JP2019136527A - Sleep evaluation device and sleep evaluation program - Google Patents

Abstract

To provide a sleep evaluation device, etc. capable of simply and correctly evaluating a sleeping state by using, for example, a respiratory rate or a heart rate as biological information of a subject within a predetermined period of time.SOLUTION: The sleep evaluation device detects respiration of a subject, and outputs respiratory rates contained in a respiratory rate calculation time from the detected respiration. The sleep evaluation device then calculates respiratory rate variation coefficients from an average value of respiratory rates contained in a predetermined calculation section and a standard deviation of the respiratory rates, and evaluates sleeping states of the subjects from the variation coefficients.SELECTED DRAWING: Figure 1

Description

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

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

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

Japanese Patent No. 4582642 Japanese Patent No. 3733133

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

  In addition, depending on the mounting position of the wearable sensor and the relative positional relationship between the human body and the sensor such as the sleeping position of the non-wearable sensor, the respiratory waveform changes separately from the factors inherent to the human body. When using a lot of measurement information, if all 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 There is a problem that the accuracy of the final evaluation result is lowered.

  In view of the above-described problems, the present invention aims to easily and accurately evaluate sleep by using, for example, a respiration rate or a heart rate as biological information within a predetermined time of the measurement subject. It is providing the sleep evaluation apparatus etc. which can be.

In order to solve the above-described problem, the sleep evaluation apparatus of the present invention
A detecting means for detecting a breath or heartbeat of a measurement person capable of measuring 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 first day and the first average;
A calculating means for calculating second information indicating a deviation from the second average and the second average of the respiratory rate or heart rate per unit time included in the second interval 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 providing.

The sleep evaluation program of the present invention
On the computer,
A detection function for detecting the respiration or heartbeat of the measurement subject capable of measuring 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 first day and the first average;
A calculation function for calculating second information indicating a deviation from the second average and the second average of the respiratory rate or heart rate per unit time included in the second interval 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 apparatus 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 of the respiration rate can be calculated from the average value of the respiration rate included in the coefficient of variation calculation section and the standard deviation of the respiration rate, and the sleep state of the measurement subject can be evaluated from the coefficient of variation. Thereby, the sleep state can be evaluated based on the respiration (number) 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 breath). It becomes possible to evaluate appropriately.

  Moreover, according to the sleep evaluation apparatus of this invention, sleep evaluation can be performed using a heart rate (heart rate) as biometric information of a to-be-measured person. Thereby, it becomes possible to evaluate a sleep state appropriately by using a simple device for calculating a heart rate.

It is a figure for demonstrating the whole in this embodiment. It is a figure for demonstrating the function structure in this embodiment. It is a figure which shows an example of the 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 the response | compatibility with a respiratory rate and a sleep state. It is a figure which shows the data flow of the section 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 the sleep evaluation process in this embodiment. It is the figure which showed the plot of the respiration rate. It is a figure for demonstrating the correlation of a respiration rate.

The best mode for carrying out the present invention will be described below with reference to the drawings.
[1. System appearance]
FIG. 1 is a diagram for explaining a method of using 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 prepared for. The detection device 3 and the processing device 5 constitute a sleep evaluation device.

  When the subject P is present on the mattress 20, the detection device 3 detects the body movement (vibration) of the subject P via the mattress 20. Based on the detected vibration, the respiration (respiration rate within a predetermined time) of the measurement subject P is detected (output). In the present embodiment, the detected respiration (number) is transmitted wirelessly to the processing device 5 (for example, a computer). For example, the detection device 3 is integrally formed by providing a display unit or the like. Also good. Moreover, since the processing apparatus 5 may be a general-purpose apparatus, the processing apparatus 5 is not limited to an information processing apparatus such as a computer, and may be configured by an apparatus such as a tab red or a smartphone.

  Here, the detection device 3 is configured in a sheet shape so as to be thin. Thereby, even if it is placed between the bed 10 and the mattress 20, it can be used without making the person to be measured P feel uncomfortable.

  In addition, the detection apparatus 3 should just be able to detect the to-be-measured person's P respiration. In the present embodiment, respiration is detected based on body movement. However, for example, a breathing sound is detected using an audio sensor, a body movement of the measurement subject P is detected using an infrared sensor, or the like. An actuator with a gauge may be used.

