Biological signal measuring device

Abstract

To provide information for notifying a user of an appropriate charging timing in a wearable-type biological signal measuring device in which the number of channels to be activated can be dynamically switched.SOLUTION: A wearable-type biological signal measuring device that is capable of measuring the biological signal of a plurality of channels and driven by a battery, includes: an operation mode switching part which can switch between a first operation mode for measuring the biological signal of the plurality of channels by activating the plurality of channels and a second operation mode for measuring the biological signal of a part of the channels by activating the part of the channels; a battery remaining amount acquiring part for acquiring the information of battery remaining amount of the battery; a prediction part for predicting an operable time of the biological signal measuring device based on the consumption power in each of the operation mode and the battery remaining amount; and an output part for outputting the information of the predicted value of the operable time.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a wearable type biosignal measuring device. [Background technology]

[0002] Wearable biosignal measuring devices are known that are worn on the body continuously for long periods of time to monitor biosignals. For example, there are various products, ranging from medical devices such as 24-hour Holter ECG monitors to consumer devices such as smart watches and life loggers. This type of device has the restriction that it cannot measure biosignals while charging because it needs to be removed from the body when charging the built-in battery. Although it is not necessary to continue measuring for 24 hours, there is a need to reduce the time when measurement is not possible due to charging and the number of times charging is required as much as possible. In addition, it is undesirable that measurement is interrupted for a long period of time due to a dead battery.

[0003] Patent Document 1 discloses a wearable electrocardiograph that is worn on the upper arm to measure ECG (Electrocardiogram) signals. This electrocardiograph is also powered by a built-in battery, but does not take into consideration the above-mentioned charging issue. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2005 / 027720 Summary of the Invention [Problem to be solved by the invention]

[0005] Some conventional products have a function to show the remaining battery level by displaying a percentage or an icon, etc. However, even if the remaining battery level is known, the user cannot imagine how many hours the device can be used (how long it can continue measuring), making it difficult to determine the appropriate time to charge it.

[0006] In developing a measurement device capable of measuring biosignals from multiple channels, the inventors are considering dynamically switching the number of active channels (channels performing measurements) depending on the quality of the signals being measured, the user's condition, etc. In the case of such a measurement device, the power consumption changes depending on the number of active channels, so there is a concern that it will become even more difficult for the user to determine the appropriate charging timing for themselves.

[0007] The present invention has been made in consideration of the above-mentioned situation, and aims to provide information to inform a user of the appropriate timing for charging in a wearable type biosignal measuring device that can dynamically switch the number of active channels. [Means for solving the problem]

[0008] The present disclosure includes a wearable type biosignal measuring device capable of measuring biosignals of multiple channels and powered by a battery, the biosignal measuring device having an operation mode switching unit capable of switching between a first operation mode in which the multiple channels are activated to measure the biosignals of the multiple channels and a second operation mode in which only some of the channels are activated to measure the biosignals of the some of the channels, a battery remaining capacity acquisition unit that acquires information about the remaining battery capacity of the battery, a prediction unit that predicts the operational time of the biosignal measuring device based on the power consumption in each operation mode and the remaining battery capacity, and an output unit that outputs information about the predicted operational time.

[0009] The prediction unit may predict a first operational time if the device continues to operate in the first operation mode from the power consumption in the first operation mode and the remaining battery charge, and may predict a second operational time if the device continues to operate in the second operation mode from the power consumption in the second operation mode and the remaining battery charge, and the output unit may output the first operational time and the second operational time as a minimum and maximum predicted values ​​of the operational time.

[0010] The output unit may determine whether charging is necessary based on the predicted value of the operable time, and notify a user when charging is necessary.

[0011] The output unit may control timing of the notification so that the notification is made during a time period when the user is able to charge the device.

[0012] The output unit may determine that the user has returned home when the current time passes a preset time, and may perform the notification.

[0013] The output unit may determine a time period during which the user is at home based on schedule information of the user obtained from an external device, and may perform the notification during the time period during which the user is at home.

[0014] The output unit may estimate a time period during which the user can charge the battery based on charging history information that records times when charging was performed in the past, and may make the notification during the estimated time period during which charging is possible.

[0015] The output unit may determine whether or not the user is at home based on location information of the user, and may perform the notification when it is determined that the user is at home.

[0016] The output unit may notify the user by at least one of sound, vibration, light, and electrical stimulation.

[0017] The output section may have an alarm device that notifies the user by light, and the alarm device may be disposed in a position visible to the user wearing the biosignal measuring device.

[0018] The output unit may acquire information on the current time and information on the time period during which the user is expected to be able to charge the next day, and determine that charging is necessary today if the predicted time when the biosignal measuring device will stop operating, calculated from the current time and the operable time, arrives before the time period during which charging is available the next day.

[0019] The prediction unit may predict a proportion of future operation time for each of the first operation mode and the second operation mode, and calculate the operable time based on the proportion of future operation time for each operation mode, the power consumption in each operation mode, and the remaining battery capacity.

[0020] The prediction unit may analyze time-series data of a biological signal measured in the past, and predict a future proportion of the operation time of each of the operation modes based on the analysis result.

[0021] The prediction unit may analyze the state of the waveform in time series data of a biological signal measured in the past, divide the waveform into clean sections where the quality of the waveform is above a predetermined standard and noisy sections where the quality of the waveform is worse than the predetermined standard, predict the proportion of future operation time in the first operation mode from the proportion of the noisy sections, and predict the proportion of future operation time in the second operation mode from the proportion of the clean sections.

[0022] The prediction unit may analyze the state of the waveform in time series data of the biological signal measured in the past, thereby dividing the waveform into clean sections where the quality of the waveform is above a predetermined standard and noisy sections where the quality of the waveform is worse than the predetermined standard, and further divide the clean sections into abnormal waveform sections where an abnormal waveform appears and normal waveform sections where the abnormal waveform does not appear, predict the proportion of future operating time in the first operating mode from the proportion of the noisy sections and the abnormal waveform sections, and predict the proportion of future operating time in the second operating mode from the proportion of the normal waveform sections.

[0023] The biological signal may be an ECG (Electrocardiogram) signal.

[0024] The present invention may be understood as a biosignal measuring device having at least a part of the above configuration, or as an electrocardiogram measuring device that measures an ECG signal as a biosignal. The present invention may also be understood as a charging information providing method including at least a part of the above processing, a control method for a biosignal measuring device, or a program for realizing such a method or a recording medium on which the program is non-temporarily recorded. Note that the above configurations and processing can be combined with each other as much as possible to constitute the present invention. Effect of the Invention

[0025] According to the present invention, in a wearable type biosignal measuring device capable of dynamically switching the number of active channels, it is possible to provide information to inform a user of the appropriate timing for charging. [Brief description of the drawings]

[0026] [Figure 1] FIG. 1 shows a biosignal measuring device worn on the upper arm. [Diagram 2] FIG. 2 is a plan view of the biosignal measuring device. [Diagram 3] FIG. 3 is a perspective view of the biosignal measuring device. [Figure 4] FIG. 4 is a block diagram showing the hardware configuration of the biosignal measuring device. [Diagram 5] FIG. 5 is a block diagram showing the functional configuration of the control main body. [Figure 6] FIG. 6 is a flowchart showing the flow of the measurement process of the ECG signal. [Figure 7] FIG. 7 is a diagram showing examples of operation modes and active channels. [Figure 8] FIG. 8 is a diagram for explaining the waveform of an ECG signal and heart rate information. [Figure 9] FIG. 9 is a diagram for explaining the relationship between signal quality, operation mode, and power consumption. [Figure 10]FIG. 10 is a flowchart showing the flow of the operation available time prediction process in the first embodiment. [Figure 11] FIG. 11 is a diagram showing an example of the remaining operation time display screen. [Figure 12] FIG. 12 is a flowchart showing the flow of the process of predicting the operable time in the second embodiment. [Figure 13] FIG. 13 is a flowchart showing the flow of the notification process in the third embodiment. [Figure 14] FIG. 14 is a flowchart showing the flow of the notification process in the fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] <Application Examples> An application example of the present invention will be described with reference to FIG.

