Resting heart rate calculator, resting heart rate calculator, program, and recording medium

Abstract

To provide a more accurate resting heart rate regardless of an action time of a subject.SOLUTION: A resting heart rate calculation device includes a heart rate calculation unit for calculating a heart rate from electrocardiographic data measured by an electrocardiograph, and a resting heart rate calculation unit for calculating a heart rate at a given quantile as the resting heart rate, among heart rates recorded for 24 hours or longer.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present invention relates to a resting heart rate calculation device, a resting heart rate calculation method, a program, and a recording medium.

Background Art

[0002] In aerobic exercise, exercise intensity is one of the indicators indicating how much load the exercise is imposing on the individual's physical ability. Exercise intensity is generally calculated from measured values of oxygen uptake or heart rate, and is widely used because it is easier to calculate from the measured value of heart rate.

[0003] There is a method called the Karvonen method for calculating exercise intensity from heart rate, which is widely used in the fields of medicine and exercise physiology. In the Karvonen method, exercise intensity is calculated by the following formula (see Non-Patent Document 1). Exercise intensity = (Heart rate - Resting heart rate) ÷ (Maximum heart rate - Resting heart rate) × 100 The unit of exercise intensity is %, and the minimum value is 0 and the maximum value is 100.

[0004] The resting heart rate is the heart rate measured in a situation where the body is kept still without movement. However, there is no definitive definition regarding what posture or situation is considered to be at rest. In clinical settings, the heart rate measured after sitting on a chair for about 10 minutes and resting the body is often used as the resting heart rate, but there is a report showing that using the median value of the heart rate measured in the supine position at night (during the period from 0:00 am to 5:00 am) as the resting heart rate correlates better with the actual metabolic rate than the heart rate measured by this method (see Non-Patent Document 2).

[0005] As a technique for simply calculating the resting heart rate from the heart rate during the supine position at night, a technique has been proposed in which a sensor is worn by the user and information on the user's electrocardiogram is detected from the sensor (see Non-Patent Document 3).

Prior Art Documents

Patent Documents

[0006] [Patent Document 1] International Publication No. 2020 / 004102 [Patent Document 2] Japanese Unexamined Patent Application Publication No. 2020 - 036781 [Non - Patent Document]

[0007] [Non - Patent Document 1] "Exercise Intensity", [online], [searched on April 18, 2022], Internet <URL: https: / / ja.wikipedia.org / wiki / 運動強度> [Non - Patent Document 2] Validity of simplified, calibration - less exercise intensity measurement using resting heart rate during sleep: A method - comparison study with respiratory gas analysis. Hirotaka Matsuura, Masahiko Mukaino, Yohei Otaka, Hitoshi Kagaya, Yasushi Aoshima, Takuya Suzuki, Ayaka Inukai, Emi Hattori, Takayuki Ogasawara, Eiichi Saitoh. BMC Sports Science, Medicine and Rehabilitation 11(1) November 4, 2019 [Non - Patent Document 3] Takayuki Ogasawara, Masahiko Mukaino, "Section 8 Wearable electrode material hitoe and its application to rehabilitation - From case studies of empirical experiments in a recovery - phase rehabilitation ward ~", Technical Information Association, July 2020 [Non - Patent Document 4] NTT Technical Journal, Research and Development Efforts towards the Advancement of IoT, Efforts in Rehabilitation Support Applying Wearable Material hitoe, July 2018 [Overview of the Initiative] [Problems that the invention aims to solve]

[0008] The method described in Non-Patent Document 2 calculates resting heart rate from the resting heart rate while lying down at night. This method assumes that the heart rate at night is lower than the heart rate during the day, and for subjects who are active at night, the exercise intensity calculated by the Karvonen method becomes a negative value, making it impossible to calculate correctly.

[0009] The objective of this invention is to provide a more accurate resting heart rate regardless of the subject's activity level. [Means for solving the problem]

[0010] One aspect of the present invention is a resting heart rate calculation device comprising: a heart rate calculation unit that calculates heart rate from electrocardiogram data measured by an electrocardiograph; and a resting heart rate calculation unit that calculates the resting heart rate as the heart rate corresponding to a predetermined quantile from the heart rates recorded for 24 hours or more.

[0011] One aspect of the present invention is a resting heart rate calculation method comprising: a heart rate calculation step of calculating the heart rate from electrocardiogram data measured by an electrocardiograph; and a resting heart rate calculation step of calculating the resting heart rate as the heart rate corresponding to a predetermined quantile from the heart rates recorded for 24 hours or more.

