JP4636860B2 - Evaluation system for human body support structure - Google Patents

Description

The present invention relates to an evaluation apparatus for a human body support structure that evaluates the performance of a human body support structure that supports a person in a sleeping posture, such as a mattress or a relax chair.

In Patent Document 1, the subject is put on a mattress using a three-dimensional knitted fabric and a known air mat, and the change in bed humidity, bed temperature, skin temperature, and blood flow in the lower limbs when sleeping for 2 hours is measured. We are comparing which mattress can provide a more resting sleep state.
Japanese Patent Laid-Open No. 2004-97540

  Among the comparative items disclosed in Patent Document 1, for the humidity in the bed, there is a significant difference between the two air mattresses, which is due to the fact that one uses a three-dimensional knitted fabric, For example, in the case of using a three-dimensional knitted fabric, since the difference is small only in the bed humidity, the comfort level of the mattress cannot be objectively evaluated only by the bed humidity. Further, regarding the temperature in the bed, the skin temperature, and the blood flow rate, since the difference between the mattresses is relatively small, it is determined in Patent Document 1 to determine whether or not comfortable sleep can be provided. It must be compared with about 2 hours of sleep. That is, in order to evaluate the comfort level of the mattress using the comparison items disclosed in Patent Document 1, it is necessary to comprehensively compare a plurality of items, and it takes several hours to obtain evaluation data. Therefore, for example, when evaluating the suitability of the mattress for each individual at a store or an exhibition hall where the mattress is sold, the technique disclosed in Patent Document 1 takes too much time and lacks simplicity and speed. Not suitable.

The present invention has been made in view of the above, and it is possible to easily and quickly evaluate the comfort level of whether a human body support structure that supports a person in a sleeping posture state such as a mattress is suitable for an individual. It is an object of the present invention to provide a human body support structure evaluation apparatus that can be easily implemented in an exhibition hall or the like.

In order to solve the above-described problem, the present invention according to claim 1 is an evaluation apparatus for a human body support structure for supporting a person in a sleeping posture state,
Original waveform data peak value detection means for measuring a fingertip volume pulse wave of a person supported in a sleeping posture on the human body support structure and detecting a peak value of each cycle of the original waveform of the obtained fingertip volume pulse wave When,
Calculate the difference between the peak value on the upper limit side and the peak value on the lower limit side for each predetermined time range from each peak value obtained by the original waveform data peak value detection means, and set the difference as a power value. Means,
A power value slope calculating means for obtaining a slope of the power value with respect to a time axis in a predetermined time range by sliding a predetermined number of times at a predetermined lap rate with respect to the predetermined time;
The pulse value muscle fatigue level for calculating the integral value by calculating the absolute value of the time series signal of the power value gradient obtained by the slide calculation by the power value gradient calculating means, and calculating the obtained integral value as the fatigue level A calculation means;
For the pulse wave, the human body support structure in which the pulse wave muscle fatigue curve indicating the transition of the fatigue level output by the pulse wave muscle fatigue level calculation unit appears relatively low is determined as a human body support structure capable of providing a more comfortable sleeping comfort. Comparison / determination means
An apparatus for evaluating a human body support structure is provided.
In this invention of Claim 2, it further has a frequency analysis means for performing frequency analysis of the original waveform data,
The pulse wave comparison / determination means uses the appearance position and / or peak value height of the peak frequency band obtained by the frequency analysis means as an evaluation index, and the peak frequency band is relatively shifted to the lower frequency side. The human body support structure evaluation apparatus according to claim 1, wherein the human body support structure that appears or the human body support structure that has a relatively low peak value is determined as a human body support structure having a higher degree of relaxation .
According to the third aspect of the present invention, the distribution rate calculation is further performed to measure the brain waves of a person supported in a sleeping posture and to obtain time series changes in the distribution rates of the obtained θ waves, α waves, and β waves. Means,
EEG comparison / determination means for determining whether or not a transition from time series change of distribution ratio obtained by the distribution ratio calculation means has shifted to sleep;
An apparatus for evaluating a human body support structure according to claim 2, comprising:
In the present invention according to claim 4, the electroencephalogram comparison / determination means is configured to increase the θ wave distribution ratio and decrease the β wave distribution ratio in a time series change of the distribution ratio obtained by the distribution ratio calculation means. The evaluation apparatus for a human body support structure according to claim 3, wherein it is determined that a transition has been made to sleep when a tendency appears .
In this invention of Claim 5, the said distribution rate calculation means calculates | requires by calculating | requiring the inclination of the distribution rate in the predetermined time range of the said θ wave of the said brain wave, (alpha) wave, and (beta) wave by a predetermined slide lap ratio, 4. The human body support structure evaluation apparatus according to claim 3, wherein the apparatus is configured to obtain a time-series change in the slope of the distribution ratio .