[2. Functional configuration]
Then, the mechanism structure of the sleep evaluation system 1 is demonstrated using FIG. The sleep evaluation system 1 in the present embodiment has a configuration including the detection device 3 and the processing device 5, and each functional unit (processing) may be realized by any means other than the respiratory detection unit 200.

  In the sleep evaluation system 1, a respiration detection unit 200, a storage unit 300, and an 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 configured by a control circuit necessary for the sleep evaluation system 1, such as a CPU. The control unit 100 implements 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 measurement subject. In the present embodiment, it is a sensor unit for detecting vibration. The respiration 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 breathing of the measurement subject P such as turning over and heartbeat.

  The respiration detection unit 200 according to the present embodiment detects, for example, the vibration (body movement) of the person to be measured using a pressure sensor and detects respiration from the vibration, but the gravity center position (body movement) of the person to be measured using a load sensor. It is good also as detecting respiration by the change of, and you may detect based on the sound which a microphone picks up by providing a microphone. It suffices if the respiration of the measurement subject can be detected using any sensor.

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

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

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

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

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

  As described above, the identification information includes, for example, identification information for each person to be measured, or identification information for each measurement day, thereby performing sleep evaluation for each person to be measured or performing sleep evaluation for each measurement day. It becomes possible to do.

  The section information is information for setting a section for calculating a variation coefficient (hereinafter referred to as “variation coefficient calculation section”). A coefficient of variation calculation section is set in advance in association with the section information. For example, as the section information “a01”, the first half of the sleep time, that is, 240 minutes from the start of sleep can be set. 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 second half of sleep, and the sleep time (for example, 3 am to 5 am). is there.

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

  The variation coefficient is a coefficient calculated from the respiration 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. Moreover, the average respiration rate of the variation coefficient calculation section is calculated. By dividing the calculated standard deviation by the average respiration rate, the calculated coefficient is the variation coefficient.

  Here, when the coefficient of variation is small, it is determined that breathing is stable and sleep well. Moreover, when a variation coefficient is large, it determines with it being an arousal state or a REM sleep state.

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

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

  Moreover, a line graph is a graph which shows the result of having measured the sleep stage of a to-be-measured person by polysomnography inspection. As shown to the right, it is expressed in stages 0 to 4, where “0” indicates arousal, “0.5” indicates REM sleep, and “1-4” indicates NREM (non-REM) sleep stages 1-4. Yes. Furthermore, the larger the number, the deeper the sleep.

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

  According to Fig.5 (a), it can read from a graph that the fluctuation | variation of a respiration rate is so small that sleep is stabilized and it becomes deep. On the other hand, according to FIG.5 (b), when arousal frequently mixes in the middle of sleep and it is not stable, it can read that the fluctuation | variation of a respiration rate is large.

  Thus, although it turned out that a sleep stage and a respiration rate have a fixed relationship, there is no clear relationship which can estimate a sleep step for every minute (every predetermined time). Therefore, it is a feature of this embodiment that sleep is evaluated with a long-term tendency such as the whole sleep or the first half and the second half.

  The input unit 400 is a functional unit for the measurer to instruct and operate the sleep evaluation system 1. For example, it is configured by operation buttons, a touch panel, a voice input device, and the like.

  The display unit 500 is a functional unit for displaying the sleep state and evaluation, and displaying 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 a process of the sleep evaluation system 1 in this embodiment is demonstrated.

[3.1 Respiration rate output processing]
The respiration rate output process will be described with reference to FIG. The respiration rate output process is a process realized by reading the respiration rate output program 310 in FIG.

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

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

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

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

  Then, the coefficient of variation is calculated by dividing the calculated standard deviation by the calculated average value. The calculated variation coefficient is attached with identification information as a target and information indicating a 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 process]
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 identification information, “001” to “003” are used, or a target of identification information for evaluating sleep is determined.

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

  The determination of 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 identification information or section information is designated, variation coefficients corresponding to all the identification information (section information) are read (step S306; Yes → step S304). That is, when there are a plurality of variation coefficients that need to be read out, a plurality of variation coefficients are read out.