[0012] One aspect of the present invention is a program that causes a computer to calculate heart rate from electrocardiogram data measured by an electrocardiograph, and to calculate the resting heart rate as the heart rate at a predetermined quantile from the heart rates recorded for 24 hours or more.

[0013] One aspect of the present invention is a recording medium on which a program is recorded that causes a computer to calculate heart rate from electrocardiogram data measured by an electrocardiograph, and to calculate the resting heart rate as the heart rate corresponding to a predetermined quantile among the heart rates recorded for 24 hours or more. [Effects of the Invention]

[0014] According to the present invention, regardless of the activity time of the subject, a more accurate resting heart rate can be provided.

Brief Description of the Drawings

[0015] [Figure 1] It is a diagram showing a resting heart rate calculation system 1 according to the first embodiment. [Figure 2] It is a diagram showing an example of the configuration of a resting heart rate calculation device 2 according to the first embodiment. [Figure 3] It is a histogram based on the heart rates calculated from a plurality of subjects. [Figure 4] It is a diagram showing the difference between the nighttime heart rate calculated by the method described in Non-Patent Document 2 (hereinafter, the conventional method) and the quantile of the heart rate measured for 24 hours from the subject. [Figure 5] It is a diagram showing the relationship between the resting heart rate calculated by the conventional method and the resting heart rate calculated by the method of the first embodiment. [Figure 6] It is a flowchart showing the operation of a resting heart rate calculation device 2 according to the first embodiment. [Figure 7] It is a diagram showing an example of the configuration of a resting heart rate calculation device 2 according to the second embodiment. [Figure 8] It is a diagram showing the relationship between the exercise intensity calculated by the conventional method and the exercise intensity calculated by the method of the second embodiment. [Figure 9] It is a flowchart showing the operation of a resting heart rate calculation device 2 according to the second embodiment. [Figure 10] It is a diagram showing an example of the configuration of a resting heart rate calculation device 2 according to the third embodiment. [Figure 11] It is a flowchart showing the operation of a resting heart rate calculation device 2 according to the third embodiment. [Figure 12] It is a diagram showing an example of the configuration of a resting heart rate calculation device 2 according to the fourth embodiment. [Figure 13] It is a diagram showing an example of the configuration of a resting heart rate calculation device 2 according to the fifth embodiment. [Figure 14] This figure shows an example of the configuration of the resting heart rate calculation device 2 according to the sixth embodiment. [Figure 15] This figure shows the average exercise intensity for each subject when the posture is supine. [Figure 16] This figure shows the average exercise intensity for each subject when they are standing or sitting. [Figure 17] This figure shows the average exercise intensity for each subject when the posture is walking. [Figure 18] This is a histogram created for each average motor FIM score. [Figure 19] This is a histogram created for each average motor FIM score. [Modes for carrying out the invention]

[0016] (First Embodiment) Embodiments of the present invention will now be described in detail with reference to the drawings. In the following description of embodiments, the second and subsequent embodiments will be described as embodiments in which components have been added to the first embodiment, but the components added to the second and subsequent embodiments may be added to any embodiment. For example, the components added to the second embodiment may also be added to the third and subsequent embodiments.

[0017] Figure 1 shows a resting heart rate calculation system 1 according to a first embodiment. The resting heart rate calculation system 1 includes a resting heart rate calculation device 2, a sensor terminal 202, and a relay terminal 203. In the resting heart rate calculation system 1, for example, the sensor terminal 202 is attached to the torso of a subject 201. The results measured by the sensor terminal 202 are relayed by the relay terminal 203 and transmitted to the resting heart rate calculation device 2. The sensor terminal 202 measures the electrical signals generated from the myocardium of the subject 201. In other words, the sensor terminal 202 is an electrocardiograph. The sensor terminal 202 may be a computer device such as a smartphone or tablet.

[0018] The relay terminal 203 transmits the data received from the sensor terminal 202 to the resting heart rate calculation device 2. The relay terminal 203 is connected to the sensor terminal 202 by Bluetooth® and to the resting heart rate calculation device 2 by Wi-Fi, but is not limited to these connections. The relay terminal 203 may be a computer device such as a smartphone or tablet that processes the data received from the sensor terminal 202 and transmits it to the resting heart rate calculation device 2. For example, the relay terminal 203 may generate an electrocardiogram for a predetermined period based on the received electrical signal data and transmit it to the resting heart rate calculation device 2.

