Biological signal processing device

Abstract

To perform quantization and correction of temperature artifacts in a biological signal processing device capable of acquiring a stable vital signal even during an exercise and when there is a change in the environment.SOLUTION: A biological signal processing device includes: an ECG measuring unit 611 for acquiring an electrocardiographic signal from a body surface of a living body; a heat flow measuring unit 612 for measuring a heat flow that flows between the inside of the living body and the environment; an acceleration measuring unit 613 for measuring an acceleration of the living body; an environment measuring unit 620 for measuring a state of the environment surrounding the living body; an ECG-SNR comparison unit 631 for calculating a signal-to-noise ratio of the electrocardiographic signal, and comparing it with a first threshold; a deep part temperature-to-noise comparison unit 632 for calculating noise contained in the heat flow measured by the heat flow measuring unit, and comparing it with a second threshold; a threshold generation unit 635 for changing the first threshold and / or the second threshold from the acceleration measured by the acceleration measuring unit and the state of the environment measured by the environment measuring unit; and an output unit 640 for outputting a communication signal on the basis of results of the comparison from the ECG-SNR comparison unit and the deep part temperature-to-noise comparison unit.SELECTED DRAWING: Figure 34

Description

[Technical field]

[0001] The present invention relates to a biological signal processing device, and more particularly to a biological signal processing device capable of acquiring stable vital signals even during exercise or in a changing environment. [Background technology]

[0002] Many technologies for measuring biosignals have been proposed to date. As an example, Patent Document 1 proposes a bioinformation analysis device that includes a bioinformation detection unit that detects a user's bioinformation, a user determination unit that determines the user's athletic ability, an information setting unit that sets analysis information according to the user's athletic ability when it is determined that the user's athletic ability meets certain conditions, and an analysis unit that analyzes the bioinformation based on the set analysis information, thereby enabling even users with an athletic heart to appropriately measure the bioinformation.

[0003] Patent document 2 describes a biometric information processing device that includes a biometric information detection unit that detects biometric information about a subject, a body movement information detection unit that detects body movement information about the subject's movements, a reliability judgment unit that judges the reliability of the biometric information based on a specified criterion, a memory unit that stores a correlation between the body movement information and the biometric information, and an update unit that updates the correlation stored in the memory unit, in order to improve the accuracy of pulse rate estimated from exercise intensity, and when the reliability judgment unit judges that the biometric information satisfies the specified criterion, the update unit updates the correlation based on the biometric information and the body movement information.

[0004] Patent Document 3 describes a respiration rate estimation method including a first step of estimating the subject's respiration rate from a time series signal of first data related to the subject's cardiac function and a time series signal of second data related to acceleration due to the subject's respiratory movement, respectively; a second step of estimating the respiration rate estimated from the first data and the respiration rate estimated from the second data after filtering out noise using a Kalman filter; and a third step of performing a weighted averaging process on the multiple respiration rate estimates obtained in the second step.

[0005] Patent Document 4 also describes an electrocardiogram analysis device and electrode set that includes electrocardiogram measurement electrodes for measuring an electrocardiogram, noise measurement electrodes for measuring noise, a measurement unit that measures an electrocardiogram signal measured by the electrocardiogram measurement electrodes and a noise signal measured by the noise measurement electrodes, and a chest compression noise removal processing unit that analyzes the measured electrocardiogram signal and noise signal to extract a noise-removed electrocardiogram from which noise has been removed, thereby reducing the effects of noise due to chest compression. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] International Publication No. 2016 / 088307 [Patent Document 2] International Publication No. 2014 / 196119 [Patent Document 3] International Publication No. 2017 / 090732 [Patent Document 4] JP 2014-076117 A Summary of the Invention [Problem to be solved by the invention]

[0007] Biometric information is measured (detected) not only when the patient is at rest but also when the patient is working or exercising. However, the above-mentioned conventional technologies mainly focus on pulse waves and respiratory rates, and even in the case of electrocardiograms, they focus on the effects of body movement when using an AED, and do not take into account strenuous exercise, exercise, work, and the large changes in the environment that accompany them.

[0008] Therefore, an object of the present invention is to make it possible to obtain stable vital information during daily life and exercise, and even when there are changes in body movement and the environment. [Means for solving the problem]

[0009] In order to solve the above problems, the biological signal processing device of the present invention includes an ECG measurement unit that acquires an electrocardiogram signal from a body surface of a living body, a heat flow measurement unit that measures a heat flow between the inside of the living body and the environment, an acceleration measuring unit for measuring acceleration caused by the movement of the living body; and an environmental measuring unit for measuring environmental conditions surrounding the living body selected from temperature, humidity, atmospheric pressure, wind speed, atmospheric composition, and latitude and longitude; Calculate the signal-to-noise ratio of the electrocardiogram signal. , which is set as the initial value when the device is first installed An ECG-SNR comparison unit compares the ECG-SNR with a predetermined first threshold value, and calculates noise contained in the heat flow measured by the heat flow measurement unit. , the initial value was set when the organism was stationary. A deep temperature-noise comparison unit that compares the deep temperature with a second predetermined threshold value; During the movement of the above organism From the acceleration measured by the acceleration measuring unit and the environmental condition measured by the environmental measuring unit, Detecting the amount of movement of the living body, The first threshold value and / or the second threshold value The above amount of exercise a threshold generating unit which changes the threshold value in response to the The device is characterized by comprising an output section which outputs a notification signal based on the comparison results from the ECG-SNR comparison section and the deep temperature-noise comparison section. Effect of the Invention

