JP6976387B2 - Evaluation device and program - Google Patents

Description

The present invention relates to a sleep evaluation device and the like.

Conventionally, a technique for estimating the sleep stage by PSG from heartbeat / respiratory information has been known. For example, there is known a sleep stage determination device that determines that a person is in a deep sleep state when the respiratory rate, the variation in the respiratory rate, and the variation in the respiratory cycle within a predetermined time are equal to or less than the threshold value and there is no body movement (for example). , See Patent Document 1).

Further, there is known a sleep state estimation device that estimates a sleep state from the coefficient of variation of the variance of the peak interval of the respiratory waveform and the coefficient of variation of the variance of the peak value (see, for example, Patent Document 2).

Japanese Patent No. 4582642 Japanese Patent No. 37333133

The above-mentioned technique uses the respiratory cycle / interval and the respiratory peak value for evaluation, but there is a problem that it is difficult to accurately detect the sleep state from the respiratory waveform because it is input with various noises. ..

In addition, the respiratory waveform changes separately from the original factor of the human body due to the relative positional relationship between the sensor such as the sleeping position and the human body in the wearable sensor and the non-wearable sensor. When a lot of measurement information is used, if all the measurement items can be measured accurately, the accuracy of the final evaluation result may be improved, but if there is a measurement item with low accuracy, the measurement item is concerned. There was a problem that the accuracy of the final evaluation result was lowered because it was pulled by.

In view of the above-mentioned problems, an object of the present invention is to easily and accurately evaluate sleep by using, for example, respiratory rate or heart rate as biological information within a predetermined time of the subject. It is to provide a sleep evaluation device and the like that can be used.

In order to solve the above-mentioned problems, the evaluation device of the present invention comprises a detecting means for detecting the breathing of the measured person and the breathing rate of the measured person in the first period in which the measured person uses the first bedding. A calculation means for calculating the first coefficient of variation based on the above, and calculating the second coefficient of variation based on the respiratory rate of the person to be measured in the second period in which the person to be measured uses the second bedding, and the first method. The coefficient of variation is compared with the coefficient of variation of the second, and the first bedding and the evaluation means for evaluating the sleeping comfort of the second bedding are provided.

The program of the present invention provides a computer with a detection function for detecting the breath of the subject and a first coefficient of variation based on the respiratory rate of the subject during the first period in which the subject uses the first bedding. The calculation function for calculating the second coefficient of variation based on the respiratory rate of the person to be measured in the second period in which the person to be measured uses the second bedding, the first coefficient of variation, and the first It is characterized by realizing an evaluation function for evaluating the sleeping comfort of the first bedding and the second bedding by comparing with the coefficient of variation of 2.

According to the sleep evaluation device of the present invention, respiration is detected as biological information of the person to be measured, and the respiration rate included in the respiration rate calculation time is output from the detected respiration. Then, the coefficient of variation of the respiratory rate can be calculated from the average value of the respiratory rate included in the coefficient of variation calculation section and the standard deviation of the respiratory rate, and the sleep state of the subject can be evaluated from the coefficient of variation. This makes it possible to evaluate the sleep state based on the respiration (number) included in the fluctuation coefficient calculation section, and when evaluating the sleep state in a short section (for example, one respiration or one minute of respiration). It is possible to make an appropriate evaluation by comparing with.

Further, according to the sleep evaluation device of the present invention, sleep evaluation can be performed using the heart rate (heart rate) as the biological information of the person to be measured. This makes it possible to appropriately evaluate the sleep state by using a simple device for calculating the heart rate.

It is a figure for demonstrating the whole in this embodiment. It is a figure for demonstrating the functional structure in this embodiment. It is a figure which shows an example of the data structure of the respiratory rate table in this embodiment. It is a figure which shows an example of the data structure of the coefficient of variation table in this embodiment. It is a figure for demonstrating the correspondence between the respiratory rate and the sleep state. It is a figure which shows the data flow of the section respiratory rate output processing in this embodiment. It is a figure which shows the data flow of the coefficient of variation calculation processing in this embodiment. It is a figure which shows the data flow of the sleep evaluation processing in this embodiment. It is a figure which showed the plot of the respiratory rate. It is a figure for demonstrating the correlation of the respiratory rate.