The human body support structure evaluation apparatus of the present invention measures brain waves or pulse waves, analyzes the obtained brain waves or pulse waves, obtains time series changes of the analyzed data, and how these time series changes appear The human body support structure is evaluated using as an evaluation index. In other words, in the present invention, the human body support structure is evaluated using an electroencephalogram or a pulse wave in which a clear change appears depending on a person's mind and body state, and can be measured in a shorter time compared to the conventional technique. In addition, a simple electroencephalograph is sufficient as the electroencephalograph, and the pulse wave can be easily measured by a fingertip volume pulse wave measuring device, so that it can be easily used at a store or an exhibition hall and can be judged quickly. In particular, for brain waves, obtain the time-series change of the distribution rate of the θ-wave, α-wave, and β-wave, and for the pulse wave, obtain the pulse wave muscle fatigue curve that is obtained based on the time-series signal of the slope of the power value. It is said. In the case of an electroencephalogram, when sleepiness occurs, the distribution rate of the θ wave increases, so it is possible to objectively evaluate whether a person is easy to sleep even in a short time, that is, whether it is easy to relax. In the case of a pulse wave, the pulse wave muscle fatigue curve transitions lower, so that it is possible to easily evaluate whether any of the comparison mattresses is less fatigued by the subject and is easier to relax. Moreover, the reliability of evaluation can also be increased by using both together.

  Hereinafter, the present invention will be described in more detail based on embodiments shown in the drawings. FIG. 1 is a block diagram of an evaluation apparatus for a human body support structure according to an embodiment of the present invention. This figure shows a configuration of an evaluation apparatus for measuring an electroencephalogram, and is configured to include a measurement apparatus (electroencephalograph) 10 and a data processing apparatus (for electroencephalogram) 20. The “human body support structure” to be evaluated in the present invention refers only to a structure that supports a person in a sleeping position, and a person is in a predetermined posture against gravity, such as a driver's seat of an automobile. It does not include those used to maintain a stable, stable support for people in a relaxed state. Typically, mattresses, beddings such as futons, or relax chairs, etc., such as passenger seats for cars, seats for passengers on trains, etc. It is also possible to apply it to the evaluation of a human body support structure that requires emphasis on the function of supporting the body.

  In the present embodiment, an electroencephalograph is used as the measuring device 10, but it is preferable to use a simple electroencephalograph that can be easily used without being in a sealed room. As such a simple electroencephalograph, for example, FM-515A manufactured by FUTEK Co., Ltd. can be used.

  The data processing device (for electroencephalogram) 20 performs an analysis process on the electroencephalogram obtained from the measurement device 10 and obtains a time series change of the analyzed data, and an electroencephalogram analysis operation means 21. The brain wave comparison / determination means 22 is configured to compare / determine how the obtained time-series changes appear.