[0029] According to the present invention, stable vital information can be obtained during daily life and exercise, and even when there are changes in body movement or environment. [Brief description of the drawings]

[0030] [Figure 1] FIG. 1 is a schematic diagram showing a basic configuration of a first embodiment of the present invention. [Diagram 2] FIG. 2 is a schematic diagram showing a specific configuration of the first embodiment. [Figure 3a] FIG. 4 is a waveform diagram showing an example of an electrocardiogram waveform measured by the ECG measurement unit. [Figure 3b] FIG. 4 is a waveform diagram for explaining an example of signal processing in an R wave extraction unit. [Figure 3c] 5 is a waveform diagram for explaining an example of signal processing in a signal calculation unit. FIG. [Figure 3d] 5A to 5D are waveform diagrams illustrating an example of signal processing in a wave removal unit. [Figure 3e] 5 is a waveform diagram for explaining an example of signal processing in a noise calculation unit. [Figure 3f] 5 is a waveform diagram for explaining an example of signal processing in an SNR calculation unit. [Figure 3g] 5 is a schematic diagram for explaining an example of signal processing in an SNR comparison unit, an output unit, and a frequency analysis unit. [Figure 4] FIG. 4 is a schematic diagram showing a first aspect of the second embodiment of the present invention. [Diagram 5] FIG. 4 is a schematic diagram for explaining the operation of the first embodiment. [Figure 6] 4 is a wave diagram for explaining details of the SNR comparison means in the first embodiment. [Figure 7] FIG. 4 is a schematic diagram showing a second aspect of the second embodiment of the present invention. [Figure 8] FIG. 4 is a schematic diagram for explaining the operation of the second embodiment. [Figure 9] 13A is a schematic perspective view showing a first mode of a sensor structure having a plurality of ECG electrodes according to a third embodiment of the present invention, and FIG. 13B is a view taken along an arrow A in FIG. 13A (bottom view). [Figure 10] 5A is a schematic perspective view showing a second embodiment of the sensor structure, and FIG. 5B is a view taken along the line B in FIG. 5A (bottom view). [Figure 11] FIG. 4 is a schematic perspective view showing a third embodiment of the sensor structure. [Figure 12]FIG. 13 is a schematic perspective view of a fourth embodiment of the above sensor structure further equipped with a deep body temperature measurement function, (b) a view taken along arrow C in (a) (side view), and (c) a view taken along arrow D in (a) (bottom view). [Figure 13a] FIG. 13 is a schematic exploded perspective view showing a first example of a case applied to the fourth embodiment. [Figure 13b] FIG. 13 is a schematic exploded perspective view showing a second example of the case applied to the fourth embodiment. [Figure 13c] FIG. 13 is a schematic exploded perspective view showing a third example of the case applied to the fourth embodiment. [Figure 14] 13A and 13B are schematic diagrams showing the front and rear of a garment having ECG electrodes and heat flow pads for detecting heat flow according to a fourth embodiment of the present invention. [Figure 15] 1A is a schematic plan view showing the wiring on the above-mentioned wafer, FIG. 1B is a perspective view, and FIG. 1C is a schematic cross-sectional view taken along line EE in FIG. [Figure 16] 1A is a plan view showing ECG electrode pads provided on the garment, and FIG. 1B is a schematic cross-sectional view taken along line FF in FIG. [Figure 17] 16(a) and 16(b) are schematic cross-sectional views taken along line GG in FIG. 16(a), each showing an ECG electrode pad provided on the garment. [Figure 18] FIG. 1A is a plan view showing a heat flow pad of the SHF type provided on the above-mentioned garment, and FIG. 1B is a schematic cross-sectional view taken along line HH in FIG. [Figure 19] 18(a) is a plan view similar to FIG. 18(a), and FIG. 18(b) is a schematic cross-sectional view taken along line II in FIG. 18(a), showing a heat flow pad of the SHF type provided on the above-mentioned wafer. [Figure 20] FIG. 1A is a plan view showing a DHF type heat flow pad provided on the above-mentioned wafer, and FIG. 1B is a schematic cross-sectional view taken along line JJ in FIG. [Figure 21] 20(a) is a plan view similar to FIG. 20(a), and FIG. 20(b) is a schematic cross-sectional view taken along line KK in FIG. 20(a), showing a DHF-type heat flow pad provided on the above-mentioned wafer. [Figure 22]1A is a schematic perspective view showing a first example of an insulating material applied to the heat flow pad; FIG. 1B is a schematic perspective view showing a second example; and FIG. 1C is a schematic perspective view showing a third example. [Figure 23] FIG. 13 is a schematic diagram showing a first aspect according to the fifth embodiment of the present invention. [Figure 24] FIG. 13 is a schematic diagram showing a second aspect of the fifth embodiment. [Diagram 25] FIG. 4 is a schematic diagram for explaining the operation of the second embodiment. [Figure 26] FIG. 13 is a schematic diagram showing a third aspect of the fifth embodiment. [Figure 27] FIG. 11 is a schematic diagram for explaining the operation of the third embodiment. [Figure 28] FIG. 13 is a schematic diagram showing a fourth aspect of the fifth embodiment. [Figure 29] FIG. 13 is a schematic diagram for explaining the operation of the fourth embodiment. [Diagram 30] FIG. 13 is a schematic diagram showing a fifth aspect of the fifth embodiment. [Diagram 31] FIG. 13 is a schematic diagram showing a sixth aspect of the fifth embodiment. [Diagram 32] FIG. 13 is a schematic diagram for explaining the operation of the sixth embodiment. [Diagram 33] FIG. 13 is a schematic diagram showing a basic configuration of a sixth embodiment of the present invention. [Diagram 34] FIG. 23 is a schematic diagram showing a specific configuration of the sixth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0031] Next, some embodiments of the present invention will be described with reference to the drawings, but the present invention is not limited to these embodiments.