[0019] Figure 2 shows an example of the configuration of the resting heart rate calculation device 2 according to the first embodiment. The resting heart rate calculation device 2 according to the first embodiment includes a data receiving unit 200, a heart rate calculation unit 210, a resting heart rate calculation unit 220, an output unit 230, and a storage unit 300.

[0020] The data receiving unit 200 receives data from the relay terminal 203. The heart rate calculation unit 210 calculates the heart rate based on the data received by the data receiving unit 200. The heart rate calculation unit 210 calculates the heart rate by calculating the interval between R waves (heart rate interval: RRI) in the received electrocardiogram. The heart rate calculation unit 210 may also generate an electrocardiogram based on the electrical signal data received by the data receiving unit 200 and calculate the heart rate. The heart rate calculation unit 210 calculates the heart rate at predetermined time intervals. For example, the heart rate calculation unit 210 calculates the heart rate every minute. The heart rate calculation unit 210 records the calculated heart rate in the storage unit 300. The storage unit 300 records the heart rate at predetermined time intervals. The heart rate recorded in the storage unit 300 is recorded by the heart rate calculation unit 210 for at least 24 hours.

[0021] The resting heart rate calculation unit 220 calculates the resting heart rate from the heart rate data stored in the memory unit 300 at predetermined intervals. The resting heart rate calculation unit 220 calculates the resting heart rate as the heart rate corresponding to an arbitrary quantile among the heart rates stored in the memory unit 300. For example, the quantile is the point corresponding to the 20th to 30th percentile. The output unit 230 outputs the calculated resting heart rate. The output resting heart rate is input to a display device, for example, and the value is displayed.

[0022] Figure 3 is a histogram based on heart rate data calculated from multiple subjects. The method for creating this histogram is as follows: First, heart rate data was collected from the subjects. In this experiment, heart rate data was obtained from 2041 subjects, calculated every minute for 24 hours. In other words, there were 1440 heart rate data points calculated for each subject, and a total of 2,939,040 heart rate data points calculated from all subjects combined. The calculated heart rates are integer values.

[0023] Subsequently, using heart rate data calculated from all subjects, data corresponding to the 0th to 100th percentile was calculated in 1st percentile increments. Then, the number of data points that fall between the 0th and 1st percentile values ​​was calculated, and the number of data points that fall between the 1st and 2nd percentile values ​​was calculated, and this was repeated in 1st percentile increments up to the number of data points that fall between the 99th and 100th percentile values. At this point, it is possible that some data points may be calculated multiple times. For example, if the value of the data point corresponding to the 1st percentile is the same as the value of the data point corresponding to the 2nd percentile, the data point corresponding to the 1st percentile is included in the number of data points that fall between the 0th and 1st percentile values, and also in the number of data points that fall between the 1st and 2nd percentile values.

[0024] Using this method, the number of data points was calculated in 1st percentile increments, and then the number of data points was added up for every 5th percentile. In Figure 3, 0-5% represents the sum of five numbers: the number of data points between the 0th and 1st percentile, the number of data points between the 1st and 2nd percentile, the number of data points between the 2nd and 3rd percentile, the number of data points between the 3rd and 4th percentile, and the number of data points between the 4th and 5th percentile. The numbers shown in the graph from 5-10% to 95%-100% were calculated using the same method. Since there are data points for which the number is calculated multiple times, the values ​​shown in the graph will be different for each category.

[0025] The histogram shown in Figure 3 shows peaks at 20-25% and 65-70%. The peak at 20-25% is thought to be due to the heart rate when the subject is lying down or sleeping, while the peak at 65-70% is thought to be due to the heart rate when the subject is active, such as sitting, standing, or walking. Since the peak at 20-25% is due to the heart rate when the subject is lying down or sleeping, it is desirable to calculate the resting heart rate at the 20th-25th percentile. Alternatively, since the values ​​at 25-30% are also high, similar to the peak at 20-25%, the resting heart rate may be arbitrarily calculated at the 25th-30th percentile, taking into account individual differences among subjects. In this way, by statistically processing heart rate, the resting heart rate can be calculated without needing information on posture or time of measurement.

