Heart rate detection device, heart rate detection system, heart rate detection method, and program

Abstract

It accurately generates heart rate information representing the heart rate of the person being measured. [Solution] The heart rate detection device comprises an acquisition unit, a correction unit, and a data determination unit. The acquisition unit acquires N heart rate data sequences (where N is an integer of 2 or more) that represent the time change in the subject's heart rate interval during the measurement period, each generated in a different manner. The correction unit performs error correction processing on each of the N heart rate data sequences. The data determination unit generates a final heart rate data sequence that represents the time change in the subject's heart rate interval during the measurement period, based on the N heart rate data sequences. For each set of N heart rate interval data that is estimated to represent the heart rate interval at the same time contained in the N heart rate data sequences, the data determination unit generates the final heart rate interval data to be included in the final heart rate data sequence.

Description

[Technical Field]

[0001] The present invention relates to a heart rate detection device, a heart rate detection system, a heart rate detection method, and a program. [Background technology]

[0002] Society 5.0, one of Japan's science and technology policies, aims to create new value by analyzing data in a society where everything is connected to the internet using IoT (Internet of Things) technology, thereby achieving a comfortable, vibrant, and high-quality life, as well as economic development and the resolution of social issues. IoT technology is also beginning to be applied to the field of human beings. For example, Patent Documents 1-5 describe technologies for sensing the biosignals of a person being measured. In recent years, in order to realize Society 5.0, technologies that measure heart rate non-contact without the person being measured's awareness, which can lead to the analysis of human health and emotions, have attracted attention. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-096161 [Patent Document 2] Japanese Patent Publication No. 2021-174046 [Patent Document 3] Japanese Patent Publication No. 2020-174690 [Patent Document 4] Japanese Patent Publication No. 2019-198531 [Patent Document 5] Japanese Patent Publication No. 2018-187161 [Overview of the project] [Problems that the invention aims to solve]

[0004] Sensors that detect heart rate, whether by contact or non-contact, can be prone to false detections, especially when the subject is moving. This is particularly likely with non-contact heart rate detection. The heart rate signal may contain many disturbance components, making it difficult to accurately generate heart rate information such as heart rate interval data (RRI: RR Interval) from the heart rate signal.

[0005] The present invention aims to provide a heart rate detection device, a heart rate detection system, a heart rate detection method, and a program that can accurately generate heart rate interval data representing the heart rate interval of a subject from a heart rate signal that includes disturbance components caused by the subject's movement or other factors. [Means for solving the problem]

[0006] To solve the above-mentioned problems and achieve the objective, the heart rate detection device according to the present invention comprises an acquisition unit, a correction unit, and a data determination unit. The acquisition unit acquires N heart rate data sequences (where N is an integer of 2 or more) that represent the time change in the heart rate interval of a person being measured during a measurement period, which are generated in different ways from one another. The correction unit performs error correction processing on each of the N heart rate data sequences. The data determination unit generates a final heart rate data sequence that represents the time change in the heart rate interval of the person being measured during the measurement period, based on the N heart rate data sequences. For each set of N heart rate interval data that is estimated to represent the heart rate interval at the same time contained in the N heart rate data sequences, the data determination unit generates final heart rate interval data to be included in the final heart rate data sequence. [Effects of the Invention]

[0007] According to the present invention, heart rate interval data representing the heart rate interval of a subject can be accurately generated from a heart rate signal that includes disturbance components caused by the subject's movement, etc. [Brief explanation of the drawing]

[0008] [Figure 1]FIG. 1 is a diagram showing the configuration of a heartbeat detection system according to an embodiment. [Figure 2] FIG. 2 is a diagram showing the functional configuration of a heartbeat detection device. [Figure 3] FIG. 3 is a diagram showing an example of N heartbeat data sequences and a final heartbeat data sequence. [Figure 4] FIG. 4 is a diagram showing the functional configuration of a final data sequence generation unit. [Figure 5] FIG. 5 is a flowchart showing the flow of reliability value addition processing. [Figure 6] FIG. 6 is a flowchart showing the flow of first error correction processing. [Figure 7] FIG. 7 is a diagram showing an example of a delimiter position when the delimiter positions of a plurality of first divided periods with respect to a measurement period are shifted. [Figure 8] FIG. 8 is a flowchart showing an example of the flow of the process of S35. [Figure 9] FIG. 9 is a diagram showing an example of a delimiter position when second error correction processing is executed after executing first error correction processing with respect to a measurement period. [Figure 10] FIG. 10 is a diagram for explaining the first example of the first correction process. [Figure 11] FIG. 11 is a diagram for explaining the second example of the first correction process. [Figure 12] FIG. 12 is a diagram for explaining the first example of the second correction process. [Figure 13] FIG. 13 is a diagram for explaining the second example of the second correction process. [Figure 14] FIG. 14 is a diagram for explaining the third example of the second correction process. [Figure 15] FIG. 15 is a diagram showing an example of the arrangement of N corrected heartbeat data sequences. [Figure 16] FIG. 16 is a flowchart showing the flow of the process of a data determination unit. [Figure 17] FIG. 17 is a flowchart showing an example of the flow of the generation process of final heartbeat interval data. [Figure 18] FIG. 18 is a diagram showing an arrangement of N corrected heartbeat data sequences and an example of a final heartbeat data sequence. [Figure 19] FIG. 19 is a diagram showing a hardware configuration of the information processing apparatus. Mode for Carrying Out the Invention

[0009] Hereinafter, embodiments will be described with reference to the drawings.

[0010] FIG. 1 is a diagram showing a configuration of a heartbeat detection system 10 according to an embodiment. The heartbeat detection system 10 detects heartbeat information representing information related to the heartbeat of a measurement subject, such as heartbeat interval data (RRI: R-R Interval) representing the heartbeat interval of the measurement subject.

[0011] The heartbeat detection system 10 according to the embodiment includes a sensor device 22, a heartbeat detection device 24, and a display device 26.

[0012] The sensor device 22 outputs a sensor signal including components of the heartbeat of the measurement subject. For example, the sensor device 22 non-contactedly detects components of the heartbeat of the measurement subject and outputs a sensor signal including the detected components of the heartbeat.

[0013] For example, the sensor device 22 is a camera. The camera functioning as the sensor device 22 images the measurement subject and outputs an imaging signal obtained by imaging the measurement subject as a sensor signal. The camera is optical and generates a moving image at a frame rate of 30 fps or more with a resolution of 2K or more, for example. When the measurement subject moves, the camera may control the movement of the imaging direction so as to follow the measurement subject and include the measurement subject within the angle of view. The imaging signal output from the camera includes components of the heartbeat in, for example, a component of a change in the amount of light in a region where the skin of the subject is exposed.

[0014] Furthermore, for example, the sensor device 22 may be a millimeter-wave radar device. The millimeter-wave radar device functioning as sensor device 22 emits electromagnetic waves in the millimeter-wave band to the person being measured and detects the reflected waves from the person being measured. The millimeter-wave radar device then outputs a radar output signal, which includes the heart rate component of the person being measured, as a sensor signal. For example, the millimeter-wave radar device includes at least one MIMO (Multi Input Multi Output) millimeter-wave radar that transmits and receives radio waves with a frequency of 24 GHz or higher. Note that the millimeter-wave radar device is not limited to the MIMO system and may include multiple millimeter-wave radars of other types.

[0015] Furthermore, the sensor device 22 is not limited to a device that detects components of the subject's heart rate without contact with the subject, but may also be a device that detects components of the subject's heart rate by making contact with the subject.

[0016] The heart rate detection device 24 outputs the subject's heart rate information based on the sensor signal output from the sensor device 22. The heart rate information is a sequence of heart rate interval data representing the time change in the subject's heart rate interval during the measurement period. The heart rate detection device 24 may also output error information indicating that heart rate information could not be detected at a time when it is not possible to detect heart rate information from the sensor signal.

[0017] The heart rate detection device 24 is comprised of a computer. The heart rate detection device 24 may be a server device on a network, or it may be a cloud system in which multiple server devices on a network work together. If the heart rate detection device 24 is a server device on a network, the sensor device 22 is connected to the heart rate detection device 24 via the network. The computer and server device function as the heart rate detection device 24 by executing a program.

[0018] The display device 26 acquires heart rate information from the heart rate detection device 24 and displays it on the monitor. This allows the display device 26 to allow the person taking the measurement to recognize the heart rate information of the person being measured. The display device 26 also acquires error information from the heart rate detection device 24 and displays it on the monitor. This allows the display device 26 to allow the person taking the measurement to recognize that an error has occurred in detecting the heart rate information of the person being measured. The display device 26 may also display heart rate information and error information on an LED (Light Emitting Diode) or the like.

[0019] The heart rate detection system 10 may also include, in place of or in addition to the display device 26, at least one of a printer, an audio output device, a storage device, or a communication device. The printer acquires heart rate information and error information from the heart rate detection device 24 and prints it on paper or the like. The audio output device acquires heart rate information and error information from the heart rate detection device 24 and outputs it as audio. The storage device acquires heart rate information and error information from the heart rate detection device 24 and stores it in a storage medium. The communication device acquires heart rate information and error information from the heart rate detection device 24 and transmits it to other devices via a network. By including a printer, an audio output device, a storage device, or a communication device, such a heart rate detection system 10 can also allow the person taking the measurement to recognize the heart rate information of the person being measured and whether an error has occurred.

[0020] Figure 2 shows the functional configuration of the heart rate detection device 24.

[0021] The heart rate detection device 24 comprises a heart rate signal generation unit 32, a heart rate data sequence generation unit 34, and a final data sequence generation unit 36.