[0032] [First embodiment] Calculation of SNR of ECG wave and its use As shown in FIG. 1, the biological signal processing apparatus according to the first embodiment basically includes an ECG measurement section 110, an R wave extraction section 120, an SNR calculation section 130, and an output section (RRI output section) 140.

[0033] To briefly explain the role of each unit, the ECG (Electrocardiogram) measurement unit 110 measures (acquires) an electrocardiogram signal from the body surface. The R-wave extraction unit 120 extracts the R-wave contained in the electrocardiogram signal from its characteristics and identifies the position of the R-wave peak.

[0034] The SNR calculation unit 130 calculates the signal-to-noise ratio (SNR) of the electrocardiogram signal. As the signal, the amplitude from the minimum to the maximum of the electrocardiogram signal can be used, or the effective value can be used. Noise is a component other than the thermoelectric power caused by the heartbeat in the acquired electrocardiogram signal, and is caused by the shift and contact change between the electrode and the skin caused by exercise or movement, the change in contact potential, static electricity, the change in conductance due to sweat, myoelectricity, induction from an AC power source, etc.

[0035] The output unit (RRI output unit) 140 applies signal processing based on the SNR obtained by the SNR calculation unit 130 to the R wave and its surrounding section obtained by the R wave extraction unit 120, and outputs the result. As the signal processing, for example, the heart rate, heart rate variability (HRV), the shape of the PQRST wave, and biological information (vital information) obtained from them are displayed, notified, or made available for use by other programs.

[0036] Next, as shown in FIG. 2, the specific configuration of this biological signal processing device includes, in addition to an ECG measurement unit 110, an R wave extraction unit 120, an SNR calculation unit 130, and an output unit (RRI output unit) 140, a signal calculation unit 121, a wave removal unit 122, a noise calculation unit 123, an SNR comparison unit 131, and a frequency analysis unit 150.

[0037] To explain the operation of each part in more detail, the ECG measurement part 110 amplifies the signal from the electrodes (ECG electrodes) for electrocardiogram detection attached to the body surface, applies an appropriate filter to the signal, and outputs it (see FIG. 3a). The filters include a high-pass filter (HPF) and a low-pass filter (LPF).

[0038] The high-pass filter removes fluctuations in the baseline of the ECG signal. The low-pass filter removes inductive noise from AC power lines and electromyographic noise caused by chest muscle movements, etc. The passband determined by the high-pass and low-pass filters is usually set to pass a few Hz to about 40 Hz, and in noisy environments, to pass about 10 Hz to 20 Hz.

[0039] Narrowing the passband increases the effect of suppressing noise, but it also reduces the reproducibility of the original electrocardiogram signal generated when the heart beats.In addition, noise may enter the narrowed passband due to exercise or other movements in daily life, making it impossible to completely remove it.

[0040] One of the factors that generates noise due to movement is the contact potential that occurs between the ECG electrodes and the skin. Although the contact potential can be reduced by using silver / silver chloride (Ag / AgCl) as the electrode material, it is difficult to reduce it to zero.

[0041] When movement causes a shift in the contact between the ECG electrodes and the skin, or when the contact area changes, this finite potential changes and becomes noise. Impulse-like potential changes have a wide spectrum and fall within the above passband.

[0042] The belts and clothing used to attach ECG electrodes to the body are usually made of fabric, making it difficult to completely eliminate static electricity, which also generates impulse-like potentials and causes the same problems.

[0043] When the body sweats due to exercise, a layer of sweat forms on the surface of the skin, or is absorbed by a belt or clothing and has a conductivity of about 0.1 mS (resistivity of about 10 kΩ). If this conductivity changes due to exercise, it can cause the same problem.

[0044] These phenomena are random processes that vary depending on the vector of the movement, the position of the ECG electrodes, the degree of contact with the skin, etc., and appear as noise (artifacts) in certain sections, as shown in Figure 3a.

[0045] Here, the interval is defined as the time domain for each R wave, which is divided at the midpoint between the peak time of one R wave and the peak time of the next R wave. As shown in Figure 3a, there are intervals with little noise and intervals with a lot of noise.

[0046] 3b, the R wave extraction unit 120 extracts the R wave. For example, a method of extracting the R wave is to set a threshold value for the amplitude of the QRS wave and identify the value above the threshold as a QRS wave. Alternatively, a threshold value can be set for characteristics such as the slope or length of the waveform.

[0047] In addition, since electrocardiogram signals are generally repetitive waveforms of the same shape, the position of the R wave can also be identified using an autocorrelation function, template matching, wavelets, etc.

[0048] Many methods for extracting these R waves are known, but they have limitations when there is noise with a shape similar to the original electrocardiogram signal, when the original electrocardiogram signal is buried in noise, etc. In addition, by applying the features of the present invention, which selects and rejects R wave sections based on the SNR and selects and combines good signals from multiple electrodes while using these conventional R wave detection methods, it is possible to obtain a more effective output.

[0049] 3c, the signal calculator 121 calculates the signal amount for SNR calculation. As described above, the amplitude from the minimum to the maximum of the electrocardiogram signal or the effective value can be used as the signal.

