JP6745379B2 - Evaluation device and program - Google Patents

Description

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

Conventionally, there is known a technique for estimating a sleep stage by PSG from heartbeat/respiration information. 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 within a predetermined period of time, the variation of the respiratory rate, and the variation of the respiratory cycle are less than or equal to a threshold value, and there is no body movement (for example, , Patent Document 1).

There is also known a sleep state estimation device that estimates a sleep state from a coefficient of variation of variance of peak intervals of a respiratory waveform and a coefficient of variation of variance of peak values (for example, see Patent Document 2).

Japanese Patent No. 4582642 Japanese Patent No. 3733133

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

In addition, the respiratory waveform changes from the original factor of the human body due to the wearing position of the wearable sensor and the relative positional relationship between the sensor such as the sleeping position and the human body of the non-wearing sensor. When a large amount of measurement information is used, the accuracy of the final evaluation result may improve if all measurement items can be measured with high accuracy, but if there are measurement items with low accuracy, However, there is a problem that the accuracy of the final evaluation result is lowered.

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

In order to solve the problems described above, the sleep evaluation device of the present invention,
Detection means for detecting the breathing or heartbeat of the subject, which can measure the number of times per unit time,
Calculating first information indicating a deviation from the first average of the respiratory rate or the heart rate per unit time included in the first section of the first day,
Calculation means for calculating second information indicating a deviation from the second average of the respiratory rate or heart rate per unit time included in the second section of the second day different from the first day;
Evaluation means for evaluating the sleep state of the measurement subject from the first information and the second information,
It is characterized by including.

The sleep evaluation program of the present invention is
On the computer,
A detection function that detects the breathing or heartbeat of the measurement subject that can measure the number of times per unit time,
Calculating first information indicating a deviation from the first average of the respiratory rate or the heart rate per unit time included in the first section of the first day,
A calculation function of calculating second information indicating a deviation from the second average of the respiratory rate or heart rate per unit time included in the second section of the second day different from the first day;
An evaluation function for evaluating the sleep state of the measurement subject from the first information and the second information,
It is characterized by realizing.

According to the sleep evaluation device of the present invention, respiration is detected as the biological information of the measurement subject, and the respiration rate included in the respiration rate calculation time is output from the detected respiration. Then, the coefficient of respiration variation can be calculated from the average value of the respiratory rate and the standard deviation of the respiratory rate included in the variation coefficient calculation section, and the sleep state of the measurement subject can be evaluated from the coefficient of variation. As a result, the sleep state can be evaluated based on the number of breaths included in the variation coefficient calculation section, and when the sleep state is evaluated in a short section (for example, one breath or one minute). It becomes possible to compare with and evaluate appropriately.

Further, according to the sleep evaluation device of the present invention, sleep evaluation can be performed by using the heartbeat (heart rate) as the biological information of the measurement subject. This makes it possible to appropriately evaluate the sleep state by using a simple device that calculates a heartbeat.

It is a figure for explaining 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 a data structure of the respiration rate table in this embodiment. It is a figure which shows an example of a data structure of the variation coefficient table in this embodiment. It is a figure for demonstrating correspondence of a breathing rate and a sleep state. It is a figure which shows the data flow of the area respiration rate output process in this embodiment. It is a figure which shows the data flow of the variation coefficient calculation process in this embodiment. It is a figure which shows the data flow of sleep evaluation processing in this embodiment. It is the figure which showed the plot of the respiratory rate. It is a figure for demonstrating the correlation of a 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 a value output from the detection device 3. It is equipped with. The detection device 3 and the processing device 5 constitute a sleep evaluation device.

When the person to be measured P is present 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 measurement subject P (the respiration rate within a predetermined time) is detected (output). In the present embodiment, the detected respiration (number) is wirelessly transmitted to the processing device 5 (for example, a computer or the like), but is integrally formed by providing the detection device 3 with a display unit or the like. 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 tabread or a smartphone.

Here, the detection device 3 is formed in a sheet shape so as to have a small thickness. As a result, even if it is placed between the bed 10 and the mattress 20, it can be used without causing the person to be measured P to feel uncomfortable.

The detection device 3 only needs to be able to detect the breathing of the measurement subject P. In the present embodiment, the respiration is detected based on the body movement. However, for example, a breathing sound is detected by using a voice sensor, the body movement of the person P to be measured is detected by an infrared sensor, or distortion is detected. An actuator with a gauge may be used.