[0028] The biosignal measuring device 1 is a wearable type measuring device capable of measuring a biosignal of a user. The biosignal to be measured is, for example, an electrocardiogram signal (a minute electric signal accompanying a heartbeat). These include electromyography (microelectrical signals associated with muscle activity), electroencephalography (microelectrical signals associated with brain activity), pulse waves, and blood pressure.

[0029] During measurement, the user wraps the band 10 around a measurement site to wear the biosignal measuring device 1. Examples of measurement sites to which the band 10 is worn include the upper limbs (upper arm, forearm, wrist, hand, finger), lower limbs (thigh, lower leg, ankle, foot, finger), head, neck, chest, abdomen, earlobe, etc., and are appropriately selected depending on the type of biosignal to be measured, the measurement algorithm, etc.

[0030] The biosignal measuring device 1 has an operation mode switching function that can switch between a first operation mode in which multiple channels are activated to measure biosignals of multiple channels, and a second operation mode in which only some channels are activated to measure biosignals of some channels. For example, when highly accurate or reliable measurement is required, the device operates in the first operation mode to collect as much data as possible, and when sufficient measurement accuracy is possible even with a small number of channels, the device operates in the second operation mode to reduce power consumption.

[0031] The most basic configuration is that the first operation mode is a mode in which all channels are used (also called multi-channel mode), and the second operation mode is a mode in which only one channel is used (also called single-channel mode). However, this configuration is not limited, and the number of channels to be active in each operation mode may be set arbitrarily. For example, if the total number of channels possessed by the biosignal measuring device 1 is N, the number of active channels in the first operation mode is n1, and the number of active channels in the second operation mode is n2, then: N ≥ n1 > n2 ≥ 1 Also, third, fourth, etc. operation modes having a different number of active channels from the first and second operation modes may be provided.

[0032] The biosignal measuring device 1 is configured to operate continuously for several days to several weeks with the battery fully charged, and is basically intended to be used in daily life with the device 1 always attached and to monitor biosignals 24 hours a day. Since the device 1 must be removed from the body only when charging the battery, it is desirable to charge the device as few times as possible to minimize the gap in the measurement period. However, if the battery runs out while refraining from charging and in a situation where charging is not possible, such as when the user is out or at work, measurement cannot be resumed until charging is performed when the user returns home, resulting in a long gap in measurement. Some general wearable devices show the remaining battery level using a percentage display or an icon display, but it is difficult to grasp how much time measurement can be performed (i.e., how much longer it is necessary to charge) using the percentage display or icon display. In particular, in the case of a device that can dynamically switch operation modes as in the present invention, the amount of power consumed changes depending on how the operation mode is switched after this, so it is difficult for the user to determine the appropriate charging timing by himself.

[0033] Therefore, the biosignal measuring device 1 predicts the available operation time of the biosignal measuring device 1 based on the power consumption and the remaining battery capacity in each operation mode, and outputs information on the predicted value of the available operation time. Furthermore, it may determine whether charging is necessary based on the predicted value of the available operation time, and if charging is necessary, notify the user at an appropriate timing by means of sound, vibration, light, electrical stimulation, or the like.

[0034] For example, the biosignal measuring device 1 may predict a first operable time when the device continues to operate in the first operation mode from the power consumption and the remaining battery charge in the first operation mode, and may predict a second operable time when the device continues to operate in the second operation mode from the power consumption and the remaining battery charge in the second operation mode. The first operable time corresponds to the operable time when the power consumption is estimated to be the highest, and the second operable time corresponds to the operable time when the power consumption is estimated to be the lowest. If the first and second operable times are presented as the minimum and maximum values ​​of the predicted operable times, the user can easily plan when to charge the device since the user knows that charging should be performed within the time span of the presented predicted values.

[0035] Alternatively, the biosignal measuring device 1 may predict the future proportion of the operation time of each of the first and second operation modes, and calculate the available operation time based on the future proportion of the operation time of each operation mode and the power consumption and remaining battery capacity in each operation mode. By predicting the future proportion of the operation time of each operation mode and estimating the available operation time, the available operation time can be presented taking into account actual use. This allows the user to determine the appropriate timing for charging. Note that the prediction of the operation time proportion may be performed by any method, but for example, time-series data of biosignals measured in the past may be analyzed, and the future proportion of the operation time of each operation mode may be predicted based on the analysis results. By analyzing data measured in the past, it is possible to grasp how each operation mode was switched during the actual use of the device 1 by the user, so that the available operation time can be estimated with high accuracy.

[0036] In the following, a specific configuration example in which the present invention is applied to an upper arm electrocardiogram device will be described as one embodiment of the present invention.

[0037] First Embodiment

[0038] (Device configuration) An embodiment of the present invention will be described with reference to Fig. 1 to Fig. 4. Fig. 1 is a diagram showing a state in which a biosignal measuring device 1 is worn on the upper arm, Fig. 2 is a plan view of the biosignal measuring device 1, Fig. 3 is a perspective view of the biosignal measuring device 1, and Fig. 4 is a block diagram showing the hardware configuration of the biosignal measuring device 1.

[0039] The biosignal measuring device 1 of this embodiment is an upper arm electrocardiogram device that is worn on a user's upper arm (preferably the left upper arm close to the heart) and used to measure an ECG (Electrocardiogram) signal (electrocardiogram signal) as a biosignal.

[0040] The biosignal measuring device 1 mainly comprises a band 10, a plurality of electrodes 11 fixed to the band 10, and a control unit 12 fixed to the band 10.

[0041] The band 10 is a member (fixing member) for fixing the electrode 11 in a state where it is pressed against the living body. In this embodiment, a strip-shaped band 10 made of a flexible and malleable material (e.g., chemical fiber, silicone, leather, etc.) is used. A fixing mechanism 13 is provided at the longitudinal end of the band 10. As shown in Figs. 1 and 3, the band 10 is made into a loop and fastened with the fixing mechanism 13, so that the biosignal measuring device 1 can be worn on the upper arm. The fixing mechanism 13 may be any type of fastener, hook, connector, button, magnet, etc.