[0050] For example, by averaging the positions of the R waves by using the R wave time extracted by the R wave extraction unit 120, it is possible to calculate a signal amount with less noise. A moving average can also be used as an averaging method. Since the QRS wave is usually the maximum amplitude wave of the original electrocardiogram signal, the peak to peak of this QRS wave can also be used as the signal amplitude.

[0051] In some cases, the signal quality can be determined using only the noise without performing signal calculation in the signal calculation unit 121. However, in the case of ECG, there are individual differences in amplitude, and differences in amplitude may occur depending on the attachment position of the ECG electrodes. Furthermore, the gain of the amplifier may be automatically adjusted by AGC (Auto Gain Control). Therefore, it is preferable to perform signal calculation in the signal calculation unit 121.

[0052] 3d, the wave removal unit 122 removes waves such as PQRST contained in the original electrocardiogram signal (electrocardiogram waveform). In this example, as shown in FIG. 3d(a), the QRS wave period and the T wave period are removed. The periods of other waves such as P waves and U waves can also be removed, but these P waves, U waves, etc. often do not have a significant effect on the calculation of the noise amount, so they may be left as they are.

[0053] The top row of Figure 3d(b) shows the actual electrocardiogram waveform before the PQRST wave was removed, and the bottom row shows the waveform after the PQRST wave was removed. The R wave peak positions are aligned and overlapped for a section of about 100. Since the data was acquired in a stationary state, the amount of noise is small, with an amplitude of about -8 to +6 LSB and an effective value of about 3 LSB RMS. Incidentally, the amplitude of the QRS wave in this example is about 350 LSB, which means that the signal-to-noise ratio (SNR) is over 100 (signal amplitude to effective noise value).

[0054] Figure 3d(c) is an example taken during exercise. The top row shows the actual electrocardiogram waveform before PQRST waves were removed, and the bottom row shows the waveform after PQRST waves were removed. The R-wave peak positions are aligned and a section of about 100 is overlaid. The noise level is about -600 to +600 LSB in amplitude, and about 100 LSB rms in effective value. The signal is about 300 LSB, so the SNR is about 3.

[0055] As another example of wave removal, as shown in FIG. 3d(d), a moving average may be calculated by aligning the position of the R wave in each section, and the moving average may be subtracted from the electrocardiogram signal including noise. Such an embodiment is also included in the present invention.

[0056] Next, referring to Fig. 3e, the noise calculation unit 123 obtains, for example, the effective value of the noise waveform extracted as described above as the noise amount. The noise amplitude can also be used as the noise amount. If the noise amount of each section is, for example, the noise amount of the latest section Ni, the noise amount of the section immediately before that Ni-1, the noise amount of the section immediately before that Ni-2, ..., the noise amount Ni of the latest section is obtained in sequence and added after the section immediately before Ni-1.

[0057] The SNR calculation unit 130 calculates the SNR from the signal amount and the noise amount. The signal amount can be a moving average or an instantaneous value for each section, and the noise amount can be an effective value for each section. An example of the SNR calculated in this way is shown in FIG. 3f. The heart rate is also shown for reference. The first half of the graph with a low heart rate is when the user is sitting (sitting), and the second half of the graph with a high heart rate is when the user is exercising on an exercise bike (registered trademark) (during exercise).

[0058] When the SNR falls below about 20, the frequency of R-wave extraction errors (false positive detection) increases, such as the R-wave extraction time being shifted or noise being extracted as an R-wave. There is also a risk of missed detection, where the actual R-wave cannot be extracted.

[0059] In the first half of the sitting position, the SNR fluctuates but is generally above 30, and the frequency of false positives and false negatives is low. In the second half of the exercise period, the SNR frequently drops below 20, and false positives and false negatives occur frequently. False positives and false negatives not only reduce the accuracy of heart rate calculations, but also reduce the accuracy of HRV calculated using the R wave interval (RRI: RR Interval). In some cases, it may not be possible to output heart rate or HRV.

[0060] The SNR for each section varies greatly. Even in the first half of the sitting position, there are sections where the body is completely still and sections where it is not, so the SNR varies from over 200 to several tens. Even in the second half of the exercise, while constantly pedaling the Aero Bike (registered trademark), there are sections where the SNR is very poor and sections where it is relatively good.

[0061] The length of the interval (RR interval) varies depending on the heart rate, but is about 0.3 to 1 second. Exercise bike (registered trademark) exercise results in a 1-second period when pedaling at 60 rpm, for example. If there is a time period of, for example, about 0.5 seconds in which no artifacts occur in the ECG electrodes during the 1-second period of motion vector change, then this indicates that there is an interval with a high SNR.

[0062] 3g, the SNR comparator 131 compares the SNR with a threshold value in each section. As the threshold value, for example, a value equal to or less than 20, which is the SNR at which the above-mentioned erroneous detection occurs, can be used.

[0063] A decrease in the section SNR makes it impossible to extract the features of the ECG, resulting in missed detections, but the missed detections are in fact a problem with feature extraction and are not related to the threshold. Setting a high threshold to reduce false positives increases the risk of causing problems such as deleting sections that were normally detected (missed detections due to the threshold).

[0064] The probability of detection omissions due to the threshold value increases to a certain extent when the SNR, at which R waves can be detected, is about 10. In order not to discard normal detections, it is preferable to set the threshold value at about 10 or less.