[0022] The heart rate signal generation unit 32 acquires sensor signals from the sensor device 22 and generates N heart rate signals, where N is an integer greater than or equal to 2. Each of the N heart rate signals represents the heart rate of the subject during a predetermined measurement period. Each of the N heart rate signals may, for example, have a different source sensor signal, or may be generated using different methods based on the same sensor signal. Therefore, although each of the N heart rate signals represents the heart rate of the same subject during the same measurement period, their waveforms may differ from those of other heart rate signals.

[0023] For example, the heart rate signal generation unit 32 extracts image components of the exposed spatial region of the subject's skin from the imaging signal output from the camera, and generates one of N heart rate signals based on the image components of the extracted spatial region. Alternatively, for example, the heart rate signal generation unit 32 generates a detection signal representing the heart rate component in the subject's body from the radar output signal output from the millimeter-wave radar device, and generates one of N heart rate signals based on the generated detection signal.

[0024] Each of the N heart rate signals output from the heart rate signal generation unit 32 is time-series data representing the magnitude of the heartbeat. However, each of the N heart rate signals may include disturbance components caused by, for example, the movement of the person being measured, and disturbance components caused by vibration of the sensor device 22.

[0025] The heart rate data sequence generation unit 34 acquires N heart rate signals from the heart rate signal generation unit 32. Based on the acquired N heart rate signals, the heart rate data sequence generation unit 34 generates N heart rate data sequences.

[0026] Each of the N heart rate data sequences represents the time variation of the subject's heart rate intervals during the same measurement period, generated in different ways from one another. More specifically, each of the N heart rate data sequences includes multiple heart rate interval data points arranged in a time series, each representing a heart rate interval, and multiple confidence values ​​corresponding to the multiple heart rate interval data points.

[0027] The heart rate data sequence generation unit 34 generates the first heart rate data sequence out of N heart rate data sequences based on the first heart rate signal out of N heart rate signals. The heart rate data sequence generation unit 34 calculates the first heart rate data sequence as follows, for example.

[0028] The heart rate data sequence generation unit 34 generates a binarized signal, for example, by binarizing the first heart rate signal. Next, the heart rate data sequence generation unit 34 performs bandpass filtering to restrict the period of the binarized signal to a range between a preset upper period and a preset lower period smaller than the upper period. Subsequently, the heart rate data sequence generation unit 34 detects a first edge, which is either a rising or falling edge in the bandpass filtered binarized signal, and divides the measurement period for each first edge. For each of the multiple edge intervals into which the measurement period is divided for each first edge, the heart rate data sequence generation unit 34 calculates heart rate interval data, which is the time length.

[0029] Next, the heart rate data sequence generation unit 34 calculates a confidence value for each of the multiple edge intervals. The confidence value is a value that represents the reliability of the corresponding heart rate interval data. For example, the confidence value is represented by two values: a high confidence interval value or a low confidence interval value. The high confidence interval value indicates that the target heart rate interval data is data from an interval with a reliability of above a certain standard. The low confidence interval value indicates that the target heart rate interval data is data from an interval with a reliability lower than the standard.

[0030] For example, the heart rate data sequence generation unit 34 defines the confidence value of heart rate interval data where the absolute value of the difference between the multiple heart rate interval data and the average value of the multiple heart rate interval data is less than or equal to a predetermined margin value as the high confidence interval value. Conversely, the heart rate data sequence generation unit 34 defines the confidence value of heart rate interval data where the absolute value of the difference between the multiple heart rate interval data and the average value of the multiple heart rate interval data is greater than a predetermined margin value as the low confidence interval value.

[0031] Furthermore, for example, the heart rate data sequence generation unit 34 may, for heart rate interval data that is temporally adjacent to heart rate interval data whose confidence value is a low confidence interval value, set the confidence value to the low confidence interval value regardless of the absolute value of the difference with respect to the mean.

[0032] The heart rate data sequence generation unit 34 then generates a first heart rate data sequence that includes the multiple heart rate interval data generated as described above, and multiple confidence values ​​corresponding to the multiple heart rate interval data.

[0033] The final data sequence generation unit 36 ​​acquires N heart rate data sequences. Based on the N heart rate data sequences, the final data sequence generation unit 36 ​​performs correction processing on the heart rate data to generate the final heart rate data sequence. In this case, the final data sequence generation unit 36 ​​generates the final heart rate interval data to be included in the final heart rate data sequence for each set of N heart rate interval data that are estimated to represent the heart rate interval at the same time contained in the N heart rate data sequences. The final heart rate data sequence represents the time change of the subject's heart rate interval during the measurement period. More specifically, the final heart rate data sequence includes multiple final heart rate interval data, each representing a heart rate interval, arranged in a time series.

[0034] When performing correction processing on heart rate data, the final data sequence generation unit 36 ​​calculates a data sequence confidence value representing reliability for each of the N heart rate data sequences based on multiple confidence values. Then, for each set of N heart rate interval data that is estimated to represent the heart rate interval of the same heartbeat included in the N heart rate data sequences, the final data sequence generation unit 36 ​​generates the final heart rate interval data to be included in the final heart rate data sequence, based on the confidence value of each of the N heart rate interval data and the data sequence confidence value for each of the N heart rate data sequences.

[0035] The final data sequence generation unit 36 ​​then outputs the generated final heart rate data sequence as heart rate information to the display device 26.

[0036] Figure 3 shows an example of N heart rate data sequences and a final heart rate data sequence.

[0037] Each of the N heart rate data sequences contains multiple heart rate interval data points arranged in time series, along with multiple confidence values.

[0038] Each of the multiple heart rate interval data represents a heart rate interval of time. For example, in the first heart rate data column (#1) in Figure 3, the heart rate interval data are T11, T12, T13, ... For example, in the second heart rate data column (#2) in Figure 3, the heart rate interval data are T21, T22, T23, ... For example, in the Nth heart rate data column (#N) in Figure 3, the heart rate interval data is T N 1,T N 2,T N 3, ... and so on.

[0039] Multiple confidence values ​​correspond one-to-one with multiple heart rate interval data. Each of the multiple confidence values ​​represents the reliability of the corresponding heart rate interval data among the multiple heart rate interval data. For example, in the case of the N heart rate data sequence in Figure 3, the confidence values ​​represent high confidence interval values ​​or low confidence interval values ​​described in correspondence with the heart rate interval data (T11, T12, ..., etc.).

[0040] The final heart rate data sequence is generated based on N heart rate data sequences. The final heart rate data sequence contains multiple final heart rate interval data points arranged in time series.

[0041] Each of the multiple last heart rate interval data represents a heart rate interval, which is time. For example, in the last heart rate data column (#E) in Figure 3, the last heart rate interval data is T E 1,T E 2,T E 3, ... and so on.

[0042] Figure 4 shows the functional configuration of the final data column generation unit 36.

[0043] The final data sequence generation unit 36 ​​includes an acquisition unit 42, a data sequence storage unit 44, a confidence value addition unit 46, a correction unit 48, an association unit 50, a corrected data storage unit 52, and a data determination unit 54.

[0044] The acquisition unit 42 acquires N heart rate data sequences from the heart rate data sequence generation unit 34, each generated using a different method, which represent the time change in the subject's heart rate interval during the measurement period. The acquisition unit 42 stores the acquired N heart rate data sequences in the data sequence storage unit 44.

[0045] At least one of the N heart rate data sequences acquired by the acquisition unit 42 may be an uncalculated heart rate data sequence that does not contain multiple confidence values. For example, the acquisition unit 42 may acquire N heart rate data sequences that include one or more uncalculated heart rate data sequences.

[0046] The data sequence storage unit 44 stores N heart rate data sequences. The data sequence storage unit 44 identifies and stores each of the N heart rate data sequences.

[0047] The confidence value addition unit 46 determines whether or not an uncalculated heart rate data sequence is included in the N heart rate data sequences stored in the data sequence storage unit 44. If the N heart rate data sequences stored in the data sequence storage unit 44 do not include an uncalculated heart rate data sequence, the confidence value addition unit 46 does not perform any further processing on the N heart rate data sequences stored in the data sequence storage unit 44.

[0048] The confidence value addition unit 46 calculates a confidence value for each of the multiple heart rate interval data included in the uncalculated heart rate data if the N heart rate data sequences stored in the data sequence storage unit 44 include an uncalculated heart rate data sequence. In this case, the confidence value addition unit 46 calculates the confidence value in the same way as the heart rate data sequence generation unit 34. Then, the confidence value addition unit 46 adds the calculated confidence value to each of the multiple heart rate interval data included in the uncalculated heart rate data sequence stored in the data sequence storage unit 44.

[0049] The correction unit 48 performs error correction processing on each of the N heart rate data sequences stored in the data sequence storage unit 44.

[0050] The correction unit 48 includes a first error correction unit 62 and a second error correction unit 64. The first error correction unit 62 performs a first error correction process on each of the N heart rate data sequences stored in the data sequence storage unit 44. The second error correction unit 64 performs a second error correction process on each of the N heart rate data sequences stored in the data sequence storage unit 44. For example, the second error correction unit 64 performs a second error correction process on each of the N heart rate data sequences after the first error correction process has been performed.

[0051] The first error correction unit 62 includes a first extraction processing unit 72, a first error correction processing unit 74, a first confidence value update unit 76, and a first repetition control unit 78.