Hereinafter, the best mode for carrying out the present invention will be described with reference to the drawings.
[1. System appearance]
FIG. 1 is a diagram for explaining how to use the sleep evaluation system. As shown in FIG. 1, the sleep evaluation system 1 includes a detection device 3 placed between the floor of the bed 10 and the mattress 20, and a processing device 5 for processing the value output from the detection device 3. It is configured in preparation. The detection device 3 and the processing device 5 constitute a sleep evaluation device.

When the person to be measured P is on the mattress 20, the detection device 3 detects the body movement (vibration) of the person to be measured P via the mattress 20. Then, based on the detected vibration, the respiration of the subject P (respiratory rate within a predetermined time) is detected (output). In the present embodiment, the detected respiration rate (number) is transmitted to the processing device 5 (for example, a computer or the like) via radio, but the detection device 3 is integrally formed by providing a display unit or the like, for example. May be good. Further, since the processing device 5 may be a general-purpose device, it is not limited to an information processing device such as a computer, and may be configured by a device such as a tablet or a smartphone.

Here, the detection device 3 is configured in a sheet shape so as to be thin. As a result, even if it is placed between the bed 10 and the mattress 20, it can be used without causing the subject P to feel a sense of discomfort.

It is sufficient that the detection device 3 can detect the respiration of the person to be measured P. In the present embodiment, the respiration is detected based on the body movement, but for example, the breath sound is detected by using a voice sensor, the body movement of the subject P is detected by an infrared sensor or the like, or distortion is detected. An actuator with a gauge may be used.

[2. Function configuration]
Subsequently, the mechanical configuration of the sleep evaluation system 1 will be described with reference to FIG. The sleep evaluation system 1 in the present embodiment has a configuration including a detection device 3 and a processing device 5, and each functional unit (processing) may be realized by any other than the respiratory detection unit 200.

In the sleep evaluation system 1, the respiration detection unit 200, the storage unit 300, and the input unit 400 are connected to the control unit 100 via a bus.

The control unit 100 is a functional unit for controlling the operation of the sleep evaluation system 1, and is composed of a control circuit necessary for the sleep evaluation system 1 such as a CPU. The control unit 100 realizes various processes by reading and executing various programs stored in the storage unit 300. In the present embodiment, the control unit 100 operates as a whole, but is provided in each of the detection device 3 and the processing device 5.

The respiration detection unit 200 is a functional unit for detecting the respiration of the subject. In the present embodiment, it is a sensor unit for detecting vibration. The respiration of the person to be measured is detected from the vibration (body movement) detected by the sensor unit. Further, by using the sensor unit, it is possible to detect body movements other than respiration of the person to be measured, such as turning over and heartbeat.

The breathing detection unit 200 in the present embodiment detects the vibration (body movement) of the person to be measured by the pressure sensor and detects the breathing from the vibration, but the load sensor detects the position of the center of gravity (body movement) of the person to be measured. Breathing may be detected by the change of the microphone, or may be detected based on the sound picked up by the microphone by providing the microphone. It suffices if the respiration of the subject can be detected using any of the sensors.

The storage unit 300 is a functional unit that stores various data and programs for operating the sleep evaluation system 1. The control unit 100 realizes various functions by reading and executing the program stored in the storage unit 300. Here, the storage unit 300 is composed of, for example, a semiconductor memory, a magnetic disk device, or the like.

Here, the respiratory rate table 302 and the coefficient of variation table 304 are stored in the storage unit 300, and the respiratory rate output program 310, the coefficient of variation calculation program 312, and the sleep evaluation program 320 are stored as programs. ing.

The respiratory rate table 302 is a table in which the respiratory rate output based on the breath detected by the respiratory detection unit 200 is stored. As shown in FIG. 3, the respiratory rate table 302 stores the respiratory rate in a predetermined time (hereinafter referred to as “respiratory rate calculation time”) in a time series. The respiratory rate calculation time in this embodiment is set to "1 minute" as an example.

Further, the respiratory rate table 302 may be configured to be stored in a plurality for each identification information. By using the identification information, for example, it may be stored for each person to be measured, or even for the same person to be measured, it may be stored separately for each measurement day.

The coefficient of variation table 304 is a table in which the coefficient of variation calculated based on the calculated respiratory rate is stored. As shown in FIG. 4, the identification information, the section information, and the coefficient of variation are stored in association with each other.

As for the identification information, as described above, for example, the identification information is attached to each person to be measured, or the identification information is attached to each measurement day to evaluate the sleep of each person to be measured or to evaluate the sleep of each measurement day. It becomes possible to do.