[0065] If the SNR comparison result is the latest section Ri and the previous section Ri-1, the latest section Ri is found and added to the results before Ri-1 in sequence. If it is above the threshold, it is judged as OK, and if it is below the threshold, it is judged as NG.

[0066] The RRI output unit 140 outputs the RRI calculation result. The RRI is calculated by taking the difference in time between two consecutive R-wave peaks. At this time, the period in which the SNR comparison unit 131 has determined that the signal is NG is not used.

[0067] For example, if the section Ri-2 is NG, the R wave extraction result in the section i-2 is not used, which means that the RRI is not calculated between the sections i-1 and i-2, and further between the sections i-2 and i-3.

[0068] The NG section often includes missed detection of R waves, and it is often incorrect to skip section i-2 and calculate the RRI between section i-1 and section i-3, so this calculation is also not performed.

[0069] The frequency analysis unit 150 calculates and outputs the fluctuation of the RRI, that is, the HRV. Conventionally, there is a method of applying spline interpolation to the RRI and resampling at regular time intervals, but applying spline interpolation to an RRI that includes missing parts can cause spurious vibrations, which is not preferable.

[0070] It is preferable to perform frequency analysis based on the least squares method of a sine wave using the RRI with the irregular intervals, without performing spline interpolation or resampling. For example, the Lomb-Scargle periodogram is an example of such frequency analysis.

[0071] In addition, by averaging several sections of raw ECG waveforms with high SNR by aligning the position of the R wave peak, it is possible to obtain a waveform that is faithful to the original ECG waveform with few errors due to noise. Averaging using ECG waves that are disturbed by artifacts during exercise will cause large errors in the wave information.

[0072] The peak value and slope of the PQRSTU waves reflect the characteristics of the living body, the state of the autonomic nerves, hormones, blood oxygen concentration, potassium concentration, and the concentrations of other substances. For example, in an experiment simulating high-altitude mountain climbing, a phenomenon has been reported in which a decrease in blood oxygen concentration causes changes in ST waves. By obtaining accurate ECG wave information, it is possible to grasp such living body conditions.

[0073] [Second embodiment] Synthesis of multiple electrode signals using ECG SNR The second embodiment includes a first aspect shown in FIG. 4 and a second aspect shown in FIG. 7, both of which have a plurality of ECG electrodes 1, 2, . . .

[0074] -First aspect- First, the first aspect will be described. In addition to the ECG measurement section 210, the R wave extraction section 220, and the SNR calculation section 230, it further includes an SNR·inter-electrode comparison section 231, an SNR·threshold comparison section 232, an RRI output section 240, and a frequency analysis section 250.

[0075] Of these, the ECG measurement unit 210, the R wave extraction unit 220, the SNR calculation unit 230, the RRI output unit 240 and the frequency analysis unit 250 may have the same configuration as the ECG measurement unit 110, the R wave extraction unit 120, the SNR calculation unit 130, the RRI output unit 140 and the frequency analysis unit 150 described in the first embodiment above, respectively.

[0076] The ECG electrodes 1, 2, ... are attached to the skin of a living body to detect electrocardiograms. As the electrode material, Ag / AgCl or Ag, which has a small contact potential, or conductive plastic is preferably used.

[0077] Artifacts are superimposed on the original electrocardiogram signal depending on the vector of the movement, the location of the ECG electrodes, muscle movement, the degree of contact with the skin, etc. Since the muscles and vectors used differ depending on the type of exercise (for example, from basic training such as sit-ups, push-ups, and running to training using machines, competitive sports, stretching and yoga that involves free movement, dance, etc.), the way artifacts are introduced differs between multiple ECG electrodes.

[0078] An ECG measurement section 210 may be provided for each ECG electrode, but it is possible to reduce the number of ECG measurement sections to one by switching and using a high-resolution ADC (analog-to-digital converter) in a time-division (interleaved) manner.

[0079] By combining signals from multiple ECG electrodes 1, 2, ... according to the SNR, the influence of artifacts can be suppressed. By synchronously adding (adding at the same position) the original ECG signal, the ECG signal can be made larger.

[0080] Since the ECG signal is unknown, it is difficult to completely separate the ECG and the artifacts. However, the artifacts have waveforms and spectra different from the original ECG signal (PQRST wave) because they are generated by the above-mentioned mechanism.

[0081] Many of these are waves that are band-limited due to impulse-like or step-function-like changes in contact potential caused by the impact of exercise, and are different in nature from the original electrocardiogram signal. The SNR calculation unit 230 quantifies the wave energy of the artifacts that spread across each section.

[0082] The R wave extraction section 220 and the subsequent blocks may have the same configuration as in the first embodiment, but can be made into a single system by switching the processing electrodes at regular intervals.

[0083] The SNR calculation unit 230 calculates the SNR at each time for each ECG electrode 1, 2, ..., and obtains a time series of sectional SNR for each ECG electrode 1, 2, ... as shown in Fig. 5. In Fig. 5, SNR1,i-2:SNR1,i-1:SNR1,i is the time series of sectional SNR for ECG electrode 1, and SNR2,i-2:SNR2,i-1:SNR2,i is the time series of sectional SNR for ECG electrode 2.

[0084] The SNR·electrode comparison unit 231 compares the SNRs of the ECG electrodes at each time and selects the best SNR.

[0085] The SNR threshold comparison unit 232 compares the selected SNR with the threshold. If it is equal to or greater than the threshold, it outputs the R-wave time extracted by the ECG electrode with the best SNR at each time. If it is less than the threshold, it outputs a blank. In FIG. 5, Ri, Ri-1, Ri-2... are the above outputs stored in a memory or the like.