[0052] The first extraction processing unit 72 performs a first extraction process for each of the N heart rate data sequences stored in the data sequence storage unit 44. For example, when performing a first error correction process on the first heart rate data sequence among the N heart rate data sequences, the first extraction processing unit 72 extracts one or more heart rate interval data representing the heart rate interval of the target heart rate in the first heart rate data sequence for each of the multiple first division periods, which are obtained by dividing the measurement period into predetermined first time lengths.

[0053] The first error correction processing unit 74 executes the first correction process for each of the multiple first division periods. For example, for each of the multiple first division periods, the first error correction processing unit 74 executes a process to correct the heart rate interval data whose confidence value is the low confidence interval value among the one or more heart rate interval data extracted by the first extraction process if the heart rate interval data whose confidence value is the low confidence interval value is included in a predetermined first proportion or more of the predetermined reference time.

[0054] The first confidence value update unit 76 calculates and updates the confidence value for each of the multiple heart rate interval data included in each of the N heart rate data sequences on which the first correction process has been performed. For example, when the first error correction process is performed on the first heart rate data sequence, the first confidence value update unit 76 calculates and updates the confidence value for each of the multiple heart rate interval data included in the first heart rate data sequence.

[0055] The first repetition control unit 78 performs a first repetition control process for each of the N heart rate data sequences, shifting the phase of the positions of the divisions of the multiple first division periods relative to the measurement period, and executing a first error correction process. More specifically, as the first repetition control process, the first repetition control unit 78 shifts the phase of the divisions of the first division periods relative to the measurement period for each of the N heart rate data sequences, and executes a set of a first extraction process, a first correction process, and a first confidence value update process each time the phase is shifted.

[0056] The second error correction unit 64 performs a second error correction process similar to the first error correction process, but with a change in the length of the division period that divides the measurement period.

[0057] For example, the second error correction unit 64 includes a second extraction processing unit 82, a second error correction processing unit 84, a second confidence value update unit 86, and a second repetition control unit 88.

[0058] The second extraction processing unit 82 performs a second extraction process for each of the N heart rate data sequences stored in the data sequence storage unit 44. For example, when performing a second error correction process on the first heart rate data sequence among the N heart rate data sequences, the second extraction processing unit 82 extracts one or more heart rate interval data representing the heart rate interval of the target heart rate in the first heart rate data sequence for each of the multiple second division periods, which are obtained by dividing the measurement period into a predetermined second time length that is longer than the first time length.

[0059] The second error correction processing unit 84 executes a second correction process for each of the multiple second division periods. For example, for each of the multiple second division periods, the second error correction processing unit 84 executes a process to correct the heart rate interval data whose confidence value is a low confidence interval value among the one or more extracted heart rate interval data, if the one or more heart rate interval data extracted by the second extraction process contain a predetermined second proportion or more of heart rate interval data whose confidence value is a low confidence interval value relative to a predetermined reference time.

[0060] The second confidence value update unit 86 calculates and updates the confidence value for each of the multiple heart rate interval data included in each of the N heart rate data sequences on which the second correction process has been performed. For example, when the second error correction process is performed on the first heart rate data sequence, the second confidence value update unit 86 calculates and updates the confidence value for each of the multiple heart rate interval data included in the first heart rate data sequence.

[0061] The second repetition control unit 88 performs a second repetition control process for each of the N heart rate data sequences, shifting the phase of the boundary positions of each of the multiple second division periods relative to the measurement period, and executing a second error correction process. More specifically, as a second repetition control process, the second repetition control unit 88 shifts the phase of the boundary positions of the second division periods relative to the measurement period for each of the N heart rate data sequences, and executes a set of a second extraction process, a second correction process, and a second confidence value update process each time the phase is shifted.

[0062] The association unit 50 obtains N heart rate data sequences from the data sequence storage unit 44 after the correction process has been performed by the correction unit 48. The association unit 50 associates N sets of heart rate interval data that are estimated to represent the heart rate intervals of heartbeats that occurred at the same time in the N heart rate data sequences, identifies each of the N corrected heart rate data sequences, and stores the N heart rate data sequences as N corrected heart rate data sequences in the corrected data storage unit 52.

[0063] The correction data storage unit 52 stores N corrected heart rate data sequences, each associated with a set of N heart rate interval data that the association unit 50 estimates to represent the heart rate intervals of heartbeats that occurred at the same time.

[0064] Each of the N corrected heart rate data sequences stored in the corrected data storage unit 52 includes multiple heart rate interval data and multiple confidence values.

[0065] The data determination unit 54 generates a final heart rate data sequence that represents the time change in the subject's heart rate interval during the measurement period, based on N heart rate data sequences. In this case, for each set of N heart rate interval data that is estimated to represent the heart rate interval of the same heartbeat included in the N heart rate data sequences, the data determination unit 54 generates final heart rate interval data that represents the heart rate interval of the corresponding heartbeat from among the multiple final heart rate interval data included in the final heart rate data sequence, based on the confidence value of each of the N heart rate interval data.

[0066] In this embodiment, the data determination unit 54 generates a final heart rate data sequence that represents the time change in the subject's heart rate interval during the measurement period, based on N corrected heart rate data sequences stored in the corrected data storage unit 52. In this case, for each set of N heart rate interval data that are estimated to represent the heart rate interval of the same heartbeat included in the N corrected heart rate data sequences, the data determination unit 54 generates final heart rate interval data that represents the heart rate interval of the corresponding heartbeat from among the multiple final heart rate interval data included in the final heart rate data sequence, based on the confidence value of each of the N heart rate interval data.

[0067] For example, the data determination unit 54 includes a data sequence confidence value generation unit 92, a heart rate confidence value generation unit 94, and a final data determination unit 96.

[0068] The data sequence confidence value generation unit 92 calculates a data sequence confidence value for each of the N corrected heart rate data sequences stored in the corrected data storage unit 52. More specifically, for each of the N corrected heart rate data sequences, the data sequence confidence value generation unit 92 calculates a data sequence confidence value based on the ratio of the number of heart rate interval data points whose confidence value is a high confidence interval value to the total number of heart rate interval data points included.

[0069] The heart rate confidence value generation unit 94 calculates a heart rate confidence value for each of the N sets of heart rate interval data associated with heartbeats occurring at the same time, which are included in the N corrected heart rate data sequences stored in the corrected data storage unit 52. More specifically, the heart rate confidence value generation unit 94 calculates a heart rate confidence value corresponding to the number of heart rate interval data whose included confidence values ​​represent high confidence interval values.

[0070] The final data determination unit 96 generates the final heart rate interval data to be included in the final heart rate data sequence for each of the N sets of heart rate interval data, based on the heart rate confidence value and the data sequence confidence values ​​of each of the N corrected heart rate data sequences. The final data determination unit 96 then outputs the generated final heart rate data sequence.

[0071] Figure 5 is a flowchart showing the flow of the confidence value addition process. The confidence value addition unit 46 executes the process in the flow shown in Figure 5, for example.

[0072] The confidence value addition unit 46 executes the processes from S12 to S20 for each of the N heart rate data sequences stored in the data sequence storage unit 44 (loop processing between S11 and S21).

[0073] Within the loop processing, first, in S12, the confidence value addition unit 46 determines whether or not the heart rate data sequence to be processed contains confidence values. If the heart rate data sequence to be processed does not contain confidence values, that is, if the heart rate data sequence to be processed is an uncalculated heart rate data sequence (No in S12), the confidence value addition unit 46 proceeds to S13. If the heart rate data sequence to be processed contains confidence values, that is, if the heart rate data sequence to be processed is not an uncalculated heart rate data sequence (Yes in S12), the confidence value addition unit 46 proceeds to S21 without executing the processes from S12 to S20.

[0074] In S13, the confidence value addition unit 46 calculates the average value of multiple heart rate interval data included in the uncalculated heart rate data sequence to be processed.

[0075] Next, the confidence value addition unit 46 performs the processes from S15 to S19 for each of the multiple heart rate interval data included in the uncalculated heart rate data sequence to be processed (loop processing between S14 and S20).

[0076] Within the loop processing between S14 and S20, first, in S15, the confidence value addition unit 46 calculates the absolute value of the difference between the target heart rate interval data and the average value of multiple heart rate interval data.

[0077] Next, in S16, the confidence value addition unit 46 determines whether the absolute value of the calculated difference is less than or equal to a predetermined margin value. If the absolute value of the calculated difference is less than or equal to the margin value (Yes in S16), the confidence value addition unit 46 proceeds to S17. If the absolute value of the calculated difference is greater than the margin value (No in S16), the confidence value addition unit 46 proceeds to S18.

[0078] In S17, the confidence value addition unit 46 sets the confidence value of the target heart rate interval data to a high confidence interval value. In S18, the confidence value addition unit 46 sets the confidence value of the target heart rate interval data to a low confidence interval value. After completing S17 or S18, the confidence value addition unit 46 proceeds to S19.

[0079] In S19, the confidence value addition unit 46 assigns a confidence value, either a high confidence interval value or a low confidence interval value, to the target heart rate interval data and adds it to the uncalculated heart rate data sequence to be processed.

[0080] In S20, if the confidence value addition unit 46 has completed the processing from S15 to S19 for all of the multiple heart rate interval data included in the uncalculated heart rate data sequence to be processed, it exits the loop processing between S14 and S20 and proceeds to processing in S21.

[0081] In S21, if the confidence value addition unit 46 has completed the processing from S12 to S20 for all N heart rate data sequences, it exits the loop processing between S11 and S21. Then, when the confidence value addition unit 46 exits the loop processing between S11 and S21, this flow is terminated.