[2. Functional configuration]
Next, 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 one other than the breath detection unit 200.

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

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

The respiration detection unit 200 in the present embodiment detects, for example, the vibration (body motion) of the measurement subject by the pressure sensor and detects respiration from the vibration, but the position of the center of gravity (body motion) of the measurement subject by the load sensor. The breathing may be detected based on the change of, or a microphone may be provided to detect the breathing based on the sound picked up by the microphone. It suffices if the breathing of the measurement 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 storage unit 300 stores a respiratory rate table 302 and a coefficient of variation table 304, and a respiratory rate output program 310, a coefficient of variation calculation program 312, and a sleep evaluation program 320 as programs. ing.

The breathing rate table 302 is a table in which the breathing rate output based on the breathing detected by the breathing 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 time series. The respiratory rate calculation time in the present embodiment is “1 minute” as an example.

A plurality of breathing rate tables 302 may be stored for each identification information. By using the identification information, for example, it may be stored for each person to be measured, or may be stored separately for each measurement day even for the same person to be measured.

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

Identification information, as described above, for example, by attaching the identification information for each person to be measured, or by attaching the identification information for each measurement day, perform sleep evaluation for each person to be measured, or perform sleep evaluation for each measurement day It becomes possible.

The section information is information for setting a section for calculating the coefficient of variation (hereinafter referred to as “variation coefficient calculation section”). A variation coefficient calculation section is preset in association 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, various settings such as the ratio of the total sleep time (for example, 30% from the start of sleep), comparison in the second half of sleep, and sleep time (for example, 3 am to 5 am) can be performed. is there.

These variation coefficient calculation sections are preset and may be selected by the measurer (user), or the plurality of variation coefficient 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-described variation coefficient calculation section. Specifically, the standard deviation of the respiratory rate in the variation coefficient calculation section is calculated. Also, the average respiratory rate in the variation coefficient calculation section is calculated. The coefficient calculated by dividing the calculated standard deviation by the average respiratory rate is the coefficient of variation.

If the coefficient of variation is small, it is determined that breathing is stable and that the subject is sleeping well. If the coefficient of variation is large, it is determined that the user is in the awake state or the REM sleep state.

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

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

Further, the line graph is a graph showing the result of measuring the sleep stage of the subject by the polysomnography test. As shown on the right, it is expressed in 0 to 4 stages. "0" indicates awakening, "0.5" indicates REM sleep, and "1 to 4" indicates NREM (non-rem) sleep stages 1 to 4. There is. Furthermore, the larger the number, the deeper the sleep.

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

According to FIG. 5A, it can be seen from the graph that the more stable and continuous the sleep is, the deeper 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 the awakening is frequently mixed during 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 that allows the sleep stage to be estimated every minute (every predetermined time). Therefore, the feature of the present embodiment is that sleep is evaluated based on the tendency of the entire sleep or the first half/second half of the sleep for a long time.

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

The display unit 500 is a functional unit that displays a sleep state and an evaluation, and displays the operation of the sleep evaluation system 1. For example, it is configured by a display device such as a liquid crystal display.

[3. Process flow]
Then, the flow of processing of sleep evaluation system 1 in this embodiment is explained.

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

Breathing is detected by the breathing detection unit 200 (step S102). Then, it is determined whether the respiratory rate calculation time has elapsed (step S104). Here, when the respiratory rate calculation time has elapsed (step S104; Yes), the number of breaths detected during 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 breathing rate output process is completed (step S108; No→step S102).

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

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

Then, a 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 variation coefficient calculation section is calculated. Next, the average value of the respiratory rate included in the variation coefficient calculation section is calculated.

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

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

In addition, section information for reading out the coefficient of variation is also determined. For example, the calculated range and target are determined based on the section information such that the extracted coefficient of variation is a coefficient of variation calculated based on “240 minutes” after the start of sleep.

The identification information and the section information may be arbitrarily determined by the measurer or may be determined in advance.

Next, the coefficient of variation is read based on the identification information and the section information (step S304). Here, when a plurality of pieces of identification information or section information are designated, the coefficient of variation corresponding to all pieces of identification information (section information) is read (step S306; Yes→step S304). That is, when there are a plurality of variation coefficients that need to be read, the plurality of variation coefficients 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. As a criterion for this evaluation, for example, an average value of a plurality of subjects, a reference value that is a preset reference, or an average value of the same subject, for evaluating sleep Is the standard value of. For example, the position of the distribution of values of the same age is evaluated by an index such as a deviation value.