[0026] Figure 4 shows the difference between the nocturnal heart rate calculated by the method described in Non-Patent Document 2 (hereinafter referred to as the conventional method) and the quantiles of the heart rate measured from subjects over a 24-hour period. The number of subjects is 2041, the same as described above. The bar graph shows the mean of the difference, and the error bars show the standard deviation of the difference. In Figure 4, the difference is smallest at the 25th percentile. Therefore, it can be said that the heart rate at the 25th percentile has the same reliability as the nocturnal heart rate.

[0027] Figure 5 shows the relationship between the resting heart rate calculated by the conventional method and the resting heart rate calculated by the method of the first embodiment. Points within the circled area indicate that the resting heart rate calculated by the conventional method is 120 bpm or higher, which is too high a value for a resting heart rate. However, the resting heart rate calculated by the method of the first embodiment, excluding the points within the circled area, is close to the resting heart rate calculated by the conventional method. Therefore, the method of the first embodiment can calculate a high-quality resting heart rate.

[0028] Figure 6 is a flowchart showing the operation of the resting heart rate calculation device 2 according to the first embodiment. The data receiving unit 200 receives data from the relay terminal 203 (step S11). The heart rate calculation unit 210 calculates the heart rate based on the data (step S12) and records the heart rate (step S13). The resting heart rate calculation unit 220 calculates the resting heart rate based on the recorded heart rate (step S14). The output unit 230 outputs the calculated resting heart rate (step S15).

[0029] (Second embodiment) Figure 7 shows an example of the configuration of the resting heart rate calculation device 2 according to the second embodiment. The resting heart rate calculation device 2 according to the second embodiment includes an exercise intensity calculation unit 240 in addition to the resting heart rate calculation device 2 according to the first embodiment.

[0030] The exercise intensity calculation unit 240 calculates exercise intensity based on the resting heart rate. The exercise intensity calculation unit 240 calculates exercise intensity using, for example, the following formula. Exercise intensity = (Heart rate - Resting heart rate) ÷ (Maximum heart rate - Resting heart rate) × 100 Here, the heart rate is any heart rate stored in the memory unit 300. The maximum heart rate is calculated, for example, from the age of the subject as described in Non-Patent Literature 2.

[0031] Figure 8 shows the relationship between exercise intensity calculated by the conventional method and exercise intensity calculated by the method of the second embodiment. Each point corresponds to each subject. The exercise intensity shown by each point is calculated from heart rate recorded over 24 hours. Exercise intensity is usually in the range of 0 to 100, but the exercise intensity calculated by the conventional method may take negative values. The exercise intensity calculated by the method of the second embodiment does not take negative values. Therefore, it is possible to calculate a higher quality exercise intensity.

[0032] In the second embodiment, the output unit 230 may output the calculated exercise intensity.

[0033] Figure 9 is a flowchart showing the operation of the resting heart rate calculation device 2 according to the second embodiment. The data receiving unit 200 receives data from the relay terminal 203 (step S21). The heart rate calculation unit 210 calculates the heart rate based on the data (step S22) and records the heart rate (step S23). The resting heart rate calculation unit 220 calculates the resting heart rate based on the recorded heart rate (step S24). The exercise intensity calculation unit 240 calculates the exercise intensity based on the resting heart rate (step S25). The output unit 230 outputs the calculated exercise intensity (step S26).

[0034] (Third embodiment) Figure 10 shows an example of the configuration of the resting heart rate calculation device 2 according to the third embodiment. The resting heart rate calculation device 2 according to the third embodiment includes a measurement period determination unit 250 in addition to the resting heart rate calculation device 2 according to the first embodiment.

[0035] The measurement period determination unit 250 determines whether the number of heart rate data recorded in the storage unit 300 exceeds a certain number. For example, the measurement period determination unit 250 determines whether the number of heart rate data exceeds the number of data recorded for 90% of 24 hours (i.e., if the heart rate is recorded every minute, 24 × 60 × 0.9 = 1296 data points).

[0036] In the third embodiment, the resting heart rate calculation unit 220 calculates the resting heart rate when the measurement period determination unit 250 determines that the number of heart rate data points exceeds a certain limit. In the third embodiment, the resting heart rate calculation unit 220 does not calculate the resting heart rate when the measurement period determination unit 250 determines that the number of heart rate data points is below a certain limit. This prevents the calculation of the resting heart rate when the number of heart rate data points is small and the resting heart rate cannot be accurately calculated.