  As shown in FIG. 1, the electroencephalogram analysis calculation means 21 includes a distribution rate calculation means 21a composed of a computer program. In the simplified electroencephalograph, the amplitude spectrum of the frequency component of the θ wave, α wave, and β wave is calculated every predetermined time, for example, every second, but the distribution rate calculating means 21a is obtained every second. The output values of the θ wave, α wave, and β wave are divided from the amplitude spectrum and summed up within a predetermined time range, and each of the θ wave, α wave, and β wave with respect to the sum of all output values of the θ wave, α wave, and β wave The distribution ratio is calculated by the ratio of the total of the individual output values. At this time, the time range in which the output values of the θ wave, the α wave, and the β wave are summed is divided by a predetermined slide wrap ratio and obtained by a slide calculation method. For example, if the slide lap rate is 90%, the total output value of θ wave, α wave, and β wave every second in the time range of 0 second to 180 seconds, 18 seconds to 198 seconds, 36 seconds to 216 seconds Then, each distribution ratio is obtained and plotted to obtain a time series change. Thereby, it becomes easy to grasp the change tendency of the distribution rate of the θ wave, the α wave, and the β wave. Note that preferable values of the time range and the slide lap ratio that are divided when performing slide calculation are the same as the values used in the slide calculation performed in the later-described pulse wave analysis process, and will be described in detail later. The distribution rate calculated by the distribution rate calculation means 21a is output as time series data by the output means 21b and sent to the electroencephalogram comparison / determination means 22.

  Based on the time-series data obtained from the electroencephalogram calculation means 21, the electroencephalogram comparison / determination means 22 is, for example, an upward trend in the distribution rate of the θ wave that predominates during sleepiness and sleep, and predominance during consciousness dispersion and tension. When a tendency to decrease the distribution rate of the β wave appears, it is determined that the state has shifted to sleep. Therefore, when this tendency appears earlier, it is understood that the human body support structure (mattress or the like) is easy for the subject to sleep.

FIG. 2 is a block diagram of an evaluation apparatus for a human body support structure according to another embodiment of the present invention, and shows a configuration of the evaluation apparatus when measuring a pulse wave. The human body support structure evaluation apparatus according to the present embodiment includes a measurement device (fingertip volume pulse wave measuring device) 30 and a data processing device (for pulse wave) 40.
The fingertip volume pulse wave measuring device constituting the measuring device 30 of the present embodiment includes an infrared light emitting diode and a phototransistor, and can measure a pulse wave very simply by being attached to the finger. The data processing device (for pulse wave) 40 includes a pulse wave analysis calculation means 41 and a pulse wave comparison / determination means 42 which are computer programs, and the pulse wave analysis calculation means 41 includes original waveform data. A peak value detecting means 41a, a power value calculating means 41b, a power value inclination calculating means 41c, and a pulse wave muscle fatigue calculating means 41d are provided.

  The original waveform data peak value detecting means 41 a detects the peak value of each period of the original waveform data of the pulse wave obtained by the measuring device 30. Specifically, the original waveform data is smoothed and differentiated by Savitzky and Golay and detected with a predetermined threshold with respect to the fluctuation range of the waveform, preferably 70% of the fluctuation range of the waveform as a threshold, and the peak on the upper limit side is detected. Find the value and the lower limit peak value (bottom value).

  In the power value calculation means 41b, each peak value of the original waveform data of the pulse wave obtained by the original waveform peak value detection means 41a is divided every predetermined time range, for example, every 5 seconds (s). In the time range, an average value of the upper limit side peak value and the lower limit side peak value is obtained, and a difference between them is obtained as a power value. However, in order to emphasize the amount of change, it is preferable to square the difference between the average value of the upper limit side peak value and the average value of the lower limit side peak value in the predetermined time range to obtain the power value.

  The power value inclination calculation means 41c obtains the inclination of the power value obtained by the power value calculation means 41b with respect to the time axis in a predetermined time range by sliding calculation at a predetermined slide lap ratio with respect to the predetermined time. Go. The slide calculation is performed as follows.