[0042] A plurality of electrodes 11 (also called an electrode array) are embedded and fixed in the band 10 such that the surface that comes into contact with the living body is exposed on the inside (living body side) of the band 10. The plurality of electrodes 11 are arranged in a row at equal intervals in the longitudinal direction of the band 10. In this way, when the band 10 is wrapped around the arm, the electrodes 11 come into contact with different positions around the arm. The number of electrodes 11 can be designed as desired. For the purpose of measuring an ECG signal, at least two electrodes 11 (one electrode pair) are sufficient, and three or more electrodes 11 may be provided to improve the reliability and robustness of the measurement. In this embodiment, a configuration in which six electrodes 11 (three electrode pairs) are provided is adopted.

[0043] The electrode 11 is a dry metal electrode. Wet electrodes (such as gel electrodes) have problems such as the possibility of causing skin rashes and itching when worn for a long time, and low durability and ease of maintenance, whereas the dry electrode 11 does not have such problems. The biosignal measuring device 1 of this embodiment is intended to be worn for a long time and to monitor ECG signals for 24 hours, so the dry electrode 11 is preferable.

[0044] The control body 12 is a processing unit that controls the biosignal measuring device 1 and performs signal processing. As shown in FIG. 4, the control body 12 has a structure in which a measurement circuit 120 for measuring an ECG signal, a biosignal processing device 121 for performing various signal processing on the ECG signal, a battery 122, an alarm device 123, and other circuits are mounted inside a case made of, for example, resin or metal. The control body 12 may be provided with a physical switch and a display. The measurement circuit 120 is an analog circuit composed of a differential amplifier, etc., and an ECG sensor is composed of a plurality of electrodes 11 and the measurement circuit 120. The biosignal processing device 121 is composed of, for example, an AD converter, a filter, a processor, a memory, etc. The battery 122 is a rechargeable secondary battery. The AD converter, the filter, the processor, the memory, and other circuits included in the biosignal processing device 121 are driven by the power of the battery 122. The notification device 123 is a device that notifies the user, and may be any type of device, such as a buzzer or speaker that emits sound, a vibrator that emits vibration, a light source that emits light, or an electrode that emits electrical stimulation. A plurality of types of notification devices may be provided. When notifying by light, it is preferable that the light source is disposed in a position where the light can be seen by the user wearing the biosignal measuring device 1, for example, on the upper side surface of the control body 12 (the side surface facing the base of the arm) as shown in FIG. 3.

[0045] (Control unit) FIG. 5 is a block diagram showing an example of the functional configuration of the control main unit 12. As shown in FIG.

[0046] The control body 12 includes an operation mode switching unit 30, an ECG measurement unit 20, an ECG signal processing unit 21, an ECG heart rate information calculation unit 22, an ECG signal quality determination unit 23, an AF determination unit 24, a storage unit 25, and a communication unit 26 as components related to the measurement of an ECG signal. The operation mode switching unit 30 is a unit that dynamically switches the number of active channels used for measurement according to the quality of the ECG signal to be measured. The ECG measurement unit 20 is a unit that amplifies the potential difference between the active electrode pair by a differential amplifier and outputs it as an ECG signal. The ECG signal processing unit 21 is a unit that performs AD conversion and filtering of the ECG signal, and includes an AD conversion unit 210 that performs analog-to-digital conversion of the ECG signal by an AD converter, an electromagnetic noise removal unit 211 that removes electromagnetic noise from the ECG signal to increase the S / N ratio, and a baseline drift removal unit 212 that removes baseline drift (low-frequency drift) of the ECG signal. The ECG heart rate information calculation unit 22 is a unit that extracts various heart rate information from the ECG signal, and includes an R wave detection unit 220, an RRI calculation unit 221, a heart rate variability calculation unit 222, and a P wave detection unit 223. The ECG signal quality determination unit 23 is a unit that determines whether the quality of the ECG signal is good or bad (i.e., whether accurate or reliable data suitable for purposes such as diagnosis is measured or not). The AF determination unit 24 is a unit that detects the occurrence of AF (Atrial Fibrillation) based on the heart rate information and calculates an index related to AF. The storage unit 25 is a non-volatile memory that stores measured or calculated data. The storage unit 25 also stores parameters (such as power consumption values ​​for each operation mode) that are referred to in predicting the available operation time described later. The communication unit 26 is a unit that performs wireless data communication with external devices (such as the user's smartphone, other health devices, and a home server).

[0047] The control unit 12 also includes a remaining battery charge acquisition unit 31, a remaining battery charge prediction unit 32, and an output unit (notification unit) 33 as components related to prediction of remaining battery charge time. Reference numeral 1 denotes a part that acquires information on the remaining battery charge. An operational time prediction unit 32 predicts the operational time of the biosignal measuring device 1 based on the power consumption in each operational mode and the remaining battery charge. An output unit (notification unit) 33 outputs information on the predicted operational time, determines whether charging is required based on the predicted operational time, and notifies the user at an appropriate time when charging is required.

[0048] Of the functional units shown in FIG. 5, the ECG measurement unit 20 is a function provided by the measurement circuit 120 in FIG. 4, the output unit 33 is a function provided by the cooperation of the biosignal processing device 121 and the alarm device 123 in FIG. 4, and the other functional units are functions provided by the biosignal processing device 121 in FIG. 4.

[0049] (ECG signal measurement and processing) The measurement process of an ECG signal by the biosignal measuring device 1 will be described with reference to Fig. 6 to Fig. 9. Fig. 6 is a flowchart showing the flow of the measurement process of an ECG signal, Fig. 7 is a diagram showing examples of operation modes and active channels, Fig. 8 is a diagram explaining the waveform and heart rate information of an ECG signal, and Fig. 9 is a diagram explaining the relationship between signal quality, operation mode, and power consumption.

[0050] When the user wraps the band 10 around the upper arm and fastens the band 10 with the fastening mechanism 13, and then performs an operation to instruct the start of measurement, the processor of the control unit 12 starts the measurement process of FIG.

[0051] In step S500, the operation mode switching unit 30 selects a channel to be activated according to the current operation mode. As shown in Fig. 7, the biosignal measuring device 1 of this embodiment has a first operation mode (multi-channel mode) in which all three sets of electrode pairs and their corresponding circuits (differential amplifiers AMP#1 to AMP#3, AD converters ADC#1 to ADC#3, etc.) are activated to measure ECG signals of three channels of channels #1 to #3, and a second operation mode (single-channel mode) in which only one set of electrode pairs and its corresponding circuits (differential amplifier AMP#1, AD converter ADC#1) are activated to measure ECG signals of only one channel.

[0052] In this embodiment, as shown in FIG. 7, three electrode pairs are set so that two electrodes 11 that are exactly opposite each other when the band 10 is wrapped around the upper arm are paired. This is because the greater the distance between the two paired electrodes 11, the greater the potential difference (i.e., an ECG signal with a high S / N ratio) that can be measured. The distance between the two electrodes 11 is, for example, the linear distance between the two electrodes 11 when measured in a state in which the band 10 is wrapped around the upper arm as shown in FIG. 3. However, the method of setting the electrode pairs is not limited to this. For example, a multiplexer may be used to freely switch the combination of the paired electrodes 11. In this case, it is also possible to measure ECG signals of four or more channels from six electrodes 11.