[0082] By performing the above processing, the confidence value addition unit 46 can determine, for each of the multiple heart rate interval data included in the uncalculated heart rate data column, set the confidence value to a high confidence interval value if the absolute value of the difference between the target heart rate interval data and the average value of the multiple heart rate interval data is less than or equal to a preset margin value, and set the confidence value to a low confidence interval value if the absolute value is greater than the margin value.

[0083] Figure 6 is a flowchart showing the flow of the first error correction process. The correction unit 48 executes the first error correction process, for example, in the flow shown in Figure 6.

[0084] First, the correction unit 48 performs the processing from S32 to S37 for each of the N heart rate data sequences (loop processing between S31 and S38).

[0085] In S32, the correction unit 48 identifies a plurality of first division periods, each of which is a predetermined first time length, within the measurement period. For example, if the measurement period is 30 seconds and the frame rate is 30 fps, the correction unit 48 identifies a plurality of first division periods, each of which is 5 seconds long.

[0086] Next, the correction unit 48 executes the processes in S34 and S35 for each of the specified first division periods (loop processing between S33 and S37).

[0087] In S34, the correction unit 48 performs a first extraction process. For example, the correction unit 48 performs a first extraction process to extract one or more heart rate interval data representing the heart rate interval of the target first division period in the heart rate data sequence to be processed.

[0088] Next, in S35, the correction unit 48 executes the first correction process. For example, if the heart rate interval data extracted by the first extraction process contains, for a predetermined first percentage or more of a predetermined reference time, heart rate interval data with a low confidence interval value among the extracted heart rate interval data, the correction unit 48 executes a process to correct the heart rate interval data with a low confidence interval value among the extracted heart rate interval data. For example, the correction unit 48 executes a correction process if, for a reference time of 5-second intervals, heart rate interval data with a low confidence interval value accounts for 40% or more of the time. The details of the first correction process will be described later with reference to Figure 8.

[0089] In S36, the correction unit 48 performs a first confidence value update process on the target heart rate data sequence on which the first correction process has been performed, calculating and updating the confidence value for each of the multiple heart rate interval data included.

[0090] If the correction unit 48 has completed the processing in S34 to S36 for all of the multiple first division periods, it exits the loop processing between S33 and S37 and proceeds to processing in S38.

[0091] Then, once the correction unit 48 has completed the processing from S32 to S37 for all N heart rate data sequences, it exits the loop processing between S31 and S38 and terminates this flow.

[0092] By performing the first error correction process described above, the correction unit 48 can correct N heart rate data sequences to reduce the number of heart rate interval data points with low confidence interval values ​​and include more heart rate interval data points with good accuracy.

[0093] Figure 7 shows an example of the division positions when the division positions of multiple first division periods are shifted relative to the measurement period.

[0094] The correction unit 48 may perform the first error correction process shown in Figure 6 by shifting the phase of the boundary positions of each of the multiple first division periods relative to the measurement period by an interval shorter than the first division period. That is, for each of the N heart rate data sequences, the correction unit 48 may shift the phase of the boundary positions of the first division periods relative to the measurement period by an interval shorter than the first division period, and execute a set of the first extraction process (S34), the first correction process (S35), and the first confidence value update process (S36) each time the phase is shifted.

[0095] For example, suppose the measurement period is 30 seconds, the frame rate is 30 fps, and the first division period is 5 seconds. In this case, as shown in Figure 7, the correction unit 48 sequentially shifts the division position of the first division period backward by 1 second from the beginning of the measurement period, and for each 1-second shift in the division position, it executes a set of the first extraction process (S34), the first correction process (S35), and the first confidence value update process (S36).

[0096] In this way, the correction unit 48 increases the likelihood of correcting heart rate interval data whose confidence value is a low confidence interval value by shifting the position of each of the multiple first division periods relative to the measurement period at intervals shorter than the first division period, and can correct N heart rate data sequences to include more accurate heart rate interval data.

[0097] Figure 8 is a flowchart showing an example of the processing flow in S35. The correction unit 48 performs the first correction process in S35, for example, in the flow shown in Figure 8.

[0098] First, in S41, the correction unit 48 determines whether the extracted heart rate interval data contains, or does not contain, heart rate interval data whose confidence value is a high confidence interval value, at least one predetermined percentage of a predetermined reference time.

[0099] If, among the one or more extracted heart rate interval data points, there are heart rate interval data points with a high confidence interval value that account for a predetermined first percentage or more of the predetermined reference time (Yes in S41), then no correction processing is required for the first division period to be processed, and this flow is terminated without performing any correction processing on any of the one or more extracted heart rate interval data points.

[0100] If, among the one or more extracted heart rate interval data, there are no heart rate interval data with a confidence value equal to a high confidence interval value in a predetermined proportion or more of a predetermined reference time (No. in S41), the correction unit 48 proceeds to S42.

[0101] In S42, the correction unit 48 determines whether the extracted heart rate interval data includes heart rate interval data whose confidence value is a high confidence interval value in one or more predetermined arrangement patterns.

[0102] If the extracted heart rate interval data does not include any heart rate interval data whose confidence value is a high confidence interval value in any of the predetermined arrangement patterns (No. in S42), the correction unit 48 determines that correction processing cannot be performed for the first division period to be processed, and terminates this flow without performing correction processing on any of the extracted heart rate interval data.

[0103] If the extracted heart rate interval data includes one or more heart rate interval data where the confidence value is a high confidence interval value in one or more predetermined arrangement patterns (Yes in S42), the correction unit 48 proceeds to the loop processing in S43 to S48.

[0104] In the loop processing from S43 to S48, the correction unit 48 performs processing on each of the heart rate interval data points included in the extracted 1 or more heart rate interval data points whose confidence value is a low confidence interval value.

[0105] In S44 within the loop, the correction unit 48 calculates the heart rate interval when the target heart rate interval data is corrected according to a predetermined rule.

[0106] Next, in S45, the correction unit 48 calculates the average value of the heart rate interval data whose confidence value is a high confidence interval value, which is included in one or more extracted heart rate interval data.

[0107] Next, in S46, the correction unit 48 calculates the absolute value of the difference between the heart rate interval when the correction process is performed according to the predetermined rule calculated in S44 and the average value of the heart rate interval data for which the confidence value calculated in S45 is a high confidence interval value. The correction unit 48 then determines whether the heart rate interval data to be processed is correctable data for which the absolute value of the difference is less than or equal to a predetermined margin value.

[0108] If the heart rate interval data to be processed is not correctable data (No. in S46), the correction unit 48 proceeds to S48 without performing the correction process.

[0109] If the heart rate interval data to be processed is correctable data (Yes in S46), the correction unit 48 proceeds to S47.

[0110] In S47, the correction unit 48 performs a correction process on the heart rate interval data to be processed according to a predetermined rule. After completing the process in S47, the correction unit 48 proceeds to process S48.

[0111] Then, if the correction unit 48 has executed the processing in S44 to S47 for all of the heart rate interval data included in the extracted heart rate interval data whose confidence value is a low confidence interval value, it exits the loop processing in S43 to S48. After the correction unit 48 has finished the loop processing in S43 to S48, it terminates this flow.

[0112] By performing the above processing, the correction unit 48 can identify heart rate interval data that is highly likely to become a high confidence interval value after correction as correctable data, and can perform correction processing on the identified correctable data.

[0113] Figure 9 shows an example of the delimiter position when the second error correction process is performed after the first error correction process has been performed on the measurement period.

[0114] In this embodiment, the correction unit 48 performs a first error correction process for each of the N heart rate data sequences, and then performs a second error correction process for each of the N heart rate data sequences.

[0115] For example, when performing a second error correction process on the first heart rate data sequence among N heart rate data sequences, the correction unit 48 performs a second extraction process to extract one or more heart rate interval data representing the heart rate interval of the heart rate during the target period in the first heart rate data sequence, for each of the multiple second division periods divided by a predetermined second time length. The second time length is longer than the first time length.

[0116] Next, the correction unit 48 performs a second correction process for each of the multiple second division periods. If, for each of the extracted heart rate interval data, one or more heart rate interval data with a low confidence interval value are included in a predetermined second proportion or more of the predetermined reference time, the correction unit 48 corrects the heart rate interval data with a low confidence interval value among the one or more extracted heart rate interval data. Then, the correction unit 48 performs a second confidence value update process, which calculates and updates the confidence value for each of the multiple heart rate interval data included in the first heart rate data column.

[0117] For example, as shown in Figure 9, suppose the measurement period is 30 seconds, the frame rate is 30 fps, and the first division period is 5 seconds. In this case, the correction unit 48 identifies multiple second division periods, each divided into 10-second intervals.

[0118] Furthermore, the correction unit 48 may perform a second error correction process by shifting the phase of the boundary positions of each of the multiple second division periods relative to the measurement period at intervals shorter than the second division period. That is, for each of the N heart rate data sequences, the correction unit 48 may shift the phase of the boundary positions of the second division periods relative to the measurement period at intervals shorter than the second division period, and perform a set of second extraction, second correction, and second confidence value update processes each time the phase is shifted.

[0119] For example, suppose the measurement period is 30 seconds, the frame rate is 30 fps, and the second division period is 10 seconds. In this case, as shown in Figure 9, the correction unit 48 sequentially shifts the delimiter position of the second division period backward by 1 second from the beginning of the measurement period, and executes a set of second extraction processing, second correction processing, and second confidence value update processing each time the delimiter position is shifted by 1 second.

[0120] In this way, the correction unit 48 performs a second error correction process after performing a first error correction process, thereby increasing the likelihood of correcting heart rate interval data whose confidence value is a low confidence interval value, and correcting N heart rate data sequences to include more accurate heart rate interval data.