[0037] Figure 11 is a flowchart showing the operation of the resting heart rate calculation device 2 according to the third embodiment. The data receiving unit 200 receives data from the relay terminal 203 (step S31). The heart rate calculation unit 210 calculates the heart rate based on the data (step S32) and records the heart rate (step S33). The measurement period determination unit 250 determines whether the number of heart rate data points exceeds a certain number (step S34). If the number of heart rate data points exceeds a certain number (step S35: YES), the resting heart rate calculation unit 220 calculates the resting heart rate based on the recorded heart rate (step S36), and the output unit 230 outputs the calculated resting heart rate (step S37). If the number of heart rate data points is less than or equal to a certain number (step S35: NO), the operation ends.

[0038] (Fourth embodiment) Figure 12 shows an example of the configuration of the resting heart rate calculation device 2 according to the fourth embodiment. The resting heart rate calculation device 2 according to the fourth embodiment includes an ensemble averaging processing unit 260 in addition to the resting heart rate calculation device 2 according to the first embodiment.

[0039] The ensemble averaging processing unit 260 calculates the ensemble average of heart rates corresponding to the same time if the storage unit 300 has recorded heart rates for 24 hours or more. The resting heart rate calculation unit 220 according to the fourth embodiment calculates the resting heart rate using the ensemble average of heart rates as the heart rate.

[0040] (Fifth embodiment) Figure 13 shows an example of the configuration of the resting heart rate calculation device 2 according to the fifth embodiment. The resting heart rate calculation device 2 according to the fifth embodiment includes a lifestyle regularity evaluation unit 270 in addition to the resting heart rate calculation device 2 according to the first embodiment.

[0041] The lifestyle regularity evaluation unit 270 evaluates the lifestyle regularity of the subject 201 based on the heart rate and resting heart rate recorded in the memory unit 300. For example, the lifestyle regularity evaluation unit 270 evaluates the degree of lifestyle regularity by calculating the number of heart rates recorded during a specific period that are smaller than the resting heart rate.

[0042] A specific period is, for example, nighttime. The lifestyle regularity evaluation unit 270 calculates, for example, the percentage of nighttime heart rates that are higher than the resting heart rate, and uses this as the lifestyle irregularity score. For example, if 60 out of 300 heartbeats per minute from midnight to 5 AM are higher than the resting heart rate, the lifestyle irregularity score would be 60 ÷ 300 = 20%. The lifestyle irregularity score can be used to identify subjects who are active at night and to evaluate the degree of circadian rhythm deviation, such as how active a subject is at night. Furthermore, since the resting heart rate is usually close to the nighttime heart rate, the time when the heart rate is below the resting heart rate can be estimated as time spent active, and this can be used to evaluate the quality of sleep, such as whether or not a subject is sleeping at night.

[0043] The lifestyle regularity evaluation unit 270 may calculate the degree of lifestyle irregularity based on daily heart rate data. The lifestyle regularity evaluation unit 270 may count the days on which the degree of lifestyle irregularity exceeds a predetermined value. The lifestyle regularity evaluation unit 270 may be provided in the resting heart rate calculation device 2 according to the second embodiment and may calculate the degree of lifestyle irregularity based on exercise intensity. For example, the lifestyle regularity evaluation unit 270 may determine the degree of lifestyle irregularity by calculating the percentage of negative values ​​for exercise intensity during a specific period. The lifestyle regularity evaluation unit 270 may calculate the period on which the exercise intensity exceeds a predetermined value as the activity period. The activity period can be used to evaluate the activity level of the subject.

[0044] (Sixth embodiment) Figure 14 shows an example of the configuration of the resting heart rate calculation device 2 according to the sixth embodiment. The resting heart rate calculation device 2 according to the sixth embodiment includes a state estimation unit 280 and an exercise intensity classification unit 290 in addition to the resting heart rate calculation device 2 according to the second embodiment. The data receiving unit 200 according to the sixth embodiment acquires acceleration data or angular velocity data of the subject 201. The data receiving unit 200 acquires acceleration data or angular velocity data of the subject 201 from, for example, an accelerometer or gyro sensor attached to the subject 201. The acceleration data may be received via the relay terminal 203, similar to the data received from the sensor terminal 202.

[0045] The state estimation unit 280 estimates the posture of the subject 201 based on the subject 201's heart rate and acceleration or angular velocity. The estimated postures are, for example, lying down, standing, sitting, and walking. The state estimation unit 280 also estimates the posture of the subject 201 based on the tilt of the subject 201's upper body, as described in, for example, Non-Patent Document 3.