The section information is information for setting a section for calculating the coefficient of variation (hereinafter referred to as "coefficient of variation calculation section"). The coefficient of variation calculation section is preset in correspondence with the section information. For example, the section information "a01" can be set to the first half of the sleep time, that is, 240 minutes from the start of sleep. In addition, it is possible to make various settings such as the ratio of the total sleep time (for example, 30% from the start of sleep), comparison in the latter half of sleep, and sleep time (for example, 3:00 am to 5:00 am). be.

These coefficient of variation calculation sections are preset and may be selected by the measurer (user), or a plurality of coefficient of variation calculation sections may be arbitrarily set by the measurer (user). good.

The coefficient of variation is a coefficient calculated from the respiratory rate in the above-mentioned coefficient of variation calculation section. Specifically, the standard deviation of the respiratory rate in the coefficient of variation calculation section is calculated. In addition, the average respiratory rate in the coefficient of variation calculation section is calculated. The coefficient of variation is the coefficient of variation calculated by dividing the calculated standard deviation by the average respiratory rate.

Here, when the coefficient of variation is small, it is determined that the breathing is stable and the person is sleeping well. If the coefficient of variation is large, it is determined to be in a wakefulness state or a REM sleep state.

This is because the overnight average of the respiratory rate per unit time is highly reproducible for the same individual, and the variation in the respiratory rate per unit time reflects the sleep state. The sleep state can be evaluated by the average of the respiratory rate per unit time (respiratory rate calculation time) within a predetermined time (coefficient of variation calculation interval) and the variation (standard deviation) of the respiratory rate per unit time.

This point will be further described with reference to FIG. FIG. 5 is a graph measuring the relationship between the sleep stage of a certain measurer and the respiratory rate. The horizontal axis shows time.

The line graph is a graph showing the result of measuring the sleep stage of the subject by the polysomnography test. As shown to the right, it is represented by stages 0 to 4, where "0" indicates arousal, "0.5" indicates REM sleep, and "1-4" indicates stages 1 to 4 of NREM (non-REM) sleep. There is. Furthermore, the higher the number, the deeper the sleep.

On the other hand, the respiratory rate is superimposed on the graph and displayed. As shown on the left vertical axis, the respiratory rate per minute is displayed.

According to FIG. 5A, it can be read from the graph that the more stable and persistent the sleep is, the smaller the fluctuation of the respiratory rate is. On the other hand, according to FIG. 5B, it can be read that the fluctuation of the respiratory rate is large when awakening is frequently mixed in the middle of sleep and is not stable.

As described above, it was found that the sleep stage and the respiratory rate have a certain relationship, but there is no clear relationship such that the sleep stage can be estimated every minute (every predetermined time). Therefore, it is a feature of this embodiment that sleep is evaluated based on the tendency of the whole sleep or a long time such as the first half and the second half.

The input unit 400 is a functional unit for the measurer to give an instruction / operation to the sleep evaluation system 1. For example, it is composed of an operation button, a touch panel, a voice input device, and the like.

The display unit 500 is a functional unit for displaying the sleep state and the evaluation, and displaying the operation of the sleep evaluation system 1. For example, it is composed of a display device such as a liquid crystal display.

[3. Processing flow]
Subsequently, the processing flow of the sleep evaluation system 1 in the present embodiment will be described.

[3.1 Respiratory rate output processing]
The respiratory rate output process will be described with reference to FIG. The respiratory rate output process is a process realized by reading out the respiratory rate output program 310 in FIG. 2 and executing it by the control unit 100.

Respiration is detected by the respiration detection unit 200 (step S102). Subsequently, it is determined whether or not the respiratory rate calculation time has elapsed (step S104). Here, when the respiratory rate calculation time elapses (step S104; Yes), the respiratory rate detected in the respiratory rate calculation time is output to the respiratory rate table 302 as the respiratory rate (step S106). This process is repeatedly executed until the respiratory rate output process is completed (step S108; No → step S102).

[3.2 Coefficient of variation calculation process]
The coefficient of variation calculation process will be described with reference to FIG. 7. The coefficient of variation calculation process is a process realized by reading the coefficient of variation calculation program 312 in FIG. 2 and executing it by the control unit 100.