[0121] Figure 10 is a diagram illustrating the first example of the first correction process.

[0122] Figure 10 shows an example in which five heart rate interval data points (T1, T2, T3, T4, and T5) arranged in time series are included in the first division period (e.g., 5 seconds). The correction unit 48 calculates the average value of the three heart rate interval data points with high confidence interval values ​​as the TA, for example, if there is an arrangement pattern in the first division period that includes a region in which three consecutive heart rate interval data points have high confidence interval values. For example, in the example in Figure 10, there is an arrangement pattern that includes regions T2, T3, and T4 in which three consecutive heart rate interval data points have high confidence interval values, so the correction unit 48 calculates the average value of T2, T3, and T4 as the TA.

[0123] The correction unit 48 then determines that the heart rate interval data included in the first division period, whose confidence value is a low confidence interval value, is correctable data if it falls within the range of TA±f. f represents a predetermined margin value.

[0124] In the example in Figure 10, T1 and T5 are heart rate interval data with low confidence interval values. Therefore, the correction unit 48 determines that heart rate interval data with low confidence interval values ​​can be corrected if each of T1 and T5 is within the range of TA±f. If the correction unit 48 determines that the heart rate interval data with low confidence interval values ​​(e.g., T1 and T5) is correctable data, it corrects each of T1 and T5 to TA.

[0125] Furthermore, if the heart rate interval data whose confidence value is a low confidence interval value is not within the range of TA±f, the correction unit 48 determines that correction is impossible and does not perform the correction process for T1 or T5.

[0126] By performing such processing, the correction unit 48 can perform correction processing according to predetermined rules, provided that the first division period includes heart rate interval data with a high confidence interval value in a predetermined arrangement pattern, and that heart rate interval data with a low confidence interval value can be corrected.

[0127] Figure 11 is a diagram illustrating a second example of the first correction process.

[0128] Figure 11 also shows an example in which the first segmented period contains five time-series heart rate interval data points (T1, T2, T3, T4, and T5). In the example in Figure 11, there is an arrangement pattern that includes regions of T1, T2, and T3 where three consecutive heart rate interval data points have a high confidence interval value. Therefore, the correction unit 48 calculates the average value of T1, T2, and T3 as the TA.

[0129] Furthermore, if the correction unit 48 contains two or more consecutive low-confidence regions within the first division period where the confidence value is the low-confidence interval value, it calculates the average value of the heart rate intervals in the low-confidence regions as the TNA.

[0130] The correction unit 48 then determines that the data is correctable if the TNA is within the range of TA±f. In the example in Figure 11, the correction unit 48 determines that T4 and T5 are correctable if (T4+T5) / 2=TNA is within the range of TA±f. If the heart rate interval data (e.g., T4 and T5) whose confidence value is a low confidence interval value is determined to be correctable data, the correction unit 48 corrects T4 and T5 to TNA.

[0131] Furthermore, if the correction unit 48 determines that correction is impossible if the TNA is outside the range of TA±f, it does not perform the T4 and T5 correction processes.

[0132] By performing such processing, the correction unit 48 can perform correction processing according to predetermined rules, provided that the first division period includes heart rate interval data with a high confidence interval value in a predetermined arrangement pattern, and that heart rate interval data with a low confidence interval value can be corrected.

[0133] Figure 12 is a diagram illustrating the first example of the second correction process.

[0134] Figure 12 shows an example in which 12 heart rate interval data points (T1 to T12) arranged in time series are included in the second division period (e.g., 10 seconds). The correction unit 48 recognizes, for example, that there are arrangement patterns in the second division period where there are two high-confidence regions where one or more heart rate interval data points have a confidence value within the high-confidence interval, but no region where three or more heart rate interval data points have a confidence value within the high-confidence interval. For example, the example in Figure 12 includes high-confidence regions for T5 and T6, and high-confidence regions for T10 and T11. In this case, the correction unit 48 calculates the average value of the heart rate interval data points with a confidence value within the high-confidence interval as the TA.

[0135] Furthermore, in this case, the correction unit 48 determines whether the time width of the region of two or more consecutive heart rate interval data points whose confidence value is a low confidence interval value matches the TA within an error range of a predetermined margin value. If they match, the correction unit 48 determines that two or more consecutive heart rate interval data points whose confidence value is a low confidence interval value are correctable data and replaces them with one new heart rate interval data point obtained by adding the two or more consecutive heart rate interval data points whose confidence value is a low confidence interval value. For example, in the example in Figure 12, the correction unit 48 replaces two consecutive heart rate interval data points T1 and T2 with a new heart rate interval data point T11. Also, the correction unit 48 replaces two consecutive heart rate interval data points T3 and T4 with a new heart rate interval data point T12.

[0136] Furthermore, the correction unit 48 determines whether, when heart rate interval data with a confidence value of a low confidence interval is divided into a continuous low confidence region, the heart rate intervals after the division match the average value of the heart rate interval data in the high confidence region with an error within a predetermined margin value. If the heart rate intervals obtained by dividing the low confidence region into a continuous low confidence region match the TA with an error within a predetermined margin value, the correction unit 48 determines that the heart rate interval data included in the low confidence region in which the heart rate intervals match the TA with an error within a predetermined margin value is correctable data. The correction unit 48 then replaces the correctable data with new heart rate interval data obtained by dividing the low confidence region into a continuous low confidence region. For example, the correction unit 48 replaces the heart rate interval data in the T7, T8, and T9 regions with new heart rate interval data in the T13, T14, T15, and T16 regions.

[0137] Furthermore, if multiple low-confidence regions exist discretely within the second division period, the correction unit 48 will not replace the regions that do not match the TA due to errors within a predetermined margin range even when divided equally with new heart rate interval data. For example, in the example in Figure 12, the correction unit 48 will not replace the T12 heart rate interval data with new heart rate interval data.

[0138] By performing such processing, the correction unit 48 can perform correction processing according to predetermined rules, provided that the second division period includes heart rate interval data with a high confidence interval value in a predetermined arrangement pattern, and that the heart rate interval data with a low confidence interval value can be corrected.

[0139] Figure 13 is a diagram illustrating a second example of the second correction process.

[0140] Figure 13 shows an example in which the second division period contains 12 heart rate interval data points (T1 to T12) arranged in time series. The correction unit 48 recognizes, for example, that within the second division period, there is one high-confidence region where three consecutive heart rate interval data points have a confidence value equal to the high-confidence interval, and another high-confidence region where one heart rate interval data point has a confidence value equal to the high-confidence interval. For example, the example in Figure 13 includes a high-confidence region for T3 to T5 and a high-confidence region for T10. In this case, the correction unit 48 calculates the average value of the heart rate interval data points with a confidence value equal to the high-confidence interval as the TA.

[0141] The correction unit 48 determines whether, when heart rate interval data with a low confidence interval value is divided into a continuous low confidence region, the resulting heart rate intervals match the average value of the heart rate interval data in the high confidence region with an error within a predetermined margin value. If the heart rate intervals obtained by dividing the low confidence region into equal parts match the TA with an error within a predetermined margin value, the correction unit 48 determines that the heart rate interval data included in the low confidence region where the heart rate intervals match the TA with an error within a predetermined margin value is correctable data. The correction unit 48 then replaces the correctable data with new heart rate interval data obtained by dividing the low confidence region into equal parts. For example, the correction unit 48 replaces the heart rate interval data in the T6, T7, T8, and T9 regions with new heart rate interval data in the T21, T22, T23, and T24 regions.

[0142] By performing such processing, the correction unit 48 can perform correction processing according to predetermined rules, provided that the second division period includes heart rate interval data with a high confidence interval value in a predetermined arrangement pattern, and that the heart rate interval data with a low confidence interval value can be corrected.

[0143] Figure 14 is a diagram illustrating a third example of the second correction process.

[0144] The example in Figure 14 includes nine heart rate interval data points (T1-T9) arranged in time series within a second division period (e.g., 10 seconds). The correction unit 48 identifies, for example, a configuration pattern in which there are two consecutive high-confidence regions (the T1 and T2 region, and the T8 and T9 region) within the second division period where two heart rate interval data points with high confidence interval values ​​are within the high confidence interval, but there are no consecutive high-confidence regions where three or more heart rate interval data points with high confidence interval values ​​are within the high confidence interval.

[0145] The correction unit 48 determines whether there is any heart rate interval data with a low confidence interval value that matches an integer multiple of the average value of the high confidence region with an error within a predetermined margin range. The correction unit 48 determines that heart rate interval data with a low confidence interval value that matches an integer multiple of the average value of the high confidence region with an error within a predetermined margin range is correctable data.

[0146] The correction unit 48 divides the heart rate intervals of such correctable data equally into a predetermined number of parts to generate new heart rate interval data. Then, the correction unit 48 replaces the correctable data with the new heart rate interval data.

[0147] For example, in the example shown in Figure 14, the correction unit 48 replaces the heart rate interval data for T3 with T31 ​​and T32. The correction unit 48 also replaces the heart rate interval data for T4 with T34 and T35.

[0148] By performing such processing, the correction unit 48 can perform correction processing according to predetermined rules, provided that the second division period includes heart rate interval data with a high confidence interval value in a predetermined arrangement pattern, and that the heart rate interval data with a low confidence interval value can be corrected.

[0149] Figure 15 shows an example of the arrangement of N corrected heart rate data sequences stored in the corrected data storage unit 52.

[0150] The association unit 50 stores the N heart rate data sequences after correction processing by the correction unit 48 as N corrected heart rate data sequences in the corrected data storage unit 52. In this case, the association unit 50 identifies each of the N corrected heart rate data sequences and stores them in the corrected data storage unit 52.