For example, when the inclination during T seconds (s) is obtained at a slide lap ratio of 90%, first, the peak value of the maximum Lyapunov exponent between 0 (s) and T (s) and the time axis of the power value are plotted. The slope is obtained by least square approximation. Then
Slide calculation (1): Between T / 10 (s) and T + T / 10 (s),
Slide calculation (2): Between 2 × T / 10 (s) and T + 2 × T / 10 (s),
Slide calculation (n): Each slope between n × T / 10 (s) and T + n × T / 10 (s) is obtained by least square approximation.

  Here, in order to grasp the characteristics of the power value in the time domain globally, the sampling time interval (T seconds) when performing the slide calculation is optimally 180 seconds, and the slide lap ratio is optimally 90%. is there. Note that the value of the slide lap ratio of 90% for the time interval of 180 seconds is preferably used in the same manner for the distribution rate calculation means 21a of the electroencephalogram analysis calculation means 21 in the one embodiment. The reason why the slide lap ratio of 90% was determined to be optimal for a time interval of 180 seconds was obtained from the results of performing a 30-minute sleep experiment under the same environment, collecting fingertip volume pulse waves, and analyzing them. This is reported in Japanese Patent Application No. 2003-363902 by the present applicant. Attenuation of upper central excitability due to fatigue and involvement of peripheral inhibitory reflex mechanisms reduces muscle activity commands, but is associated with recovery of central excitability in 180 seconds when blood flow returns to normal It is predicted that

  The pulse wave muscle fatigue degree calculating means 41d performs absolute value processing on the time series signal of the power value inclination obtained by the power value inclination calculating means 41b, calculates an integrated value, and calculates the integrated value as the fatigue degree. To do. Then, the fatigue level calculated by the pulse wave muscle fatigue calculating unit 41d is output as time series data by the output unit 41e to obtain a pulse wave muscle fatigue curve. Thereby, the degree of fatigue can be quantified and can be objectively grasped.

  The pulse wave comparison / determination means 42 has a high degree of relaxation for the subject and can provide a comfortable sleep when the fatigue level transition is lower due to the pulse wave muscle fatigue curve sent from the output means 41e. It is determined that the structure is a support structure (mattress or the like).

  Further, the pulse wave analysis calculation means 41 may be configured to include a frequency analysis means for performing frequency analysis on the original waveform data of the pulse wave. In this case, the pulse wave comparison / determination means 42 compares and determines the frequency and peak value of the peak frequency band. That is, when the peak frequency band is shifted to a higher frequency side or when the human body support structure (mattress etc.) where the peak value is higher is compared with the human body support structure (mattress etc.) showing the opposite tendency, the pulse rate, It shows that blood flow is high, tension is high, and relaxation is low.

The pulse wave analysis computing means 41 may have a structure having both the means for obtaining the pulse wave muscle fatigue curve and the means by frequency analysis. In this case, the determination by the pulse wave comparison / determination means 42 is performed. Increased reliability of results. Furthermore, the analysis using the electroencephalogram described in the one embodiment can be used in combination with the analysis using the pulse wave of the present embodiment.
In the above description, the distribution rate calculation means 21a that performs the slide calculation by adding the distribution rates of the θ wave, α wave, and β wave in a predetermined time range is used as the electroencephalogram analysis calculation means 21. The slope of the distribution rate, which is the rate of change in the output value of the θ wave, α wave, and β wave that are output from the electroencephalograph every second, in a predetermined time range (for example, 180 seconds), rather than being compared in total In the same manner as described above, for example, slide calculation is performed with a slide lap ratio of 90%, and a time series change in the slope of the distribution ratio can be obtained. According to the time-series change of the slope of the distribution rate, it can be easily determined whether or not the vehicle has approached the stable region based on the fluctuation range.

(Test example)
Two types of mattresses were used as the human body support structure, and a 30-minute nap experiment was performed by three subjects (subjects A, B, and C). The experiment time was from 2 to 4 pm, which is easily affected by sleepiness, and each subject took a nap on a different mattress in the same time zone on another day to reduce the influence of biological fluctuations due to circadian rhythms and the like.