[4. Example]
Next, an example using the sleep evaluation system 1 according to 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.

[4.1 First Embodiment]
As a first example, 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". 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. 9A is a plot of respiration rate by the first product, and FIG. 9B is a plot of respiration rate by the second product.

Here, in each graph, the breathing rate indicated by the dotted line is the breathing 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 of FIG. 7) and output to the coefficient of variation table 304 (step S206).

After that, the coefficient of variation between the first product (FIG. 9A) having the identification information “001” and the second product (FIG. 9B) having the identification information “002” is compared. In this case, the coefficient of variation of the first product (FIG. 9A) is lower, and thus the first product is evaluated as having a better sleep state as the sleep evaluation.

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

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

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

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

[4.2 Second Embodiment]
As a second embodiment, an embodiment used when evaluating the physical condition of the person to be measured will be described. In this case, the identification information of the previous day is set to “001”, the identification information of the day is set to “002”, and predetermined section information (for example, the first ⅓ section of sleeping time from getting up to getting up) is set. ..

For example, by comparing the coefficient of variation based on the identification information of the previous day with the coefficient of variation based on the identification information of the day, it is possible to evaluate that the physical condition is not excellent due to the increased coefficient of variation.

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

That is, the content of sleep can be evaluated separately from the length of the awakening time by excluding the period during the awakening time. Therefore, the breathing rate table 302 is also stored with the categories of sleep and awakening (or, as a separate table, the categories of sleep and awakening 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 during the time determined to be the awakening.

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

[4.4 Fourth Embodiment]
The fourth example may be an example in which a sleep evaluation report is output based on the calculated coefficient of variation. That is, a report regarding the sleep evaluation of the person to be measured is output from the coefficient of variation, in comparison with the coefficient of variation from the previous day, and from the average of the coefficient of variation.

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

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

In the above-described embodiment, the respiratory rate is used as an example of the biometric information, but the heart rate may be used as the biometric information of the measurement subject to perform the same evaluation. 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 the heart rate (number) instead of the respiration (number) as the biological information, it is possible to appropriately evaluate sleep by using a conventional device that detects a heart rate, such as an electrocardiograph. There is.

Further, in the above-described embodiment, for convenience of description, the variation coefficient is stored once in the variation coefficient table 304. However, the variation coefficient 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 Respiration Rate Table 304 Variation Coefficient Table 310 Respiration Rate Output Program 312 Variation Coefficient Calculation Program 320 Sleep Evaluation Program 400 Input Unit 500 Display

Claims (4)

Detection means for detecting the breathing or heartbeat of the subject, which can measure the number of times per unit time,
Calculating first information indicating a deviation from the first average of the respiratory rate or heart rate per unit time included in the first section of the previous day , and
Calculating means for calculating second information indicating the second average of the respiratory rate or the heart rate per unit time included in the second section of the day and the deviation from the second average;
Based on the deviation from the first average in the first information and the deviation from the second average in the second information, an evaluation unit that evaluates the sleep state of the measurement subject or the physical condition of the day .
Equipped with
It said first section and said second section are both evaluation device comprising a call is 2 hours or more, or 30% or more of total sleep time of the night. When the deviation from the second average in the second information is larger than the deviation from the first average in the first information, the evaluation means evaluates that the physical condition of the person to be measured on the day is not excellent. The evaluation device according to claim 1 , wherein: Said calculation means, it said in claim 1 or 2 the measurement subject and calculates the first information and the second information respiratory rate or to the exclusion of heart rate time that is determined to awake Evaluation device described. On the computer,
A detection function that detects the breathing or heartbeat of the measurement subject that can measure the number of times per unit time,
Calculating first information indicating a deviation from the first average of the respiratory rate or heart rate per unit time included in the first section of the previous day , and
A calculation function of calculating second information indicating the second average of the respiratory rate or the heart rate per unit time included in the second section of the day and the deviation from the second average;
Based on the deviation from the first average in the first information and the deviation from the second average in the second information, an evaluation function of evaluating the sleep state of the measurement subject or the physical condition of the day .
Is realized ,
The first section and the second section, program characterized and this is any more than 30% of the total 2 hours or more, or sleep time of overnight.

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