[0053] (In the first operating mode) In step S510, the ECG measurement unit 20 measures three-channel ECG signals using three sets of electrode pairs. Specifically, the three differential amplifiers AMP#1 to AMP#3 and the three AD converters ADC#1 to ADC#3 are each supplied with power from the battery 122 to be active (in a driven state), and the signals of the three sets of electrode pairs are input to the corresponding differential amplifiers AMP#1 to AMP#3. The potential difference between the two electrodes 11 constituting the electrode pair is amplified by the differential amplifier, and output as an ECG signal (analog voltage signal).

[0054] The three-channel ECG signals (analog voltage signals) output from the differential amplifiers AMP#1 to AMP#3 are analog-to-digital converted by the corresponding AD converters ADC#1 to ADC#3, and are output as three-channel ECG signals (digital signals). The ECG signal is subjected to digital signal processing to remove electromagnetic noise and baseline drift, which can be achieved by known noise reduction techniques such as a band-pass filter, a notch filter, or a moving average.

[0055] In step S511, the ECG heartbeat information calculation unit 22 analyzes the three-channel ECG signals that have been captured and calculates various pieces of heartbeat information. The ECG heartbeat information calculation unit 22 executes the process of step S511 when time-series data (waveform data) of the ECG signal for a predetermined unit time is captured from the ECG signal processing unit 21. The unit time may be set to, for example, about 10 to 600 seconds, and is set to 10 seconds in this embodiment.

[0056] As shown in FIG. 8, the waveform of one heartbeat of an ECG signal mainly consists of P waves, QRS waves, and T waves. The QRS wave refers to a waveform that combines an R wave, which is an upward peak, and Q and S waves, which appear before and after the R wave, which are downward. In a normal heart, an electrical impulse generated in the sinus node is transmitted from the atrium to the ventricle, and the atrial excitation (contraction) and the ventricular excitation (contraction) occur in sequence, thereby pumping blood. The P wave is a waveform that corresponds to the excitation of the atrium, the QRS wave is a waveform that corresponds to the excitation of the ventricle, and the T wave is a waveform that corresponds to the process in which the ventricle recovers from the excitation. For an average adult, the heart rate is about 60 to 80 bpm, so the time series data of an ECG signal for a unit time (10 seconds) contains about 10 to 14 heartbeat waveforms.

[0057] Examples of the heartbeat information include R amplitude (height of R wave from the baseline), QRS amplitude (defined as, for example, the sum of the height of R wave from the baseline and the depth of S wave from the baseline), P amplitude (height of P wave from the baseline), T amplitude (height of T wave from the baseline), P width (time from the start of P wave to the end of P wave), QRS width (time from the start of Q wave to the end of S wave), T width (time from the start of T wave to the end of T wave), PQ time (time from the start of P wave to the start of Q wave), QT time (time from the start of Q wave to the end of T wave), RRI (RR interval; time from the peak of R wave to the peak of the next R wave), PPI (PP interval; time from the start of P wave to the start of the next P wave), heartbeat variability (time variability of RRI and PPI), etc. It is not necessary to calculate all of these heartbeat information, and only necessary heartbeat information may be calculated. Heartbeat information other than these may also be calculated.

[0058] In step S512, the ECG signal quality determination unit 23 evaluates the quality of the ECG signal for the unit time acquired in step S510. Any index may be used for evaluating the signal quality. For example, the noise, power (strength), baseline fluctuation, etc. of the ECG signal itself may be used as the evaluation index, or the heart rate information calculated in step S511 (including whether the calculation of the heart rate information was successful or not) may be used as the evaluation index. In step S512, the evaluation indexes for each of the ECG signals of the three channels are calculated.

[0059] In step S513, the ECG signal quality determination unit 23 selects the channel from the three channels that provides the best quality ECG signal (the ECG signal with the highest evaluation index value). The ECG signal from the selected channel is used in subsequent processing.

[0060] In this way, in the first operation mode, ECG signals from multiple channels are measured redundantly, and the ECG signal with the best quality is selected from those and used for processing such as AF determination, etc. Therefore, measurements that are robust against the effects of body movement and the like can be realized.

[0061] (In the second operating mode) In step S520, only one channel of ECG signals is measured using one electrode pair by the ECG measurement unit 20. For example, in the example of FIG. 7, power is supplied from the battery 122 to one differential amplifier AMP#1 and one AD converter ADC#1, and power supply to the other differential amplifiers AMP#2 and AMP#3 and the other AD converters ADC#2 and ADC#3 is stopped. As a result, only one channel #1 becomes active (in a driven state). The channel to be activated is not limited to #1, and channel #2 or channel #3 may be activated. The potential difference between one electrode pair corresponding to the active channel is amplified by the differential amplifier and output as an ECG signal (analog voltage signal) of one channel. The ECG signal of one channel output from the differential amplifier is analog-digital converted by a corresponding AD converter and output as an ECG signal (digital signal) of one channel. The ECG signal of one channel is subjected to digital signal processing to remove electromagnetic noise and baseline fluctuation. Then, in step S521, the ECG heartbeat information calculation unit 22 analyzes the ECG signal of one channel that has been captured and calculates various heartbeat information. In step S522, the ECG signal quality determination unit 23 evaluates the quality of the ECG signal for the unit time captured in step S520. The process of steps S520 to S522 and the process of steps S510 to S512 are the same in content, except for the number of channels to be processed.

[0062] In step S530, the ECG signal quality determination unit 23 determines whether the quality of the ECG signal measured most recently for a unit time (the ECG signal selected in step S513 in the first operation mode) satisfies a predetermined standard. The predetermined standard is a threshold value for determining whether the ECG signal is accurate or reliable data suitable for purposes such as diagnosis. For example, the predetermined standard may be set to whether a heartbeat waveform can be identified from the ECG signal (whether R waves and P waves have been successfully detected). Hereinafter, an ECG signal determined to have a quality equal to or higher than the predetermined standard is also referred to as a "clean signal," and an ECG signal determined not to satisfy the predetermined standard is also referred to as a "noisy signal."

[0063] If the ECG signal is determined to be clean (YES in step S530), the ECG signal quality determination unit 23 determines whether or not an abnormal waveform is included in the ECG signal for this unit time (step S540). For example, if the heartbeat interval (RRI) is constant, it may be determined that there is no abnormal waveform, and if the heartbeat interval is random, it may be determined that there is an abnormal waveform.

[0064] The determination results of steps S530 and S540 are sent to the operation mode switching unit 30. If the most recently measured ECG signal is determined to be noisy (NO in step S530), the operation mode switching unit 30 switches the operation mode to the first operation mode (step S550). Also, if the ECG signal is determined to be clean but has an abnormal waveform (YES in step S540), the operation mode switching unit 30 switches the operation mode to the first operation mode (step S551). Then, if the ECG signal is determined to be clean and has no abnormal waveform (NO in step S540), the operation mode switching unit 30 switches the operation mode to the second operation mode (step S552).

[0065] In step S560, the AF determination unit 24 determines whether or not AF (atrial fibrillation) has occurred based on information regarding the presence or absence of P waves and information regarding heart rate fluctuations. For example, if there are "no P waves" and "heart rate fluctuations", it is determined that atrial fibrillation has occurred in the unit time indicated by the waveform data. Although not shown, at the timing when the occurrence of atrial fibrillation is detected, the output unit (notification unit) 33 may notify the user, or an alert message or the like may be output from the communication unit 26 to an external device.