  The mattress used is composed of a three-dimensional knitted fabric, has an appropriate elasticity, and has a spring characteristic close to that of the muscles of the human body, that is, exhibits a soft spring characteristic with a one-point concentrated load. A surface contact having a large size has a surface rigidity and a hard spring characteristic (mattress A), and a low rebound and high attenuation material (mattress B) made of viscoelastic urethane.

  In the measurement of the electroencephalogram, FM515A manufactured by FUTEK Co., Ltd. was used as a simple electroencephalograph as the measuring apparatus 10. In this case, the amplitude spectrum of the frequency components of the θ wave, α wave, and β wave is output in real time per second, and this was performed by wearing the head of each subject. In the measurement of the pulse wave, an optical pulse wave meter manufactured by Computer Convenience Co., Ltd. was used as a fingertip volume pulse wave measuring device as the measuring device 30. This is composed of an infrared light emitting diode and a phototransistor, and uses a time series signal obtained by performing A / D conversion by amplifying a signal with a power amplifier and applying a 10 Hz low-pass filter as the original waveform data. It was possible to wear it on the left index finger of each subject. The sampling frequency of the pulse wave was 200 Hz and the resolution was 12 bits.

The data obtained by the measuring devices 10 and 30 were arithmetically processed by the data processing devices 20 and 40, respectively, and the results were output.
In addition, during the experiment, an observer who observes the state of the subject was placed, and after the experiment, sensory evaluation was performed based on subjective judgment of each subject.

(EEG distribution rate)
FIGS. 3A to 3B show the distribution rates of the θ wave, α wave, and β wave of the brain wave of the subject A obtained by the electroencephalogram analysis calculation means 21, and among these, FIG. Shows the experimental results using the mattress A, and FIG. 3B shows the experimental results using the mattress B, respectively.

  From FIG. 3 (a), it can be seen that the distribution rate of the .beta. Wave tends to decrease immediately after the start of the experiment, whereas the distribution rate of the .theta. In addition, in the vicinity of 800 to 950 seconds, it can be seen that the distribution rate of the θ wave is higher than the α wave indicating the degree of relaxation in the awake state, leading to a deeper sleep state. As a result, when the subject A uses the mattress A, it can be determined that the transition period to sleep onset occurs immediately after the start of the experiment, and the patient enters the sleep stage from around 400 seconds.

  On the other hand, in FIG. 3B, a sudden increase in the θ wave and a decrease in the α wave are observed from immediately after the start of the experiment to around 400 seconds, but the β wave hardly fluctuates. In addition, after 400 seconds, the α wave distribution rate remains higher than the θ wave, and the β wave does not decrease. Therefore, it can be seen from FIG. 3B that the subject A who took a nap on the mattress B was in a light sleep state.

  In the inspection by the observer, it was confirmed that when the mattress A was used, the subject A fell into a deep sleep state at an early stage after the eyes were closed. In addition, subject A commented after the experiment that mattress B had a low rebound, so the body was sinking and it was difficult to fall asleep, while mattress A was very sleepy, both for EEG analysis This coincided with the fact that it can be determined from the output result of the computing means 21.

  Therefore, when the mattress A and the mattress B are compared with each other by using the electroencephalogram analysis calculation means 21, it can be objectively determined that the mattress A is more suitable for the subject A.

(Pulse muscle fatigue curve)
4A to 4C are diagrams showing pulse wave muscle fatigue curves of subjects A, B, and C obtained by the pulse wave analysis calculation means 41. FIG.
From FIG. 4A, the fatigue level of the subject A is lower in the mattress A than in the mattress B. Therefore, it can be seen from this pulse wave muscle fatigue curve that the mattress A can be shifted to sleep more comfortably and quickly for the subject A. Further, looking at the slope of the pulse wave muscle fatigue curve of FIG. 4A, the slope is lower than before about 300 seconds for the mattress A and about 450 seconds for the mattress B, respectively. The point in time when the change in the slope appears is substantially coincident with the timing at which it is possible to determine that the brain wave analysis computing means 21 has shifted to sleep and the timing at which it is possible to determine that it has shifted to sleep by inspection. It can be determined that the time point at which the change in the slope appears is the stage of transition to sleep.