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

  Specifically, when the variation coefficient is smaller than a predetermined value, it is evaluated that the sleep state is good, and when the variation coefficient is larger than the predetermined value, it is evaluated that the sleep state is bad. In order to evaluate sleep, for example, an average value of a plurality of measured persons, a reference value serving as a preset reference, or an average value of the same measured person may be used as the reference for evaluation. Is the reference value. For example, the position of the same age value distribution is evaluated by an index such as a deviation value.

[4. Example]
Then, the Example using the sleep evaluation system 1 in this embodiment is described. In the present embodiment, as shown in FIG. 1, a device for detecting respiration is placed under the measurement subject, and the respiration is detected from the body movement of the measurement subject.

[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”. As section information, 240 minutes from the start of sleep is set as section information “a01”, and a variation coefficient is calculated.

  FIG. 9 shows a state in which the respiratory rate is plotted. FIG. 9A is a plot of the respiration rate by the first product, and FIG. 9B is a plot of the respiration rate by the second product.

  Here, in each graph, the respiratory rate in the dotted line portion is the respiratory rate included in the section information “a01”. Therefore, first, the coefficient of variation of the respiration 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).

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

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

  In addition, the evaluation for every product can be performed by measuring the above-mentioned variation coefficient by two or more persons. For example, when the first product and the second product are compared, if many people have a smaller coefficient of variation in the second product, the second product can be evaluated as a comfortable bedding.

  Further, FIG. 10 shows an example of actual data when two products are evaluated. FIG. 10 shows data showing the coefficient of variation of 10 persons to be measured 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.

  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, B product can be evaluated as a mattress that provides better sleep.

[4.2 Second Embodiment]
As a second embodiment, an embodiment used when evaluating the physical condition of the measurement subject 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 1/3 section from bedtime to getting up in the sleeping time) is set. .

  For example, the coefficient of variation based on the previous day's identification information is compared with the coefficient of variation based on the current day's identification information, and it is possible to evaluate that the physical condition is not excellent due to the increased coefficient of variation.

[4.3 Third Example]
As a third embodiment, a case will be described in which fluctuation information is calculated except for awakening time.

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

  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 awakening.

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

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

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

[5. Modified example]
The embodiment of the present invention has been described in detail with reference to the drawings. However, the specific configuration is not limited to this embodiment, and the design and the like within the scope of the present invention are also within the scope of the claims. include.

  In the above-described embodiment, the respiratory rate is used as an example of the biological information. However, the heart rate may be used as the biological information of the person to be measured, and the evaluation may be similarly performed. That is, by using the detected respiration as a heart rate and the respiration rate as a heart rate, a similar sleep evaluation can be performed.

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

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

DESCRIPTION OF SYMBOLS 1 Sleep evaluation system 3 Detection apparatus 5 Processing apparatus 10 Bed 20 Mattress 100 Control part 200 Respiration detection part 300 Storage part 302 Respiration rate table 304 Change coefficient table 310 Respiration rate output program 312 Change coefficient calculation program 320 Sleep evaluation program 400 Input part 500 Display section

Claims (5)

A detecting means for detecting a breath or heartbeat of a measurement person capable of measuring 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 first day and the first average;
A calculating means for calculating second information indicating a deviation from the second average and the second average of the respiratory rate or heart rate per unit time included in the second interval 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;
A sleep evaluation apparatus comprising:   2. The sleep evaluation apparatus according to claim 1, wherein each of the first section and the second section is two hours or more in an overnight or 30% or more of the entire sleep time.   When the deviation from the first average in the second information is larger than the deviation from the second average in the first information, the evaluation means is that the physical condition of the measurement subject on the second day is not excellent. The sleep evaluation apparatus according to claim 1, wherein the sleep evaluation apparatus is evaluated.   4. The sleep evaluation according to claim 1, wherein the calculation unit calculates the first information by excluding the biological information of the time when the measurement subject is determined to be awake. 5. apparatus. On the computer,
A detection function for detecting the respiration or heartbeat of the measurement subject capable of measuring 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 first day and the first average;
A calculation function for calculating second information indicating a deviation from the second average and the second average of the respiratory rate or heart rate per unit time included in the second interval 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;
A program characterized by realizing.

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