[0066] In step S570, the AF determination unit 24 records the occurrence or absence of atrial fibrillation together with information on the measurement time of the waveform data in the storage unit 25. At this time, the waveform data and the heart rate information calculated in step S511 or S521 may be recorded together. As a result, the storage unit 25 accumulates AF determination results for each unit time.

[0067] The measurement process shown in FIG. 6 described above is repeatedly executed every unit time (for example, every 10 seconds), and the operation mode (number of active channels) is changed according to the quality and state of the measured signal. The ECG signal is monitored 24 hours a day with dynamic switching.

[0068] FIG. 9 shows the relationship between ECG signal quality, operation mode, and power consumption.

[0069] For example, when the SNR of the ECG signal is reduced due to myoelectric noise caused by body movement, the signal quality is determined to be noisy. In the noisy section, multi-channel measurement is performed in the first operation mode. By performing redundant measurements using electrode pairs placed at different locations and selecting the best signal from those for use in diagnosis, it is expected that the stability and reliability of measurement and diagnosis can be improved.

[0070] On the other hand, in the clean section where the ECG signal of a clean waveform is measured, the measurement is performed in a single channel in the second operation mode as a rule. In the second operation mode, power supply to circuits not used for measurement (differential amplifier, AD converter, filter, etc.) is stopped, so that the power consumed by the circuits can be reduced compared to the first operation mode. In addition, in the second operation mode, since it is only necessary to perform processes such as calculation of heart rate information (S521 in FIG. 6) and quality evaluation of the ECG signal (S522 in FIG. 6) on the ECG signal of one channel, the power consumed by the processor can be reduced compared to the first operation mode which requires processing of ECG signals of three channels. Since the measurement process in FIG. 6 is repeatedly executed at regular unit times (e.g., 10 seconds) regardless of whether the operation mode is the first operation mode or the second operation mode, the power consumption per unit time can be reduced in the clean period where the ECG signal is stable (i.e., the period when the device operates in the second operation mode) compared to the noisy period (i.e., the period when the device operates in the first operation mode).

[0071] However, even in a clean section, if an abnormal waveform such as a disturbance in the heartbeat interval appears, the operation mode is immediately switched to the first operation mode and measurement is performed in multiple channels. This allows the signal waveform to be captured more accurately in a situation where an arrhythmia is occurring, enabling highly accurate and reliable diagnosis. For example, in the AF determination in step S560, in order to accurately determine whether or not atrial fibrillation is occurring, it is necessary to confirm the disturbance in the heartbeat interval and the presence or absence of P waves. This is because it is not possible to distinguish whether the arrhythmia is due to atrial fibrillation or another disease (e.g., premature ventricular contraction) based on the disturbance in the heartbeat interval alone. Atrial fibrillation can be determined only after evaluating the presence or absence of P waves (waves indicating atrial excitation) and confirming that no P waves are formed. However, as shown in FIG. 8, since the amplitude of the P wave is small, it may be difficult to identify the P wave even in a clean signal. It is expected that the use of ECG signals from multiple channels will enable the identification of P waves, i.e., the determination of the presence or absence of P waves, to be performed with high accuracy, and as a result, the accuracy of AF determination can be improved.

[0072] If a disturbance in the heartbeat interval is detected during single-channel measurement in the second operation mode, it may not be possible to accurately detect P waves from the waveform data for that unit time, and it may not be possible to determine whether or not atrial fibrillation is occurring. However, it is considered sufficient to switch to the first operation mode when a disturbance in the heartbeat interval is detected and perform multi-channel measurement from the next unit time. Although there is a risk that the detection of AF will be delayed by about one unit time (e.g., 10 seconds), since AF is considered to be high risk when it continues for 30 seconds or more, this level of time lag is acceptable in practice.

[0073] (Operation time prediction) Fig. 10 shows the flow of the prediction process of the operable time in the first embodiment. The prediction process in Fig. 10 is executed at a predetermined time interval (for example, once every several minutes to several tens of minutes).

[0074] In step S100, the battery remaining capacity acquisition unit 31 acquires information on the battery remaining capacity RM of the biosignal measurement device 1. The battery remaining capacity is measured, for example, using a gas gauge circuit or the like. It can be measured.

[0075] In step S101, the operable time prediction unit 32 reads information on the power consumption PC1 in the first operation mode and the power consumption PC2 in the second operation mode from the storage unit 25. It is assumed that the power consumption value in each operation mode is obtained by an experiment or the like and is written in advance in the storage unit 25 before the biosignal measuring device 1 is shipped from the factory.

[0076] In step S102, the operable time prediction unit 32 predicts the first operable time AT1 when the biosignal measuring device 1 continues to operate in the first operation mode, based on the power consumption PC1 in the first operation mode and the remaining battery charge RM. The simplest prediction formula is AT1[h]=RM[W h] / PC1[W] However, the prediction formula is not limited to this, and the available operation time AT1 may be calculated using a more advanced prediction formula that takes into account various variable factors.

[0077] In step S103, the operable time prediction unit 32 predicts the second operable time AT2 when the biosignal measuring device 1 continues to operate in the second operation mode from the power consumption PC2 in the second operation mode and the remaining battery charge RM. The simplest prediction formula is AT2[h]=RM[W h] / PC2[W] However, the prediction formula is not limited to this, and the available operation time AT2 may be calculated using a more advanced prediction formula that takes into account various variable factors.

[0078] Because PC1>PC2, AT1 <AT2となる。

[0079] In step S104, the output unit 33 displays the information on AT1 and AT2 on a display, or notifies an external device (such as the user's smartphone) via the communication unit 26. FIG. 11 is an example of an operable time display screen displayed on the biosignal measuring device 1 or an external device. AT1 is displayed as the minimum value of the predicted operable time, and AT2 is displayed as the maximum value of the predicted operable time. Furthermore, as shown in FIG. 11, the time when the battery will run out may be calculated from the current time and the predicted value of the operable time, and the user may be notified of that time (i.e., the time when charging is required). When notifying the user of the predicted value of the operable time or the time when charging is required, a value that takes into account a small margin of time may be notified so that charging is performed before the battery runs out completely.

[0080] As shown in Fig. 11, the remaining operating time and the predicted charging time are presented as a time range (minimum to maximum), allowing the user to roughly grasp what time it is best to charge, and thus making it easier to plan charging. In the example of Fig. 11, if the remaining operating time is displayed as a minimum of 8 hours and a maximum of 16 hours as of the current time of 12 o'clock, the user knows that the battery will run out between 8 pm and 4 am today, and can make a plan according to his or her own schedule and life rhythm, such as "When I get home today, I'll remove device 1 and charge it while I'm preparing dinner or while I'm taking a bath."

[0081] According to the prediction process of the present embodiment described above, in a wearable biosignal measuring device 1 that can dynamically switch the number of active channels, it is possible to predict the available operating times AT1, AT2 taking into account the power consumption PC1, PC2 for each operating mode, and provide the user with information to inform them of the appropriate timing for charging. This improves the usability of the biosignal measuring device 1, and enables 24-hour monitoring with minimal gaps in measurement.