  4 (b) and 4 (c), it can be seen that the other subjects B and C also have lower fatigue levels in the mattress A than in the mattress B. A high degree of fatigue means that muscles are frequently used in the sleeping posture, and for subjects A, B, and C, the mattress A maintains a relaxed and correct sleeping posture. It can be judged that it can be done.

(Pulse wave frequency analysis)
FIGS. 5A to 5B are diagrams showing the frequency analysis result of the fingertip volume pulse wave of the subject A obtained by using what has frequency analysis means as the pulse wave analysis calculation means 41. FIG. is there.
From this result, the mattress B has a peak frequency band shifted to a higher frequency side than the mattress A, and has a slightly higher peak value. This shows that when mattress B is used, both the pulse rate and blood flow rate are higher than when mattress A is used, and the sleeping posture using muscles is greater. You can see that the degree of relaxation is high.
Only the frequency analysis does not know the timing of the sleep transition period, but by using it together with the above-described brain wave distribution rate and pulse wave muscle fatigue curve, it is possible to more accurately determine which mattress is suitable.

(EEG distribution rate slope)
6 (a) to 6 (b) use the data when the time series change of the distribution rate of FIGS. 3 (a) to 3 (b) is used, and the distribution of the θ wave, α wave, and β wave every 180 seconds. It is a figure which shows the time-sequential change of the distribution rate inclination which calculated | required the inclination of the rate (ratio of change), and calculated this by sliding at a slide lap rate of 90% as mentioned above.
From this result, it can be seen that the inclination of the distribution ratio of the θ wave, the α wave, and the β wave changes in a stable region in which the mattress A is closer to the inclination 0 than the mattress B. In the case of the mattress B, in particular, the fluctuation up to 400 seconds is large and the sleep is poor, and the fluctuation of the θ wave, α wave, and β wave is large even in the time zone of 600 seconds to 800 seconds and thereafter, Move, and you can see that you have not had a relaxed and stable sleep.
FIGS. 7A to 7B show the frequency analysis results of the time series change of the distribution rate slopes of FIGS. 6A to 6B. The peak value of the power spectrum is also obtained by this frequency analysis. However, the mattress A is much smaller than the mattress B, and it can be seen that the mattress A has a relaxed and stable sleeping posture.

  In the above test example, the electroencephalogram or pulse wave is measured for 30 minutes. From FIG. If the evaluation index is used, or if the transition tendency of the pulse wave muscle fatigue curve or the frequency analysis is used as the evaluation index from FIGS. 4 and 5, the comfort level of the subject due to the difference in the mattress can be determined even in about 15 minutes. Further, according to the analysis of the slope of the distribution rate of the electroencephalograms in FIGS. 6 and 7, it can be determined more clearly whether or not the region is a stable region. You can analyze the comfort level due to the closeness of the mattress. Therefore, the present invention is suitable for evaluating the human body support structure in a short time.

  In the above embodiments, brain waves and pulse waves are used. However, it is predicted that respiration is measured and processed in the same manner as in the case of pulse waves, and can be applied to the evaluation of the human body support structure.

FIG. 1 is a block diagram showing the configuration of a human body support structure evaluation apparatus according to an embodiment of the present invention. FIG. 2 is a block diagram showing a configuration of a human body support structure evaluation apparatus according to another embodiment of the present invention. FIG. 3 is an output result of the distribution rate of the brain wave (θ wave, α wave, β wave) of the subject A obtained by the nap experiment, (a) shows the result of the experiment with the mattress A, and (b) shows the mattress. It is a figure which shows the result of having experimented with B. FIGS. 4A to 4C are diagrams showing pulse wave muscle fatigue curves of subjects A, B, and C obtained by a nap experiment. FIGS. 5A and 5B are diagrams showing the results of frequency analysis of the pulse wave of the subject A obtained by the nap experiment. FIG. 5A shows the result of the experiment with the mattress A, and FIG. 5B shows the result of the experiment with the mattress B. FIG. FIG. 6 is an output result of the gradient of the distribution rate of the brain wave (θ wave, α wave, β wave) of the subject A obtained by the nap experiment, (a) is the result of the experiment with the mattress A, (b) These are figures which show the result of having experimented with the mattress B. FIG. FIG. 7 is a diagram showing the frequency analysis result of the gradient of the distribution rate of the electroencephalograms (θ wave, α wave, β wave) obtained in FIG. 6, (a) shows the result of the mattress A, (b) shows the result. It is a figure which shows the result of the mattress B.

