate difference at standing time with respect to the supine position and the Borg scale indicating the subjective exercise intensity. The fatigue indicator described. The storage unit stores a heart rate at the time of lying on the subject.
The second calculation unit calculates the heart rate difference using the heart rate at the time of lying down stored in the storage unit and the heart rate at the time of measurement obtained from the detected biological signal. The fatigue degree meter as described in any one of 1-3.   The fatigue degree meter according to any one of claims 1 to 4, wherein the detection unit is a pair of electrodes for detecting cardiac radio waves as the biological signal.   The fatigue degree meter according to any one of claims 1 to 4, wherein the detection unit is a pulse wave sensor for detecting a pulse wave as the biological signal.   The fatigue degree according to any one of claims 1 to 6, wherein the first calculation unit calculates, as the fluctuation degree, a maximum Lyapunov exponent of time-series data of heartbeat intervals obtained from a detected biological signal. Total.

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