[0082] <Second embodiment> In the prediction process of the first embodiment, the available operation time is predicted for each operation mode individually. In the prediction process of the second embodiment, the proportion of future operation time for each of the first and second operation modes is predicted, and the available operation time is calculated based on the proportion of future operation time for each operation mode and the power consumption and remaining battery capacity in each operation mode.

[0083] Fig. 12 shows the flow of the prediction process of the operable time by the biosignal-measuring device 1 of the second embodiment. The same steps as in the prediction process of the first embodiment (Fig. 10) are given the same step numbers. The following mainly describes the process that differs from the first embodiment.

[0084] In step S100, the battery remaining capacity acquisition unit 31 acquires information on the battery remaining capacity RM of the biosignal measuring device 1. In step S101, the operable time prediction unit 32 reads information on the power consumption PC1 in the first operation mode and the power consumption PC2 in the second operation mode from the storage unit 25. Up to this point, the process is the same as in the first embodiment.

[0085] In step S200, the operable time prediction unit 32 reads the time series data of the ECG signal measured in the past from the storage unit 25, analyzes the state (quality) of the waveform, and divides it into a clean section where the quality of the waveform is equal to or higher than a predetermined standard, and a noisy section where the quality of the waveform is worse than the predetermined standard. This process is the same as the process described in steps S511, S512, S521, S522, and S530 of FIG. 6. For example, data for at least the past 24 hours may be used as the data to be analyzed. Since the amount of activity (body movement) during the day and while sleeping is completely different, for example, if the data during the sleep time is used alone, there is a risk that only the clean section will be found, and if the data during the day is used alone, there is a risk that there will be many noisy sections. Therefore, by using 24 hours of data that reflects the user's life cycle, it is possible to obtain a reasonable result without bias due to time of day.

[0086] In step S201, the operation time prediction unit 32 predicts the ratio of the operation time in the first operation mode to the operation time in the second operation mode based on the result obtained in step S200. For example, when the length of the noisy period in the past 24 hours is Tn [h] and the length of the clean period is Tc [h], the operation time prediction unit 32 may calculate the ratio R1 of the future operation time in the first operation mode and the ratio R2 of the future operation time in the second operation mode as follows: R1 = Tn / (Tn+Tc) R2 = Tc / (Tn + Tc)

[0087] In step S202, the operational time prediction unit 32 predicts the operational time AT based on the ratios R1, R2 of future operation times in the first operation mode and the second operation mode, the power consumption PC1 in the first operation mode, the power consumption PC2 in the second operation mode, and the remaining battery capacity RM.

[0088] When operating in the first operating mode for a time (R1×AT) and in the second operating mode for a time (R2×AT), the amount of power consumed in each operating mode is (R1×AT)×PC1 [W·h] and (R2×AT)×PC2 [W·h]. The sum of these must be equal to the remaining battery charge RM, so (R1×AT)×PC1+(R2×AT)×PC2=RM Solving this for AT gives us: AT[h]=RM[W h] / (R1×PC1[W]+R2×PC2[W]) By using this prediction formula, it is possible to predict the available operation time AT taking into account the operation time ratio between the first operation mode and the second operation mode.

[0089] In step S203, the output unit 33 displays information on the predicted value AT on a display, or notifies an external device (such as the user's smartphone) via the communication unit .

[0090] According to the prediction process of the present embodiment described above, in a wearable biosignal measuring device 1 capable of dynamically switching the number of active channels, it is possible to predict the available operating time AT taking into consideration the power consumption PC1, PC2 for each operating mode and the future operating time ratios R1, R2, and provide information to inform the user of the appropriate charging timing. In this embodiment, the operating time ratios R1, R2 for each operating mode are predicted by analyzing the user's own past measurement data, so that the available operating time when the user uses the device as usual can be estimated with high accuracy. This improves the usability of the biosignal measuring device 1 and enables 24-hour monitoring with little blank time between measurements.

[0091] In this embodiment, the past measurement data is divided into two, a noisy section and a clean section, but the clean section may be further divided into an abnormal waveform section where an abnormal waveform appears and a normal waveform section where no abnormal waveform appears. Specifically, in the process of step S200, the operable time prediction unit 32 evaluates the fluctuation of the heartbeat interval (RRI) in the clean section, and classifies a section where the heartbeat interval is constant into a "normal waveform section" where no abnormal waveform appears, and a section where the heartbeat interval randomly fluctuates into an "abnormal waveform section" where an abnormal waveform appears. This process is the same as the process of step S540 in the first embodiment. Then, in step S201, the operable time prediction unit 32 obtains the ratio R1 of the operation time in the first operation mode and the ratio R2 of the operation time in the second operation mode as follows. Tca is the length of the normal waveform section, and Tcb is the length of the abnormal waveform section. R1 = (Tn + Tcb) / (Tn + Tc) R2 = Tca / (Tn+Tc) Tc=Tca+Tcb

[0092] In other words, the ratio of the time of the noisy section plus the abnormal waveform section in the past 24 hours is the ratio of the operation time in the first operation mode, and the ratio of the time of the normal waveform section in the past 24 hours is the ratio of the operation time in the second operation mode. The prediction formula for the operable time AT may be the same as that described above.

[0093] 9, the biosignal measuring device 1 performs control to switch to the first operation mode in order to detect P waves with high accuracy when an abnormal waveform is detected. Therefore, it is expected that a more realistic estimation of the operable time is possible by taking the abnormal waveform section into account in the prediction process.

[0094] <Third embodiment> In the first and second embodiments, the user is notified by displaying a predicted value of the available operating time on the display, but it is also possible to go further and determine whether charging is necessary based on the predicted value, and notify the user of the need for charging at an appropriate time.

[0095] FIG. 13 is an example of a notification process in the case where the minimum value AT1 and the maximum value AT2 of the operable time are predicted as in the first embodiment. The output unit (notification unit) 33 compares the minimum value AT1 of the operable time obtained in the most recent prediction process with a threshold value ATth (step S300). When the minimum value AT1 falls below the threshold value ATth (YES in step S300), a first notification is executed (step S301). The notification may be by sound, vibration, light, electrical stimulation, or any other means. Thereafter, the output unit (notification unit) 33 compares the maximum value AT2 of the operable time with the threshold value ATth (step S302), and when the maximum value AT2 also falls below the threshold value ATth (YES in step S302), a second notification is executed (step S303). By issuing such a notification, it is possible to make the user aware that the time when charging is required is approaching, and it is possible to prevent forgetting to charge. At this time, the notification method may be different between the first and second notifications, for example, by changing the sound or color of the emitted light, or by changing the light emission method or vibration method. The threshold value ATth may be set arbitrarily, for example, to about 1 hour or 2 hours. The threshold value ATth may be changed by the user.

[0096] <Fourth embodiment> FIG. 14 is an example of a notification process when a predicted value AT of the available operation time is calculated as in the second embodiment. The output unit (notification unit) 33 determines whether charging is necessary based on the predicted value AT of the available operation time obtained in the most recent prediction process (step S310). The criteria for determining whether charging is necessary may be set in any way. For example, it may be determined that "charging is necessary" when the predicted value AT falls below a predetermined threshold value ATth2. The threshold value ATth2 may be set arbitrarily, and may be set to, for example, about 3 to 6 hours with some margin of error. The threshold value ATth2 may be made changeable by the user.