[0046] The exercise intensity classification unit 290 classifies the exercise intensity calculated by the exercise intensity calculation unit 240 according to the estimated posture.

[0047] Figures 15 to 17 show the average exercise intensity for each subject, categorized by posture. Figure 15 shows the average exercise intensity for each subject when the posture is supine. Figure 16 shows the average exercise intensity for each subject when the posture is standing or sitting. Figure 17 shows the average exercise intensity for each subject when the posture is walking. For comparison, the results of classifying the exercise intensity calculated by the conventional method and the exercise intensity calculated by the sixth embodiment by posture are shown.

[0048] In all postures, the conventional method detected abnormal values ​​where the exercise intensity was less than -100%. However, in the method of the sixth embodiment, negative values ​​were not detected for exercise intensity when the posture was standing, sitting, or walking, and when the posture was lying down, the minimum value of the exercise intensity was approximately -15%, indicating improved accuracy.

[0049] (Seventh Embodiment) The resting heart rate calculation device 2 according to the seventh embodiment includes, in addition to the resting heart rate calculation device 2 according to the first embodiment, a measurement period determination unit 250 according to the third embodiment and a state estimation unit 280 according to the sixth embodiment, and a data receiving unit 200 acquires acceleration data or angular velocity data of the subject 201. In the seventh embodiment, even if the number of heart rate data recorded in the storage unit 300 does not exceed a certain number, the measurement period determination unit 250 may determine that the number of heart rate data has exceeded a certain number if the posture has been supine for a certain period or longer during a predetermined period (for example, at night) and heart rate data for that certain period has been recorded in the storage unit 300. In this case, the resting heart rate calculation unit 220 calculates the average value of the heart rate during the certain period in which the posture is supine as the resting heart rate. This makes it possible to calculate the resting heart rate even when the heart rate measurement time is short.

[0050] (Eighth embodiment) The resting heart rate calculation device 2 according to the eighth embodiment includes an index calculation unit 292 in addition to the resting heart rate calculation device 2 according to the seventh embodiment. The index calculation unit 292 calculates an index by the method disclosed in Patent Document 1. The calculated index is, for example, the value obtained by dividing the exercise intensity calculated by the exercise intensity calculation unit 240 by the activity level. The activity level is, for example, a value calculated as the norm of the subject's acceleration.

[0051] (Ninth embodiment) The resting heart rate calculation device 2 according to the ninth embodiment is an embodiment of the resting heart rate calculation device 2 in which the memory unit 300 stores the subject's rank information. The rank information includes, for example, the subject's Functional Independence Measure, SIAS (Stroke Impairment Assessment Set), age, and gender. The resting heart rate calculation unit 220 according to the ninth embodiment calculates the resting heart rate based on the subject's heart rate at predetermined time intervals and rank information stored in the memory unit 300, and the heart rate corresponding to the quantile determined by the rank information.

[0052] The method for determining quantiles based on rank information is described below. Figures 18 and 19 are histograms created for each average exercise FIM score. Heart rate data was collected from 22 subjects with an average exercise FIM score of 1, 71 subjects with an average exercise FIM score of 2, 84 subjects with an average exercise FIM score of 3, 75 subjects with an average exercise FIM score of 4, 94 subjects with an average exercise FIM score of 5, 154 subjects with an average exercise FIM score of 6, and 166 subjects with an average exercise FIM score of 7. The collected heart rate data was the same as described in the first embodiment, and heart rate data calculated every minute for 24 hours was obtained.

[0053] Subsequently, histograms were created for each subject with the same average motor FIM score. The method for creating the histograms was the same as described in the first embodiment. In the created histograms, a peak was observed at 26-30% when the motor FIM score was 3 or less. Also, a peak was observed at 21-25% when the motor FIM score was 4 or higher. In other words, the peak in the histogram differs depending on the motor FIM value. Based on these results, the resting heart rate calculation unit 220 calculates the resting heart rate as a value in the 26th-30th percentile range if the exercise FIM is 3 or less, and as a resting heart rate as a value in the 21st-25th percentile range if the exercise FIM is 4 or more.