[0151] Furthermore, the association unit 50 associates sets of N heart rate interval data that are estimated to represent the heart rate intervals of heartbeats that occurred at the same time, which are included in the N corrected heart rate data sequences, and stores them in the corrected data storage unit 52. For example, the association unit 50 estimates that N heart rate interval data with the same rank from the beginning, included in the N corrected heart rate data sequences, represent the heart rate intervals of heartbeats that occurred at the same time, and associates them with each other. Alternatively, for example, the association unit 50 estimates that N heart rate interval data with elapsed time from the beginning within a predetermined time difference, included in the N corrected heart rate data sequences, represent the heart rate intervals of heartbeats that occurred at the same time, and associates them with each other.

[0152] In this embodiment, the correction data storage unit 52 stores N correction heart rate data sequences as two-dimensional data arranged in a matrix. In this case, as shown in Figure 15, the association unit 50 causes the correction data storage unit 52 to store N correction heart rate data sequences such that multiple heart rate interval data included in the same correction heart rate data sequence are stored in the same row of the matrix. Furthermore, the association unit 50 causes the correction data storage unit 52 to store N correction heart rate data sequences such that N heart rate interval data estimated to represent heartbeats that occurred at the same time are stored in the same column of the matrix.

[0153] The data determination unit 54 performs error correction processing on N corrected heart rate data sequences, which are two-dimensional data arranged in a matrix and stored in the corrected data storage unit 52, to generate a final heart rate data sequence. For each set of N heart rate interval data that are estimated to represent the heart rate interval at the same time contained in the N corrected heart rate data sequences, the data determination unit 54 generates the final heart rate interval data to be included in the final heart rate data sequence.

[0154] For example, the data determination unit 54 calculates a data column confidence value for each row in the matrix. That is, for each of the N corrected heart rate data columns stored in the corrected data storage unit 52, the data determination unit 54 calculates a data column confidence value based on the ratio of the number of heart rate interval data that are high-confidence interval values ​​(indicating that the data is in an interval with a confidence value above a certain threshold) to the total number of heart rate interval data included.

[0155] Furthermore, the data determination unit 54 calculates a heart rate confidence value for each column in the matrix. Specifically, for each of the N sets of heart rate interval data associated with representing the heart rate intervals of heartbeats that occurred at the same time, which are included in the N corrected heart rate data columns stored in the corrected data storage unit 52, the data determination unit 54 calculates a heart rate confidence value corresponding to the number of heart rate interval data whose confidence values ​​represent high confidence interval values.

[0156] Then, for each set of N heart rate interval data, the data determination unit 54 generates the final heart rate interval data to be included in the final heart rate data sequence, based on the heart rate confidence value and the data sequence confidence values ​​of each of the N corrected heart rate data sequences.

[0157] Figure 16 is a flowchart showing the processing flow of the data determination unit 54.

[0158] The data determination unit 54 processes the data according to the flow shown in Figure 16, based on the N corrected heart rate data sequences stored in the corrected data storage unit 52.

[0159] First, in S51, the data determination unit 54 calculates a data column confidence value for each of the N corrected heart rate data columns stored in the corrected data storage unit 52. For example, the data determination unit 54 calculates a data column confidence value for each row in the matrix.

[0160] For example, the data determination unit 54 calculates a data column confidence value for each of the N corrected heart rate data columns based on the ratio of the number of heart rate interval data with a high confidence interval value to the total number of heart rate interval data included. For example, the data column confidence value may be the number of heart rate interval data with a high confidence interval value. Alternatively, for example, the data column confidence value may be the value obtained by multiplying the ratio of the number of heart rate interval data with a high confidence interval value to the total number of heart rate interval data by a predetermined coefficient. Alternatively, for example, the data column confidence value may be expressed by discretizing the ratio of the number of heart rate interval data with a high confidence interval value to the total number of heart rate interval data at a predetermined number of levels, such as low, medium, or high.

[0161] Next, in S52, the data determination unit 54 calculates a heart rate confidence value for each of the N sets of heart rate interval data associated with each other, which are included in the N corrected heart rate data sequences stored in the corrected data storage unit 52 and represent the heart rate intervals of heartbeats that occurred at the same time. For example, the data determination unit 54 calculates a heart rate confidence value for each column in the matrix.

[0162] For example, the data determination unit 54 calculates a heart rate confidence value for each of the N sets of heart rate interval data associated with each other, which are included in the N corrected heart rate data sequences stored in the corrected data storage unit 52 and represent the heart rate intervals of heartbeats that occurred at the same time, according to the number of heart rate interval data whose confidence value represents a high confidence interval value. For example, the heart rate confidence value may be the number of heart rate interval data whose confidence value represents a high confidence interval value. Alternatively, the heart rate value may be expressed by discretizing the number of heart rate interval data whose confidence value represents a high confidence interval value at a predetermined number of levels, such as low, medium, or high.

[0163] Next, in S53, the data determination unit 54 generates the final heart rate interval data to be included in the final heart rate data sequence for each of the N sets of heart rate interval data associated to represent the heart rate intervals of heartbeats that occurred at the same time, based on the heart rate confidence value and the data sequence confidence values ​​of each of the N corrected heart rate data sequences.

[0164] Next, in S54, the data determination unit 54 outputs a final heart rate data sequence that includes the generated multiple final heart rate interval data.

[0165] When the data determination unit 54 finishes processing S54, it terminates this flow.

[0166] Figure 17 is a flowchart showing an example of the flow of the final heart rate interval data generation process (S53) by the data determination unit 54. In the final heart rate interval data generation process (S53) of S53, the data determination unit 54 executes the process in the flow shown in Figure 17, for example.

[0167] For each set of N heart rate interval data associated with representing the heart rate intervals of heartbeats occurring at the same time, the data determination unit 54 executes the processes from S62 to S67 (loop processing between S61 and S68).

[0168] First, in S62, the data determination unit 54 determines whether the heart rate confidence value calculated for the N sets of heart rate interval data to be processed is equal to or greater than a predetermined reference heart rate confidence value.

[0169] If the data determination unit 54 determines that the heart rate confidence value is equal to or greater than the reference heart rate confidence value (Yes in S62), it proceeds to process S63. If the data determination unit 54 determines that the heart rate confidence value is not equal to or greater than the reference heart rate confidence value (No in S62), it proceeds to process S64.

[0170] In S63, the data determination unit 54 determines the corresponding final heart rate interval data to be the average of 1 or more heart rate interval data with a high confidence interval value, which are included in the set of N heart rate interval data to be processed. After completing the processing in S63, the data determination unit 54 proceeds to S68.

[0171] In S64, the data determination unit 54 determines whether the set of N heart rate interval data to be processed contains any heart rate interval data with a confidence value of 1 or more that represents a high confidence interval value.

[0172] If the data determination unit 54 determines that the set of N heart rate interval data to be processed contains at least one heart rate interval data with a confidence value of 1 or greater that represents a high confidence interval value (Yes in S64), it proceeds to S65. If the data determination unit 54 determines that the set of N heart rate interval data to be processed does not contain at least one heart rate interval data with a confidence value of 1 or greater that represents a high confidence interval value (No in S64), it proceeds to S67.

[0173] In S65, the data determination unit 54 determines whether any of the N sets of heart rate interval data to be processed, where one or more heart rate interval data have a confidence value that represents a high confidence interval value, are included in a corrected heart rate data sequence whose data sequence confidence value is equal to or greater than a predetermined reference data sequence confidence value.

[0174] If the data determination unit 54 finds that any of the N sets of heart rate interval data to be processed, one or more, whose confidence value represents a high confidence interval value, is included in a corrected heart rate data sequence whose data sequence confidence value is equal to or greater than the reference data sequence confidence value (Yes in S65), the processing proceeds to S66. If the data determination unit 54 finds that any of the N sets of heart rate interval data to be processed, one or more, whose confidence value represents a high confidence interval value, is not included in a corrected heart rate data sequence whose data sequence confidence value is equal to or greater than the reference data sequence confidence value (No in S65), the processing proceeds to S67.

[0175] In S66, the data determination unit 54 determines the corresponding final heart rate interval data to be the heart rate interval data included in the corrected heart rate data sequence with the largest data sequence confidence value among the one or more heart rate interval data whose confidence value represents a high confidence interval value within the set of N heart rate interval data to be processed. If there are multiple corrected heart rate data sequences with the largest data sequence confidence value, the data determination unit 54 may determine the corresponding final heart rate interval data to be the average of the multiple heart rate interval data included in the corrected heart rate data sequence with the largest data sequence confidence value. After completing the processing in S66, the data determination unit 54 proceeds to processing in S68.

[0176] In S67, the data determination unit 54 uses the corresponding final heart rate interval data as information indicating that no heartbeat was detected. After completing the processing in S67, the data determination unit 54 proceeds to processing in S68.

[0177] The data determination unit 54 exits the loop processing from S61 to S68 when it has executed the processes from S62 to S67 for all N sets of heart rate interval data associated with each other as representing the heart rate intervals of heartbeats that occurred at the same time, i.e., for all columns. The correction unit 48 terminates this flow when it has finished the loop processing from S61 to S68.

[0178] By performing the above processing, the data determination unit 54 can generate a final heart rate data sequence based on the heart rate confidence value for each set of N heart rate interval data associated with each other as representing the heart rate intervals of heartbeats that occurred at the same time, and the data sequence confidence value for each of the N corrected heart rate data sequences. In this way, since the data determination unit 54 generates a final heart rate data sequence based on N heart rate data sequences generated in different ways, it can generate a highly accurate final heart rate data sequence that removes disturbance components caused by the movement of the person being measured, etc.