[0086] The RRI output unit 240 calculates and outputs the R-wave interval based on the stored R-wave times. Similar to the first embodiment, since a blank means less than the threshold, the RRIs before and after the blank are not calculated.

[0087] The frequency analysis unit 250 performs frequency analysis at irregular intervals based on the least-squares approximation of a sine wave, similar to the first embodiment, using the above RRI.

[0088] Referring to FIG. 6, the details of the SNR threshold comparison unit 232 will be described.

[0089] FIG. 6(a) shows an example of a relatively simple case where the switching timings of the intervals match between ECG electrode 1 and ECG electrode 2, and it is assumed that there is an artifact in interval i-2 of ECG electrode 1.

[0090] The SNR electrode comparison unit 31a determines that SNR of ECG electrode 1 < SNR of ECG electrode 2. Also, if ECG electrode 2 is equal to or greater than the threshold by the SNR threshold comparison unit 31b, ECG electrode 2 is selected and its R-wave time is adopted (if it is less than the threshold, neither is adopted). That is, as follows.

[0091] (1) When the threshold < SNR1,i-2 < SNR2,i-2, the R-wave time extracted by ECG electrode 2 is adopted. (2) When SNR1,i-2 < the threshold < SNR2,i-2, the R-wave time extracted by ECG electrode 2 is adopted. (3) When SNR1,i-2 < SNR2,i-2 < the threshold, neither is adopted.

[0092] Figure 6(b) shows a somewhat complex case where the lengths of the intervals are different between ECG electrode 1 and ECG electrode 2. In ECG electrode 1, artifacts are extracted as R waves in intervals i-2 and i-1. The interval i-2 of ECG electrode 2 correctly detects the original R wave, but it spans across intervals i-2 and i-1 of ECG electrode 1.

[0093] Generally, the QRS period is the most important period for ECG feature extraction, and it is advisable to focus on this narrow period. By narrowing it, the comparison target may be narrowed down to one in some cases, but it may still be two as in this example. In this case, the following processing may be performed.

[0094] That is, when SNR1,i-2 < SNR1,i-1 < SNR2,i-2, SNR2,i-2 is adopted. The reason is that the SNRs of both intervals of ECG electrode 1 are decreased.

[0095] Except for the above cases, SNR2,i-2 is not adopted. The reason is that there may be a high-SNR extraction in ECG electrode 1 and there may be an artifact in ECG electrode 2.

[0096] -Second aspect- As shown in Figure 7, in order to perform weighted synthesis according to the SNR, instead of the SNR·inter-electrode comparison unit 231 and the SNR·threshold comparison unit 232 in the first aspect, a weight synthesis unit 233 and an R wave re-extraction unit 234 are provided. Other configurations are the same as those in the first aspect. Figure 8 shows a schematic diagram for explaining the operations of each unit.

[0097] The weight synthesis unit 233 multiplies the SNR of the corresponding interval by the ECG raw waveform of each ECG electrode 1, 2,... at each time. For example, assume that the ECG raw waveform of ECG electrode 1 is divided into intervals v1,i:v1,i-1:v1,i-2,... by temporary R wave detection.

[0098] The length of each section is determined by the RR interval as described above, and is, for example, about 0.3 to 1 second. For example, if the ADC sampling rate is 128 sps, each section contains 38 to 128 pieces of time series data (x1, x2, ...).

[0099] That is, each interval is a set of the above time series data, for example, interval v1,i = {x1, x2, ...}. Multiplying this by the SNR gives SNR1,i × v1,i = {SNR1,i × x1, SNR1,i × x2, ...}.

[0100] Furthermore, the weight synthesis unit 233 sums the polarities of the ECG electrodes 1, 2, ... together. For example, if the signals to be synthesized in the latest section are v and i, then v,i=p1×SNR1,i×v1,i+p2×SNR2,i×v2,i+… p1, p2, ... are the polarities of each ECG electrode, and take the value of +1 or -1.

[0101] Usually, once the placement of the ECG electrodes is decided, the polarity of the PQRST wave does not change, so there is no need to change the polarity for each section. In other words, the same values ​​can be used for p1, p2, ... even if the section changes.

[0102] On the other hand, there is a phenomenon in which the shape of the PQRST wave changes depending on the location of the ECG electrodes. For example, in a 12-lead electrocardiograph, the S wave is larger than the R wave in the V1 electrode. In this case, it is advisable to determine the composite polarity so that the QRS amplitude is maximized.

[0103] The R-wave re-extraction unit 234 re-extracts R-waves from the combined signal v,1:v,i-1:v,i-2.... The SNR of the combined wave is approximately the sum of the SNRs of each ECG electrode 1, 2, ... before combination, and R-wave extraction can be performed with an improved SNR.

[0104] As described above, during exercise, there are periods where the SNR is very poor and periods where it is relatively good, and this depends on the motion vector and the location of the electrodes, so by combining weights from multiple ECG electrodes 1, 2, ..., it is possible to reduce periods where the SNR is very poor. This leads to a reduction in false positives and false negatives of RRI.

[0105] Third Embodiment Here, we will explain the structure of a sensor with multiple ECG electrodes for detecting electrocardiograms. Normally, increasing the number of ECG electrodes means increasing the number of terminals for connection to the case (container) that houses the signal processing circuit, etc., and the electrode area also inevitably becomes larger, but in the present invention, we have devised a way to minimize these points.