Explanation of symbols

10 Measuring device (electroencephalograph)
20 Data processor (for EEG)
21. Calculation means for electroencephalogram analysis 21a Distribution rate calculation means 21b Output means 22 Comparison / determination means for electroencephalogram 30 Measuring device (finger plethysmograph)
40 Data processor (for pulse wave)
41 Pulse wave analysis calculation means 41a Original waveform data peak value calculation means 41b Power value calculation means 41c Power value slope calculation means 41d Pulse wave muscle fatigue calculation means 41e Output means 42 Pulse wave comparison / determination means

Claims (5)

An evaluation apparatus for a human body support structure for supporting a person in a sleeping posture state,
  Original waveform data peak value detection means for measuring a fingertip volume pulse wave of a person supported in a sleeping posture on the human body support structure and detecting a peak value of each cycle of the original waveform of the obtained fingertip volume pulse wave When,
Calculate the difference between the peak value on the upper limit side and the peak value on the lower limit side for each predetermined time range from each peak value obtained by the original waveform data peak value detection means, and set the difference as a power value. Means,
A power value slope calculating means for obtaining a slope of the power value with respect to a time axis in a predetermined time range by performing slide calculation a predetermined number of times at a predetermined lap rate with respect to the predetermined time;
The pulse value muscle fatigue level for calculating the integral value by calculating the absolute value of the time series signal of the power value gradient obtained by the slide calculation by the power value gradient calculating means, and calculating the obtained integral value as the fatigue level A calculation means;
For the pulse wave, the human body support structure in which the pulse wave muscle fatigue curve indicating the transition of the fatigue level output by the pulse wave muscle fatigue level calculation unit appears relatively low is determined as a human body support structure that can provide a more comfortable state. Comparison / determination means
An apparatus for evaluating a human body support structure, comprising: Furthermore, it has a frequency analysis means for frequency analysis of the original waveform data,
The pulse wave comparison / determination means uses the appearance position and / or peak value height of the peak frequency band obtained by the frequency analysis means as an evaluation index, and the peak frequency band is relatively shifted to the lower frequency side. The human body support structure evaluation apparatus according to claim 1, wherein the human body support structure that appears or the human body support structure whose peak value appears relatively low is determined as a human body support structure having a higher degree of relaxation. Furthermore, a distribution rate calculation means for measuring a brain wave of a person supported in a sleeping posture and obtaining a time-series change in the distribution rate of the obtained brain wave θ wave, α wave, β wave,
EEG comparison / determination means for determining whether or not a transition from time series change of distribution ratio obtained by the distribution ratio calculation means has shifted to sleep;
The apparatus for evaluating a human body support structure according to claim 2, comprising: The electroencephalogram comparison / determination means shifts to sleep when an increase tendency of the distribution ratio of the θ wave and a decrease tendency of the distribution ratio of the β wave appear in the time series change of the distribution ratio obtained by the distribution ratio calculation means. The apparatus for evaluating a human body support structure according to claim 3, wherein it is determined that the human body support has been performed. The distribution rate calculating means obtains the slope of the distribution rate of the electroencephalogram θ wave, α wave, and β wave in a predetermined time range by performing slide calculation with a predetermined slide wrap rate, and changes the slope of the distribution rate over time. The apparatus for evaluating a human body support structure according to claim 3, characterized in that:

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