First, the respiratory rate in the coefficient of variation calculation section is extracted from the respiratory rate table 302 (step S202). Specifically, the respiratory rates included in the coefficient of variation calculation section corresponding to the extracted target identification information are extracted.

Subsequently, the coefficient of variation is calculated based on the extracted respiratory rate (step S204). Specifically, first, the standard deviation of the respiratory rate included in the coefficient of variation calculation section is calculated. Next, the average value of the respiratory rate included in the coefficient of variation calculation section is calculated.

Then, the coefficient of variation is calculated by dividing the calculated standard deviation by the calculated average value. The calculated coefficient of variation is attached to the target identification information and the information indicating the coefficient of variation calculation section, and is output to the coefficient of variation table 304 as the coefficient of variation and stored (step S206).

[3.3 Sleep evaluation processing]
Subsequently, the sleep evaluation process based on the coefficient of variation will be described with reference to FIG. First, the identification information and the section information are determined (step S302). For example, the target of the identification information for evaluating sleep is determined, such as using only "001" as the identification information or using "001" to "003".

In addition, the section information for reading the coefficient of variation is also determined. For example, the coefficient of variation to be extracted is the coefficient of variation calculated based on "240 minutes" after the start of sleep, and the range to be calculated and the target are determined based on the section information.

The determination of the identification information and the interval information may be arbitrarily determined by the measurer or may be predetermined.

Next, the coefficient of variation is read out based on the identification information and the interval information (step S304). Here, when a plurality of identification information or interval information is specified, the coefficient of variation corresponding to all the identification information (interval information) is read out (step S306; Yes → step S304). That is, when there are a plurality of coefficients of variation that need to be read, a plurality of coefficients of variation are read.

Then, the read coefficient of variation is compared (step S308), and a process of outputting an evaluation based on the comparison result is executed (step S310).

Specifically, when the coefficient of variation is smaller than a predetermined value, the sleep state is evaluated as good, and when the coefficient of variation is larger than the predetermined value, the sleep state is evaluated as bad. The criteria for this evaluation include, for example, an average value of a plurality of subjects, a preset reference value, or an average value of the same subject, in order to evaluate sleep. It is a standard value of. For example, where in the distribution of values of the same age is evaluated by an index such as a deviation value.

[4. Example]
Subsequently, an example using the sleep evaluation system 1 in the present embodiment will be described. In the present embodiment, as shown in FIG. 1, a device for detecting respiration is placed under the person to be measured, and respiration is detected from the body movement of the person to be measured and executed.

[4.1 First Example]
As a first embodiment, a case where the sleeping comfort of two beddings is evaluated will be described. In this case, the identification information of the first product is "001" and the identification information of the second product is "002". Further, as the section information, 240 minutes from the start of sleep is set as the section information "a01", and the coefficient of variation is calculated.

FIG. 9 shows a state in which the respiratory rate is plotted. FIG. 9 (a) is a plot of respiratory rate by the first product, and FIG. 9 (b) is a plot of respiratory rate by the second product.

Here, in each graph, the respiratory rate of the dotted line portion is the respiratory rate included in the section information “a01”. Therefore, first, the coefficient of variation of the respiratory rate included in the section information "a01" (240 minutes from the start of sleep) is calculated (S204 in FIG. 7) and output to the coefficient of variation table 304 (step S206).

After that, the coefficient of variation of the first product of the identification information "001" (FIG. 9 (a)) and the coefficient of variation of the second product of the identification information "002" (FIG. 9 (b)) are compared. In this case, since the coefficient of variation is lower in the first product (FIG. 9A), it is evaluated that the first product has a better sleep state as a sleep evaluation.

As a result, it can be seen that the first product is a product that is more comfortable for the person to be measured, and the comfort of the bedding can be appropriately understood.

By measuring the above-mentioned coefficient of variation by a plurality of people, it is possible to evaluate each product. For example, when comparing the first product and the second product, if more people have a smaller coefficient of variation in the second product, the second product can be evaluated as a more comfortable bedding.

Further, FIG. 10 shows an example of actual data when two products are evaluated. FIG. 10 is data showing the coefficient of variation of 10 subjects for the product A as the first product and the product B as the second product. In FIG. 10, the average value of the coefficient of variation of product A and the average value of the coefficient of variation of product B are calculated.

Then, when a paired t-test is performed based on the coefficient of variation of product A and the coefficient of variation of product B, the coefficient of variation of product B is statistically significantly smaller. Therefore, it can be evaluated that the B product is a mattress that can obtain better sleep.