[0106] -First aspect- 9 shows an example in which ECG electrodes 3 are also provided on the bottom surface of case 310, minimizing an increase in the number of terminals and an increase in the occupied area. In this example, case 310 is fixed to the skin surface via belt 301. An adhesive tape may be used instead of belt 301. Although not shown, case 310 has a built-in signal processing circuit and the like.

[0107] As shown in Figures 9(a) and (b), this example has three ECG electrodes: ECG electrodes 1 and 2 arranged on both sides of case 310, and ECG electrode 3 provided on the bottom surface of case 310 (the surface that comes into contact with the skin).

[0108] As described above, the ECG electrodes 1 and 2 are preferably electrodes made of Ag / AgCl or conductive plastic, and these ECG electrodes 1 and 2 are connected to a signal processing circuit, etc. within the case 310 via terminals 321a and 321b provided on the top surface of the case 310.

[0109] The ECG electrodes 3, like the ECG electrodes 1 and 2, are preferably electrodes made of Ag / AgCl or conductive plastic and are provided on the bottom surface of the case 310, but a conductive gel may also be used for the ECG electrodes 3.

[0110] The ECG electrodes 1, 2, and 3 are attached so as to contact the skin, and an insulating cover 302 is placed so as to cover the terminal portions of the ECG electrodes 1 and 2. It is preferable that the insulating cover 302 is placed so as to protrude 10 mm or more from the end of the case 310. This is to minimize the decrease in insulation resistance between the ECG electrodes 1 and 2 due to sweat.

[0111] 10(a) and (b) show an example in which the ECG electrode 3 arranged on the bottom surface of the case 310 is divided into two ECG electrodes 3a and 3b, thereby increasing the number of electrodes.

[0112] 11 shows an example in which, in addition to the above-mentioned ECG electrodes 1, 2, and 3, four ECG electrodes 4 to 7 are provided. Of these, ECG electrodes 4 and 5 are placed on belt 301 so as to contact the sides of the body, and ECG electrodes 6 and 7 are placed on belt 110 so as to contact the back of the body.

[0113] The sides of the body are the fulcrums that support the belt or the fabric of the clothing, and are relatively less likely to shift during movement. The combination of the back, front, and sides of the body increases the probability of generating a state with fewer artifacts at any given moment in an ECG electrode when the body is stretched forward, backward, left, or right.

[0114] -Second aspect- 12(a)-(c), the second embodiment includes a plurality of (e.g., three) ECG electrodes 1-3 for detecting electrocardiograms, and thermometers 11a and 11b for measuring deep body temperature. When it is not necessary to distinguish between the thermometers 11a and 11b, they are collectively referred to as the thermometer 11.

[0115] A substrate 330 and two thermometers 11a and 11b are provided inside the case 310, which measure the heat flow between the skin and the environment. One thermometer 11a is disposed on the bottom surface of the case 310, and the other thermometer 11b is provided on the substrate 330 away from the thermometer 11a.

[0116] As shown in the figure, one heat flux can be measured by one thermometer pair (thermometers 11a, 11b) (SHF: Single Heat Flux). Also, by using two thermometer pairs, two heat fluxes can be measured (DHF: Dual Heat Flux). In this case, the ECG electrodes 3 are provided on the bottom surface of the case 310 so as to contact the skin.

[0117] -Third aspect- In this third embodiment, an example of connection between the substrate 330, the thermometer 11, and the ECG electrodes 1 to 3 will be described. Fig. 13a shows a case where the ECG electrode 3 is located on the entire bottom surface of the case 310, and Fig. 13b shows a case where the ECG electrode 3, which is a bottom electrode, is divided into ECG electrode 3a and ECG electrode 3b.

[0118] In either case, terminals 321a and 321b are provided on the top cover 311 of the case 310 to electrically connect to the ECG electrodes 1 and 2 attached to the belt 301 (or wear). When there is no need to distinguish between the terminals 321a and 321b, they are collectively referred to as terminal 321.

[0119] Terminals 321a, 321b are connected by wires L1, L2, respectively, to a substrate 330 inside case 310. An insulating sheet 312 is attached to the bottom surface of case 310 with ECG electrodes 3 attached to the outside and an insulating sheet 312 attached to the inside.

[0120] A first thermometer 11a is disposed on the insulating sheet 312. A second thermometer 11b is disposed on the substrate 330. Thermometers 11a and 11b are preferably disposed in the central portion of the case 310. The second thermometer 11b may be disposed on the lower surface side of the substrate 330.

[0121] If the second thermometer 11b is given the function of a radiation thermometer so as to simultaneously measure the substrate temperature and the bottom surface temperature, the first thermometer 11a can be omitted.

[0122] Through holes 313 are provided in the insulating sheet 312, and the ECG electrodes 3 (bottom electrodes) and the substrate 330 are connected by wiring L3 via the through holes 313. The first thermometer 11a and the substrate 330 are also connected by appropriate wiring. Flexible printed wiring can also be used as the wiring.

[0123] Plastic can be used as the insulating sheet 312. In order to increase sensitivity, it is preferable to reduce the thickness of the insulating sheet 312 and bring the temperature of the first thermometer 11a as close to the skin temperature as possible to increase the temperature difference with the second thermometer 11b.

[0124] Furthermore, in order to reduce the thickness of the case 310, it is better for the insulating sheet 312 to be thin. If a high-strength plastic material is used, the thickness can be reduced to about 1 mm. Since the insulating sheet 312 provides the strength for the bottom of the case 310, the thickness of the ECG electrodes 3 on the bottom, which use expensive silver, can be reduced. For the ECG electrodes 3 on the bottom, a sheet of Ag / AgCl can be used.