[0097] Even if a notification is given while the user is out or at work, the user cannot charge the battery, and such notification is both useless and bothersome to the user. Therefore, when it is determined that charging is necessary (YES in step S310), the output unit (notification unit) 33 determines whether the user is in a state in which charging is possible (step S311). Then, when it is determined that the user is in a state in which charging is possible (YES in step S311), the output unit (notification unit) 33 notifies the user (step S312).

[0098] The determination of whether the user is in a state in which charging is possible may be performed in any manner. For example, if the user is at home or if the user usually charges the battery, it may be considered that the user is highly likely to be in a state in which charging is possible.

[0099] For example, the output unit (notification unit) 33 may read information on a preset time of returning home from the storage unit 25, and may consider that the user has returned home (i.e., the user has become in a state in which charging is possible) when the current time passes the time of returning home. The value of the time of returning home may be set by the user, or may be set as a fixed value that is the time of returning home of an average office worker (e.g., 7 p.m.).

[0100] Alternatively, the biosignal measuring device 1 may cooperate with a schedule management service such as Google Calendar. For example, the output unit (notification unit) 33 may acquire schedule information of the user from an external device via the communication unit 26, and determine the time when the user returns home or the time period when the user is at home based on the schedule information.

[0101] Alternatively, if the biosignal measuring device 1 records a history of the times when charging was performed in the past in the storage unit 25, the time period during which the user can charge may be estimated based on the charging history information. Many users charge the device 1 according to their own lifestyle rhythm (for example, while taking a bath), and therefore charging is often performed at roughly the same time period. Therefore, by referring to the user's own charging history information, the optimal charging timing for that user can be estimated.

[0102] Alternatively, if the biosignal measuring device 1 has a built-in positioning sensor such as a GPS or is capable of connecting to an external device having such a positioning sensor, it may determine whether the user is at home based on the user's current location information.

[0103] With any of the above methods, a notification is sent when the user is in a state where charging is possible (or when there is a high probability that this will occur), so that an effective reminder can be given at an appropriate time for the user.

[0104] In step S310, if the predicted value AT of the operable time falls below the threshold value ATth2, In this case, it is determined that "charging is necessary", but the user's chargeable time period may be taken into consideration when determining whether charging is necessary. For example, consider a case where the current time is 16:00, the predicted operable time AT is 20 hours, the threshold value ATth2 is 3 hours, and the user's chargeable time period is from 19:00 to 23:00. In this case, in the process of step S310 described above, it is determined that "charging is necessary" when the operable time is less than 3 hours, that is, at around 9:00 a.m. the next day, which is 17 hours from now, but the user cannot charge even if it is notified at that time. In that case, the device 1 will stop due to running out of charge at around 12:00, resulting in a situation where measurement cannot be performed for a long time. Therefore, the output unit (notification unit) 33 may obtain information on the current time and information on the chargeable time period when the user is expected to be able to charge the device the next day, and determine that charging is necessary today if the predicted time when the biosignal measuring device 1 will stop operating, calculated from the current time and the operable time, arrives before the chargeable time period the next day. In the above case, the predicted operation stop time is 12:00 the next day, which is before the chargeable time period of the next day, which is between 19:00 and 23:00. Therefore, it is determined that charging is necessary today, and a notification is given to the user during today's chargeable time period (although there is still sufficient time left for operation). By performing such a determination process, the notification is given ahead of time, so that it is possible to prevent the device 1 from stopping during a time period when the user cannot charge. Note that information on the chargeable time period may be set in advance in the storage unit 25, may be obtained as schedule information from an external device, or may be input by the user himself.

[0105] <Other> The above embodiment merely exemplifies the configuration of the present invention. The present invention is not limited to the above specific embodiment, and various modifications are possible within the scope of the technical concept. For example, the body part on which the device is attached may be other than the upper arm. As for the fixing member for fixing the electrode 11 in a state where it is pressed against the living body, as in the above embodiment, a band-shaped (strip-shaped) one that wraps around the measurement part of the living body with the electrode 11 in contact, as well as a wrap-shaped or ring-shaped one that covers and encases the measurement part of the living body may be used. The fixing member may have elasticity or deformability to correspond to the size (diameter) of the measurement part of the living body. Alternatively, if it is made of a non-elastic material, it may have a structure that allows the length to be adjusted. The number of channels may be any number of channels, as long as it is two or more. The electrodes 11 do not need to be arranged in a single row, and may be arranged in a two-dimensional array. Also, the electrodes 11 may be arranged at different intervals rather than at equal intervals. The electrodes 11 may be integrated with the fixing member (band 10) or may have a structure separate from the fixing member. The control body 12 does not have to be fixed to the band 10. For example, the control body 12 and the band 10 may be separate structures, and a cable may be used to connect the control body 12 and the band 10 (electrodes 11). The biological signal to be measured is not limited to an ECG signal, and may be, for example, an electromyogram signal, an electroencephalogram signal, a pulse wave, or a blood pressure signal. Furthermore, the configurations of the above embodiments may be combined with each other as long as there is no technical contradiction.

[0106] This specification includes the following disclosure.

[0107] [Appendix 1] A wearable biosignal measuring device (1) capable of measuring biosignals of a plurality of channels and powered by a battery, comprising: an operation mode switching unit (30) capable of switching between a first operation mode in which the plurality of channels are activated to measure biological signals of the plurality of channels and a second operation mode in which only some of the channels are activated to measure biological signals of the some of the channels; a battery remaining capacity acquisition unit (31) for acquiring information on a remaining capacity of the battery; a prediction unit (32) that predicts an operable time of the biological signal measuring device (1) based on the power consumption in each operation mode and the remaining battery charge; and an output unit (33) that outputs information on the predicted value of the operable time. Biosignal measuring device (1).

[0108] [Appendix 2] the prediction unit (32) predicts a first operable time when the device continues to operate in the first operation mode from the power consumption in the first operation mode and the remaining battery charge, and predicts a second operable time when the device continues to operate in the second operation mode from the power consumption in the second operation mode and the remaining battery charge; The output unit (33) outputs the first operable time and the second operable time as a minimum value and a maximum value of a predicted value of the operable time. A biosignal measuring device (1) as described in Appendix 1.

[0109] [Appendix 3] The output unit (33) determines whether charging is necessary based on the predicted value of the operable time, and notifies a user when charging is necessary. A biosignal measuring device (1) according to appendix 1 or appendix 2.

[0110] [Appendix 4] The output unit (33) controls the timing of the notification so that the notification is made during a time period during which the user can charge the device. A biosignal measuring device (1) as described in Appendix 3.

[0111] [Appendix 5] The output unit (33) determines that the user has returned home when the current time passes a preset time, and issues the notification. A biosignal measuring device (1) as described in Appendix 4.

[0112] [Appendix 6] The biosignal measuring device (1) described in Appendix 4, wherein the output unit (33) determines the home time zone during which the user is at home based on the user's schedule information obtained from an external device, and makes the notification during the home time zone.

[0113] [Appendix 7] The output unit (33) estimates a time period during which the user can charge the battery based on charging history information that records a time when charging was performed in the past, and performs the notification during the estimated time period during which charging is possible. A biosignal measuring device (1) as described in Appendix 4.