[4.2 Second Example]
As the second embodiment, an example used when evaluating the physical condition of the subject will be described. In this case, the identification information of the previous day is set to "001" and the identification information of the day is set to "002", and predetermined section information (for example, the first 1/3 section from bedtime to waking up in the sleeping time) is set. ..

For example, it is possible to compare the coefficient of variation based on the identification information of the previous day and the coefficient of variation based on the identification information of the current day, and evaluate that the physical condition is not good due to the increase in the coefficient of variation.

[4.3 Third Example]
As a third embodiment, a case where the fluctuation information is calculated excluding the awakening time will be described.

That is, the content of sleep can be evaluated separately from the amount of awakening time by excluding the awakening time. Therefore, the respiratory rate table 302 also stores the classification of sleep and wakefulness (or, as a separate table, the classification of sleep and wakefulness may be stored in association with the date and time).

Then, when calculating the coefficient of variation in step S204 of FIG. 7, the coefficient of variation is calculated by excluding the respiratory rate at the time determined to be awakening.

This makes it possible to exclude respiratory fluctuations due to arousal, and it is possible to evaluate the quality of the content not only by the amount of awakening time during sleep but also by the same sleep determination. Therefore, a more detailed sleep evaluation can be performed.

[4.4 Fourth Example]
As the fourth embodiment, a sleep evaluation report may be output based on the calculated coefficient of variation. That is, the report on the sleep evaluation of the subject is output from the coefficient of variation, the comparison with the coefficient of variation from the previous day, and the comparison with the average of the coefficient of variation.

Further, the basic information (age, gender, sleep time, etc.) of the person to be measured and the average coefficient of variation are stored in advance. From the difference between the calculated coefficient of variation and the stored coefficient of variation, the sleep state of the subject may be evaluated and output as a sleep evaluation report.

[5. Modification example]
Although the embodiment of the present invention has been described in detail with reference to the drawings, the specific configuration is not limited to this embodiment, and the design and the like within a range not deviating from the gist of the present invention are also within the scope of claims. include.

In the above-described embodiment, the respiratory rate has been described as an example of the biological information, but the heart rate may be used as the biological information of the person to be measured in the same manner. That is, by using the detected respiration as the heart rate and the respiration rate as the heart rate, it is possible to perform the same sleep evaluation.

By using heart rate (number) instead of respiration (number) as biometric information, it is possible to appropriately evaluate sleep by using a conventional device that detects heart rate, such as an electrocardiograph. There is.

Further, in the above-described embodiment, for convenience of explanation, the coefficient of variation is once stored in the coefficient of variation table 304. However, the coefficient of variation may be calculated each time based on the respiratory rate read from the respiratory rate table.

1 Sleep evaluation system 3 Detection device 5 Processing device 10 Bed 20 Mattress 100 Control unit 200 Respiration detection unit 300 Storage unit 302 Respiratory rate table 304 Fluctuation coefficient table 310 Respiratory rate output program 312 Fluctuation coefficient calculation program 320 Sleep evaluation program 400 Input unit 500 Display

Claims (4)

Detection means to detect the breathing of the subject,
The first coefficient of variation was calculated based on the respiratory rate of the subject during the first period in which the subject used the first bedding.
A calculation means for calculating the second coefficient of variation based on the respiratory rate of the person to be measured in the second period during which the person to be measured uses the second bedding.
Said first coefficient of variation, and the second comparing the coefficient of variation, evaluation means for evaluating the comfort of the first bedding and the second bedding,
An evaluation device characterized by being provided with. The evaluation device according to claim 1, wherein the first period or the second period is 2 hours or more in one night or 30% or more of the total sleep time. Claim 1 or claim , wherein the calculation means calculates the first coefficient of variation or the second coefficient of variation by excluding the biological information of the time when the person to be measured is determined to be awake. Item 2. The evaluation device according to item 2. On the computer
A detection function that detects the breathing of the subject and
The measured person is put calculate the first variation coefficient based on the respiration rate of the person to be measured in the first period using the first bedding,
A calculation function for calculating the second coefficient of variation based on the respiratory rate of the subject in the second period in which the subject uses the second bedding, and a calculation function.
An evaluation function that compares the first coefficient of variation with the second coefficient of variation and evaluates the sleeping comfort of the first bedding and the second bedding.
A program characterized by realizing.

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