[0179] Figure 18 shows the arrangement of N corrected heart rate data sequences stored in the corrected data storage unit 52, and an example of the final heart rate data sequence.

[0180] For example, as shown in Figure 18, the data determination unit 54 calculates a data sequence confidence value for each of the N corrected heart rate data sequences, representing either low reliability, medium reliability, or high reliability. For example, as shown in Figure 18, the data determination unit 54 calculates a heart rate confidence value for each set of N heart rate interval data associated to represent the heart rate intervals of heartbeats that occurred at the same time, representing either low reliability, medium reliability, or high reliability. High reliability represents higher reliability than medium reliability; for example, the number of heart rate interval data where the confidence value is a high confidence interval value is greater than that for medium reliability. Medium reliability represents higher reliability than low reliability; for example, the number of heart rate interval data where the confidence value is a high confidence interval value is greater than that for low reliability.

[0181] In the example in Figure 18, the underlined values ​​represent heart rate interval data where the confidence value is a high confidence interval value.

[0182] For example, in the final heart rate data sequence in Figure 18, the set of N heart rate interval data (T12, T22, T32, T42, T52) associated with the second heart rate has a heart rate confidence value that represents high reliability, and is therefore equal to or greater than the predetermined reference heart rate confidence value (e.g., medium reliability). Accordingly, the data determination unit 54 determines the second final heart rate interval data (T ELet it be the average value of the R-R interval data (T12, T22, T32, T42, T52) with high confidence values among the N sets of R-R interval data (T12, T22, T32, T42, T52) associated with the second heartbeat.

[0183] Also, in the final heartbeat data sequence of FIG. 18, the N sets of R-R interval data (T13, T23, T33, T43, T53) associated with the third heartbeat have a heartbeat confidence value representing medium reliability, so they are equal to or higher than the reference heartbeat confidence value (for example, medium reliability). Therefore, the data determination unit 54 uses the third final R-R interval data (T E 3) as the average value of the R-R interval data (T23, T33, T43) with high confidence values among the N sets of R-R interval data (T13, T23, T33, T43, T53) associated with the third heartbeat.

[0184] Also, in the final heartbeat data sequence of FIG. 18, the N sets of R-R interval data (T11, T21, T31, T41, T51) associated with the first heartbeat have a heartbeat confidence value representing low reliability, so they are not equal to or higher than the reference heartbeat confidence value (for example, medium reliability). Furthermore, the N sets of R-R interval data (T11, T21, T31, T41, T51) associated with the first heartbeat include one or more R-R interval data (T11, T41) with high confidence values. Also, among the one or more R-R interval data (T11, T41) with high confidence values, T41 is included in the data sequence confidence value that is equal to or higher than a predetermined reference data sequence confidence value (for example, high reliability). Therefore, the data determination unit 54 uses the first final R-R interval data (T E 1) as the R-R interval data (T41).

[0185] Furthermore, for example, the set of N heart rate interval data (T1n, T2n, T34, T4n, T5n) associated with the nth heart rate in the final heart rate data sequence has a heart rate confidence value that represents low reliability, and therefore is not equal to or greater than the reference heart rate confidence value (e.g., medium reliability). Moreover, the set of N heart rate interval data (T1n, T2n, T34, T4n, T5n) associated with the nth heart rate does not include any heart rate interval data whose confidence value represents a high confidence interval value. Therefore, the data determination unit 54 determines the nth final heart rate interval data (T E n) is the information indicating that a heartbeat could not be detected.

[0186] As described above, the heart rate detection device 24 according to this embodiment performs error correction processing for each of the N heart rate data sequences. As a result, the heart rate detection device 24 can accurately generate the final heart rate data sequence representing the subject's heart rate from a heart rate signal that includes disturbance components caused by the subject's movement, etc.

[0187] Furthermore, the heart rate detection device 24 according to this embodiment generates final heart rate interval data representing the heart rate interval of the corresponding heartbeat for each set of N heart rate interval data that are estimated to represent the heart rate interval of the same heartbeat, based on the confidence value of each of the N heart rate interval data. As a result, the heart rate detection device 24 can accurately generate the final heart rate data sequence using highly reliable heart rate interval data.

[0188] Furthermore, the heart rate detection device 24 according to this embodiment generates a final heart rate data sequence based on N heart rate data sequences generated using different methods. This allows the heart rate detection device 24 to remove various disturbance components and generate a highly accurate final heart rate data sequence.

[0189] Figure 19 shows the hardware configuration of the information processing device. The heart rate detection device 24 is implemented, for example, by a device with a hardware configuration similar to that of a general information processing device, as shown in Figure 19. The information processing device comprises a CPU (Central Processing Unit) 201, an operating device 202, a main memory 203, an auxiliary memory 204, a communication device 205, and a bus 206. Each part is connected by the bus 206.

[0190] The CPU 201 uses a predetermined area of ​​the main memory 203 as a working area and, in cooperation with various programs pre-stored in the auxiliary memory 204, etc., executes various processes and comprehensively controls the operation of each part that constitutes the heart rate detection device 24. In addition, the CPU 201 operates the operating device 202 and the communication device 205, etc., in cooperation with the programs.

[0191] The operating device 202 is an input device such as a touch panel, mouse, or keyboard, which receives information input from the user as an instruction signal and outputs that instruction signal to the CPU 201.

[0192] The main memory 203 is a volatile storage medium such as SDRAM (Synchronous Dynamic Random Access Memory). The main memory 203 functions as a workspace for the CPU 201.

[0193] The auxiliary storage device 204 is a rewritable recording device such as a semiconductor storage medium like flash memory, or a magnetically or optically recordable storage medium. The auxiliary storage device 204 stores the program used for control. The communication device 205 transmits and receives data with other devices.

[0194] The program executed by the heart rate detection device 24 may be stored on a computer connected to a network such as the Internet and provided by downloading it via the network. Alternatively, the program executed by the heart rate detection device 24 may be pre-installed on a portable storage medium or the like and provided in that form.

[0195] The program executed by the heart rate detection device 24 has a modular configuration including a heart rate signal generation module, a heart rate data sequence generation module, and a final data sequence generation module. The final data sequence generation module includes an acquisition module, a confidence value addition module, a correction module, an association module, and a data determination module. The CPU 201 reads such a program from a storage medium or the like and loads each of the above modules into the main memory 203. Then, by executing such a program, the CPU 201 functions as a heart rate signal generation unit 32, a heart rate data sequence generation unit 34, and a final data sequence generation unit 36 ​​including an acquisition unit 42, a confidence value addition unit 46, a correction unit 48, an association unit 50, and a data determination unit 54. Note that some or all of the heart rate signal generation unit 32, the heart rate data sequence generation unit 34, and the final data sequence generation unit 36 ​​may be configured by hardware. Furthermore, by executing such a program, the CPU 201 causes the main memory 203 and the auxiliary memory 204 to function as a data sequence storage unit 44 and a corrected data storage unit 52.

[0196] Although embodiments of the present invention have been described above, these embodiments are presented as examples only and are not intended to limit the scope of the invention. Various modifications can be made to the embodiments. [Explanation of Symbols]

[0197] 10 Heart rate detection system 22 Sensor device 24 Heart rate detection device 26 Display device 32 Heart rate signal generation unit 34 Heart rate data sequence generation unit 36 Final Data Column Generation Unit 42 Acquisition Department 44 Data Column Storage Unit 46. ​​Confidence Value Addition Section 48 Correction Section 50 Association section 52 Correction Data Storage Unit 54 Data Determination Unit

Claims

1. An acquisition unit that acquires N heart rate data sequences (where N is an integer of 2 or more) that represent the time change in the subject's heart rate interval during the measurement period, generated using different methods from each other. A correction unit that performs error correction processing for each of the N heart rate data sequences, A data determination unit generates a final heart rate data sequence representing the time change in the heart rate interval of the person being measured during the measurement period, based on the N heart rate data sequences. Equipped with, The data determination unit generates the final heart rate interval data included in the final heart rate data sequence for each set of N heart rate interval data that are estimated to represent the same heart rate interval at the same time in the N heart rate data sequences. Heart rate detection device.

2. Each of the N heart rate data sequences includes a plurality of heart rate interval data, each representing a heart rate interval arranged in time series, and a plurality of confidence values ​​corresponding to the plurality of heart rate interval data. Each of the aforementioned multiple confidence values ​​represents the reliability of the corresponding heart rate interval data among the aforementioned multiple heart rate interval data, The aforementioned final heart rate data sequence includes multiple final heart rate interval data, each representing a heart rate interval, arranged in chronological order. The data determination unit, For each of the N heart rate data sequences, a data sequence confidence value representing reliability is calculated based on the multiple confidence values. For each of the N sets of heart rate interval data, based on the confidence value of each of the N heart rate interval data and the data column confidence value for each of the N heart rate data columns, a final heart rate interval data representing the heart rate interval of the heart rate included in the final heart rate data column is generated. The heart rate detection device according to claim 1.

3. It also includes a confidence value addition section, At least one of the N heart rate data sequences is an uncalculated heart rate data sequence that does not include the plurality of confidence values. The confidence value addition unit, when the N heart rate data sequences include a sequence of uncalculated heart rate data, calculates the confidence value for each of the multiple heart rate interval data included in the sequence of uncalculated heart rate data, and adds the calculated confidence value to the sequence of uncalculated heart rate data, corresponding to each of the multiple heart rate interval data included. The heart rate detection device according to claim 2.