[0114] [Appendix 8] The output unit (33) determines whether the user is at home based on the location information of the user, and issues the notification when it is determined that the user is at home. A biosignal measuring device (1) as described in Appendix 4.

[0115] [Appendix 9] The output unit (33) notifies the user by at least one of sound, vibration, light, and electrical stimulation. A biosignal measuring device (1) according to any one of Supplementary Note 3 to Supplementary Note 8.

[0116] [Appendix 10] The output unit (33) has an alarm device (123) that notifies the user by light, The notification device (123) notifies the user who wears the biosignal measuring device (1). Located in a visible position, A biosignal measuring device (1) according to any one of Supplementary Note 3 to Supplementary Note 9.

[0117] [Appendix 11] The output unit (33) acquires information on a current time and information on a time period when the user is expected to be able to charge the battery on the next day, and determines that charging is necessary today if a time when the biosignal measuring device (1) is expected to stop operating, calculated from the current time and the operable time, arrives before the time period when charging is possible on the next day. A biosignal measuring device (1) according to any one of Supplementary Note 3 to Supplementary Note 10.

[0118] [Appendix 12] the prediction unit (32) predicts a ratio of a future operation time of each of the first operation mode and the second operation mode, and calculates the operable time based on the ratio of the future operation time of each operation mode, the power consumption in each operation mode, and the remaining battery capacity. A biosignal measuring device (1) according to any one of Supplementary Note 1 to Supplementary Note 11.

[0119] [Appendix 13] the prediction unit (32) analyzes time-series data of the biological signals measured in the past, and predicts the future ratio of the operation time of each of the operation modes based on the analysis results; A biosignal measuring device (1) as described in Appendix 12.

[0120] [Appendix 14] The prediction unit (32) By analyzing the state of a waveform in time series data of a biological signal measured in the past, the waveform is divided into a clean section in which the quality of the waveform is equal to or higher than a predetermined standard and a noisy section in which the quality of the waveform is worse than the predetermined standard; predicting a percentage of a future operation time of the first operation mode from the percentage of the noisy period; predicting a future proportion of the operation time of the second operation mode from the proportion of the clean section; A biosignal measuring device (1) as described in Appendix 13.

[0121] [Appendix 15] The prediction unit (32) By analyzing the state of the waveform in the time series data of the biological signal measured in the past, the waveform is divided into a clean section where the quality of the waveform is equal to or higher than a predetermined standard and a noisy section where the quality of the waveform is worse than the predetermined standard, and the clean section is further divided into an abnormal waveform section where an abnormal waveform appears and a normal waveform section where the abnormal waveform does not appear. predicting a percentage of a future operation time in the first operation mode from the percentages of the noisy section and the abnormal waveform section; predicting a future proportion of the operation time in the second operation mode from the proportion of the normal waveform section; A biosignal measuring device (1) as described in Appendix 13.

[0122] [Appendix 16] The biological signal is an ECG (Electrocardiogram) signal. A biosignal measuring device (1) according to any one of Supplementary Note 1 to Supplementary Note 15. [Explanation of symbols]

[0123] 1: Biosignal measuring device 10: Band 11: Electrode 12: Control unit 13:Fixing mechanism

Claims

1. A wearable biosignal measuring device that is capable of measuring biosignals of a plurality of channels and is powered by a battery, an operation mode switching unit capable of switching between a first operation mode in which the plurality of channels are activated to measure biological signals of the plurality of channels and a second operation mode in which only a portion of the channels are activated to measure biological signals of the portion of the channels; a battery remaining capacity acquiring unit for acquiring information on a remaining capacity of the battery; a prediction unit that predicts an operable time of the biosignal measuring device based on the power consumption in each operation mode and the remaining battery charge; and an output unit that outputs information about a predicted value of operable time. Biosignal measuring device.

2. the prediction unit predicts a first operable time when the device continues to operate in the first operation mode from the power consumption in the first operation mode and the remaining battery charge, and predicts a second operable time when the device continues to operate in the second operation mode from the power consumption in the second operation mode and the remaining battery charge; the output unit outputs the first operable time and the second operable time as a minimum value and a maximum value of a predicted value of an operable time. The biosignal measuring device according to claim 1 .

3. The output unit determines whether charging is necessary based on the predicted value of the operable time, and notifies a user when charging is necessary. The biosignal measuring device according to claim 1 .

4. The output unit controls a timing of the notification so that the notification is made during a time period during which the user can charge the device. The biosignal measuring device according to claim 3 .

5. The output unit determines that the user has returned home when the current time passes a preset time, and issues the notification. The biosignal measuring device according to claim 4.

6. The output unit determines a time period during which the user is at home based on schedule information of the user acquired from an external device, and performs the notification during the time period during which the user is at home. The biosignal measuring device according to claim 4.

7. The biosignal measuring device of claim 4 , wherein the output unit estimates a time period during which the user can charge based on charging history information that records the time when charging was performed in the past, and makes the notification during the estimated time period during which charging is possible.

8. The output unit determines whether the user is at home based on the location information of the user, and issues the notification when it is determined that the user is at home. The biosignal measuring device according to claim 4.

9. The output unit notifies the user by at least one of sound, vibration, light, and electrical stimulation. The biosignal measuring device according to claim 3 .

10. The output unit has an alarm device that notifies the user by light, The notification device is disposed at a position visible to the user wearing the biosignal measuring device. The biosignal measuring device according to claim 3 .

11. The output unit acquires information on a current time and information on a time period when the user is expected to be able to charge the battery on the next day, and determines that charging is required today when a time when the biosignal measuring device is expected to stop operating, calculated from the current time and the available operating time, arrives before the available charging time on the next day. The biosignal measuring device according to claim 3 .

12. the prediction unit predicts a ratio of a future operation time of each of the first operation mode and the second operation mode, and calculates the operable time based on the ratio of the future operation time of each operation mode, the power consumption in each operation mode, and the remaining battery capacity; The biosignal measuring device according to claim 1 .

13. the prediction unit analyzes time-series data of the biological signals measured in the past, and predicts a future ratio of the operation time of each of the operation modes based on the analysis result; The biosignal measuring device according to claim 11.

14. The prediction unit is By analyzing the state of a waveform in time series data of a biological signal measured in the past, the waveform is divided into a clean section in which the quality of the waveform is equal to or higher than a predetermined standard and a noisy section in which the quality of the waveform is worse than the predetermined standard; predicting a percentage of a future operation time in the first operation mode from the percentage of the noisy period; predicting a future proportion of the operation time in the second operation mode from the proportion of the clean interval; The biosignal measuring device according to claim 13.

15. The prediction unit is By analyzing the state of the waveform in the time series data of the biological signal measured in the past, the waveform is divided into a clean section where the quality of the waveform is equal to or higher than a predetermined standard and a noisy section where the quality of the waveform is worse than the predetermined standard, and the clean section is further divided into an abnormal waveform section where an abnormal waveform appears and a normal waveform section where the abnormal waveform does not appear. predicting a percentage of a future operation time in the first operation mode from the percentages of the noisy section and the abnormal waveform section; predicting a percentage of a future operation time in the second operation mode from the percentage of the normal waveform section; The biosignal measuring device according to claim 13.

16. The biological signal is an ECG (Electrocardiogram) signal. The biosignal measuring device according to any one of claims 1 to 15.

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