[0054] As a result, the resting heart rate calculation device 2 according to the ninth embodiment can calculate a resting heart rate that is more appropriate to the individual subject's condition. Although a method for creating different histograms based on exercise FIM has been described, the method is not limited to this. For example, the resting heart rate calculation device 2 according to the ninth embodiment may create different histograms for each of the above-mentioned SIAS, age, and sex, and calculate the resting heart rate based on the peaks in the histograms. Alternatively, the resting heart rate calculation device 2 according to the ninth embodiment may create different histograms for each condition based on several combinations of FIM, SIAS, age, and sex, and calculate the resting heart rate based on the peaks in the histograms.

[0055] <Other Embodiments> Although one embodiment of this invention has been described in detail above with reference to the drawings, the specific configuration is not limited to that described above, and various design changes can be made without departing from the spirit of this invention. For example, in the embodiment described above, the resting heart rate calculation device 2 is an external device to the sensor terminal 202 and the relay terminal 203, but it is not limited to this. For example, the sensor terminal 202 or the relay terminal 203 may include the resting heart rate calculation device 2. [Explanation of symbols]

[0056] 2 Resting heart rate calculation device, 201 Subject, 202 Sensor terminal, 203 Relay terminal, 200 Data receiving unit, 210 Heart rate calculation unit, 220 Resting heart rate calculation unit, 230 Output unit, 240 Exercise intensity calculation unit, 250 Measurement period determination unit, 260 Ensemble averaging processing unit, 270 Lifestyle regularity evaluation unit, 280 State estimation unit, 290 Exercise intensity classification unit, 300 Memory unit

Claims

1. A heart rate calculation unit that calculates the heart rate from electrocardiogram data measured by an electrocardiograph, A resting heart rate calculation unit calculates the resting heart rate by determining the smaller quantile of two peaks observed in a histogram based on heart rates calculated from multiple subjects, from among the heart rates recorded for 24 hours or more; A resting heart rate calculator equipped with [specific features / features].

2. A heart rate calculation unit that calculates the heart rate from electrocardiogram data measured by an electrocardiograph, A resting heart rate calculation unit calculates the resting heart rate from the heart rates recorded for 24 hours or more, specifically the heart rates corresponding to predetermined quantiles. Equipped with, The aforementioned quantiles are between the 20th and 30th percentiles. Resting heart rate calculator.

3. An exercise intensity calculation unit calculates the exercise intensity corresponding to the heart rate based on the resting heart rate, A resting heart rate calculation device according to claim 1 or claim 2, further comprising the above.

4. A measurement period determination unit that determines whether the number of recorded heart rate data points exceeds a certain number, Furthermore, The resting heart rate calculation unit calculates the resting heart rate when the number of recorded heart rate data exceeds a certain number. A resting heart rate calculation device according to claim 1 or claim 2.

5. An ensemble averaging processing unit calculates the ensemble average of heart rates corresponding to the same time, A resting heart rate calculation device according to claim 1 or claim 2, further comprising the above.

6. A lifestyle regularity evaluation unit that evaluates the degree of lifestyle regularity by calculating the number of heart rates recorded during a specific period that are smaller than the resting heart rate, A resting heart rate calculation device according to claim 1 or claim 2, further comprising the above.

7. A posture estimation unit that estimates the posture state of the subject based on the subject's acceleration data, A posture-specific exercise intensity calculation unit that calculates exercise intensity for each of the aforementioned posture states, The resting heart rate calculation device according to claim 3, further comprising the above.

8. The resting heart rate calculation unit calculates the resting heart rate as the heart rate corresponding to the quantile determined by the subject's rank information. The resting heart rate calculation device according to claim 1.

9. A heart rate calculation step that calculates the heart rate from electrocardiogram data measured by an electrocardiograph, A resting heart rate calculation step, in which, from the heart rates recorded for 24 hours or more, the resting heart rate is calculated by determining the resting heart rate from the smaller of the two peaks observed in a histogram based on the heart rates calculated from multiple subjects, and the resting heart rate is calculated from the resting heart rate, A method for calculating resting heart rate, comprising the following characteristics.

10. On the computer, The heart rate is calculated from the electrocardiogram data measured by the electrocardiograph. Of the heart rates recorded for 24 hours or more, the resting heart rate is calculated by determining the resting heart rate from the smaller of the two peaks observed in the histogram based on the heart rates of multiple subjects. program.

11. On the computer, The heart rate is calculated from the electrocardiogram data measured by the electrocardiograph. Of the heart rates recorded for 24 hours or more, the resting heart rate is calculated by determining the resting heart rate from the smaller of the two peaks observed in the histogram based on the heart rates of multiple subjects. A recording medium on which a program is stored.

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