4. The confidence value addition unit, for each of the multiple heart rate interval data included in the uncalculated heart rate data sequence, sets the confidence value to a high confidence interval value indicating that the target heart rate interval data is data within the reliability interval of the specified interval, if the absolute value of the difference between the target heart rate interval data and the average value of the multiple heart rate interval data is less than or equal to a preset margin value, and sets the confidence value to a low confidence interval value indicating that the target heart rate interval data is data within the reliability interval of the specified interval, if the absolute value is greater than the margin value. The heart rate detection device according to claim 3.

5. The system further comprises a data sequence storage unit that stores the N heart rate data sequences. The heart rate detection device according to claim 1.

6. The correction unit performs a first error correction process for each of the N heart rate data sequences. When the first error correction process is performed on the first heart rate data sequence among the N heart rate data sequences, the correction unit performs the following: For each of the multiple first division periods obtained by dividing the measurement period into predetermined first time lengths, a first extraction process is performed to extract one or more heart rate interval data representing the heart rate interval of the heart rate during the target period in the first heart rate data sequence. For each of the plurality of first division periods, if the extracted heart rate interval data includes, in a predetermined first proportion or more of a predetermined standard time, heart rate interval data whose confidence value is a low confidence interval value indicating that the data is from an interval with a reliability lower than the standard, then a first correction process is performed to correct the heart rate interval data among the extracted heart rate interval data whose confidence value is the low confidence interval value. The first confidence value update process is executed to calculate and update the confidence value for each of the plurality of heart rate interval data included in the first heart rate data sequence. The heart rate detection device according to claim 2.

7. In the first correction process, the correction unit, For each of the aforementioned plurality of first division periods, If, among the one or more extracted heart rate interval data, there are heart rate interval data whose confidence value is a high-confidence interval value indicating that the data is for an interval with a reliability of above the standard, in a predetermined proportion or greater of the predetermined standard time, then no correction process is performed on any of the one or more extracted heart rate interval data. If none of the extracted heart rate interval data (one or more) contains any heart rate interval data where the confidence value is the high confidence interval value in any of the predetermined arrangement patterns (one or more), then no correction process is performed on any of the extracted heart rate interval data (one or more). If the extracted one or more heart rate interval data includes heart rate interval data where the confidence value is the high confidence interval value in any of the one or more arrangement patterns, Furthermore, for each of the heart rate interval data included in the extracted one or more heart rate interval data, whose confidence value is the low confidence interval value, it is determined whether the absolute value of the difference between the heart rate interval after performing a correction process according to a predetermined rule and the average value of the heart rate interval data whose confidence value is the high confidence interval value is less than or equal to a predetermined margin value, and whether the data is correctable. No correction process is performed on the heart rate interval data that is determined not to be correctable data. The heart rate interval data that has been determined to be correctable data is subjected to correction processing according to the predetermined rules. The heart rate detection device according to claim 6.

8. The correction unit executes a first repetitive control process for each of the N heart rate data sequences, shifting the phase of the positions of the divisions of the plurality of first division periods relative to the measurement period, and then executing the set of the first extraction process, the first correction process, and the first confidence value update process. The heart rate detection device according to claim 6.

9. The correction unit performs a second error correction process for each of the N heart rate data sequences. When the second error correction process is performed on the first heart rate data sequence, the correction unit performs the following: For each of the multiple second division periods obtained by dividing the measurement period into predetermined second division periods that are longer than the first division period, a second extraction process is performed to extract one or more heart rate interval data representing the heart rate interval of the heart rate during the target period in the first heart rate data sequence. For each of the aforementioned multiple second division periods, if the extracted one or more heart rate interval data contains a predetermined second proportion of heart rate interval data whose confidence value is the low confidence interval value relative to a predetermined reference time, a second correction process is performed to correct the heart rate interval data among the extracted one or more heart rate interval data whose confidence value is the low confidence interval value. A second confidence value update process is performed to calculate and update the confidence value for each of the plurality of heart rate interval data included in the first heart rate data sequence. The heart rate detection device according to claim 6.

10. The association unit further includes a unit that associates N sets of heart rate interval data, which are estimated to represent the heart rate intervals of heartbeats that occurred at the same time and are included in the N heart rate data sequences, identifies each of the N corrected heart rate data sequences, and stores the N heart rate data sequences as N corrected heart rate data sequences in the corrected data storage unit. Each of the N corrected heart rate data sequences includes the plurality of heart rate interval data and the plurality of confidence values, The data determination unit generates the final heart rate interval data included in the final heart rate data column for each set of N heart rate interval data that is estimated to represent the heart rate interval of the same heartbeat included in the N corrected heart rate data columns, based on the confidence value of each of the N heart rate interval data and the data column confidence value for each of the N heart rate data columns. The heart rate detection device according to claim 2.

11. The data determination unit, For each of the N corrected heart rate data sequences stored in the corrected data storage unit, the data sequence confidence value is calculated based on the ratio of the number of heart rate interval data that are high-confidence interval values, representing data within an interval with a confidence value equal to or greater than the standard, to the total number of heart rate interval data included. For each of the N sets of heart rate interval data included in the N corrected heart rate data sequences stored in the corrected data storage unit, which are associated to represent the heart rate intervals of heartbeats that occurred at the same time, a heart rate confidence value is calculated according to the number of heart rate interval data included whose confidence value represents the high confidence interval value. The heart rate detection device according to claim 10.

12. The data determination unit, For each of the N sets of heart rate interval data, the final heart rate interval data included in the final heart rate data column is generated based on the heart rate confidence value and the data column confidence values ​​of each of the N corrected heart rate data columns. The heart rate detection device according to claim 11.

13. For each of the N sets of heart rate interval data associated with each other as representing the heart rate intervals of heartbeats occurring at the same time, the data determination unit performs the following: If the aforementioned heart rate confidence value is equal to or greater than a predetermined reference heart rate confidence value, the corresponding final heart rate interval data is set to the average value of one or more heart rate interval data included in the set of N heart rate interval data, the confidence value of which is the high confidence interval value. If the heart rate confidence value is not equal to or greater than the reference heart rate confidence value, and the set of N heart rate interval data includes one or more heart rate interval data where the confidence value represents the high confidence interval value, and any one of the one or more heart rate interval data where the confidence value represents the high confidence interval value is included in a corrected heart rate data sequence whose data sequence confidence value is equal to or greater than a predetermined reference data sequence confidence value, then the corresponding final heart rate interval data is set to be the heart rate interval data included in the corrected heart rate data sequence with the largest data sequence confidence value among the one or more heart rate interval data where the confidence value represents the high confidence interval value. The heart rate detection device according to claim 12.

14. For each of the N sets of heart rate interval data associated with each other as representing the heart rate intervals of heartbeats occurring at the same time, the data determination unit performs the following: If the aforementioned heart rate confidence value is not equal to or greater than the aforementioned reference heart rate confidence value, and the set of N heart rate interval data does not contain one or more heart rate interval data where the confidence value represents the high confidence interval value, the corresponding final heart rate interval data shall be used as information indicating that a heart rate could not be detected. If the heart rate confidence value is not equal to or greater than the reference heart rate confidence value, and none of the one or more heart rate interval data in the set of N heart rate interval data whose confidence value represents the high confidence interval value are included in the corrected heart rate data column whose data column confidence value is equal to or greater than the reference data column confidence value, then the corresponding final heart rate interval data shall be treated as information indicating that a heart rate could not be detected. The heart rate detection device according to claim 13.

15. A sensor device that outputs a sensor signal containing components of the subject's heart rate, A heart rate signal generation unit generates N heart rate signals representing the heart rate of the person being measured, based on the sensor signal output from the sensor device. A heart rate data sequence generation unit generates N heart rate data sequences (where N is an integer of 2 or more) that represent the time change in the heart rate interval of the subject during the measurement period, each sequence being generated in a different manner based on the aforementioned N heart rate signals. A correction unit that performs error correction processing for each of the N heart rate data sequences, A final data sequence generation unit generates a final heart rate data sequence that represents the time change in the heart rate interval of the person being measured during the measurement period, based on the N heart rate data sequences. Equipped with, The final data sequence generation unit generates the final heart rate interval data included in the final heart rate data sequence for each set of N heart rate interval data that are estimated to represent the same heart rate interval at the same time included in the N heart rate data sequences. Heart rate detection system.

16. The information processing device obtains N heart rate data sequences (where N is an integer of 2 or more) that represent the time change in the subject's heart rate interval during the measurement period, each generated using a different method. The information processing device performs error correction processing on each of the N heart rate data sequences. The information processing device generates a final heart rate data sequence representing the time change in the heart rate interval of the person being measured during the measurement period, based on the N heart rate data sequences. In generating the final heart rate data sequence, the information processing device generates the final heart rate interval data to be included in the final heart rate data sequence for each set of N heart rate interval data that is estimated to represent the heart rate interval at the same time in the N heart rate data sequences. Heart rate detection method.

17. A program that makes a computer function as a heart rate detection device, The aforementioned computer, An acquisition unit that acquires N heart rate data sequences (where N is an integer of 2 or more) that represent the time change in the subject's heart rate interval during the measurement period, generated using different methods from each other. A correction unit that performs error correction processing for each of the N heart rate data sequences, A data determination unit generates a final heart rate data sequence representing the time change in the heart rate interval of the person being measured during the measurement period, based on the N heart rate data sequences. and make it work The data determination unit generates the final heart rate interval data included in the final heart rate data sequence for each set of N heart rate interval data that are estimated to represent the same heart rate interval at the same time in the N heart rate data sequences. program.

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