[0125] Also, a metal with a high Young's modulus, such as iron, plated with Ag / AgCl can be used as the bottom ECG electrode 3. By having the ECG electrode 3 provide strength for the bottom of the case 310, the thickness of the insulating sheet 312 can be made thin, and the temperature of the first thermometer 11a can be made closer to the skin temperature.

[0126] In the example of Figure 13b, when the ECG electrode 3 on the bottom surface is divided into two ECG electrodes 3a and 3b, the side portions 312a, 312b of the insulating sheet 312 on which these divided electrodes 3a, 3b are arranged can be made thinner by the thickness of the electrodes 3a, 3b, thereby making the surface in contact with the skin flat.

[0127] The area directly below and around the first thermometer 11a is an important surface for measuring heat flow, and any gap between this surface and the skin will cause errors in the heat flow measurement. Naturally, contact with the skin is also important for the ECG electrodes 3a and 3b, so it is important that there are no steps on the bottom surface of the case 310.

[0128] In addition, as a relative matter, the thickness of the central portion 312c of the insulating sheet 312 between the ECG electrodes 3a and 3b may be increased by the thickness of those electrodes 3a, 3b to prevent a step from occurring on the bottom surface of the case 310.

[0129] -Fourth aspect- In the fourth embodiment, as shown in FIG. 13c, the ECG electrodes 3 on the bottom surface are divided into four, and the insulating sheet 312 is used as a first insulating sheet, and a second insulating sheet 317 is further provided on the bottom surface of the case 310 in addition to this.

[0130] As in the third embodiment, the first thermometer 11a and the first insulating sheet 312 are placed on the bottom surface of the case 310. Four ECG electrodes 3a to 3d, which are obtained by dividing the ECG electrode 3 into four, are placed on the skin side (bottom side) of the first insulating sheet 312.

[0131] A dummy electrode D is arranged around the first thermometer 11a so as to prevent a gap from being formed under the first thermometer 11a. Note that an electrically insulating dummy sheet of the same thickness may be used instead of the dummy electrode D. A second insulating sheet 317 is further arranged underneath it.

[0132] Second insulating sheet 317 has an area larger than the bottom surface of case 310, and its peripheral portion protrudes from the bottom surface of case 310. Second insulating sheet 317 is made of an insulator such as plastic.

[0133] Conductive gels 315a-315d and non-conductive gel 316 are placed on the bottom surface of second insulating sheet 317. An opening 318 is provided in the center of second insulating sheet 317, and divided ECG electrodes 3a-3d on the case side are electrically connected to conductive gels 315a-315d, respectively. Dummy electrode D and non-conductive gel 316 are in thermal contact. Second insulating sheet 317 can be disposable.

[0134] By providing adhesiveness to conductive gels 315a to 315d and non-conductive gel 316, they can be attached to the skin including case 310. This has the advantage that they can be put on and taken off without removing clothing.

[0135] [Fourth embodiment] In an embodiment of the wear having multiple ECG electrode pads and heat flow pads to be worn on the upper body of a human body, Fig. 14(a) and (b) show an example in which ECG electrode pads E, heat flow pads Th, and a signal processing circuit P are provided on the wear W. Fig. 14(a) shows the front side of the wear W, and Fig. 14(b) shows the back side of the wear W.

[0136] As shown in Figure 14(a), in the case of the human body, there are areas on the front of the body, slightly below the ribs, on the left and right, where the positive potential of the electrocardiogram is prominent (high). In addition, there are areas at the solar plexus and above and below it, where the negative potential of the electrocardiogram is prominent (high in absolute value). By providing ECG electrode pads E in these areas, the signal strength can be increased.

[0137] An ECG electrode pad placed on a part where the electrocardiogram has a predominantly positive potential is designated E(+), and an ECG electrode pad placed on a part where the electrocardiogram has a predominantly negative potential is designated E(-). When there is no need to distinguish between them, they are simply referred to as ECG electrode pads E.

[0138] If the ECG electrode pad E is too large, it is undesirable because it may cause a short circuit between the high potential part and the surrounding relatively low potential parts. On the other hand, arranging many small ECG electrode pads E puts a burden on signal processing and wiring.

[0139] Since the area of ​​the high positive potential portion is relatively small, it is preferable to place one ECG electrode pad (E+) on each side, and three ECG electrode pads (E-) in the center portion with high negative potential, for example. This allows a large signal to be obtained, reduces the above problems, and improves the SNR by using multiple electrodes.

[0140] As shown in Fig. 14(b), the back of the body has a similar potential distribution to the front, although it is smaller than the front. Although this increases the number of electrodes, wiring, and signal processing, the above effect can be further improved by using this part (the back of the body) appropriately.

[0141] The heat flow pad Th is composed of a thermometer 11 for measuring heat flow (described later) and a heat insulating material 432, and causes heat flow in a direction perpendicular to the body surface. The reason for arranging multiple heat flow pads Th is that there is a temperature difference deep inside the body (for example, the upper and lower parts of the abdomen) and that there are artifacts (causes of error) in heat flow measurement, and this must be reduced.

[0142] Gaps between the skin and the thermal flow pad Th can cause artifacts, so it is preferable to attach the pad to a flat surface as much as possible. It is preferable to avoid areas such as the pectoral muscles, chest fat, female breasts, and shoulder blades on the back, as these areas impair flatness.

[0143] From the above viewpoints, it is preferable to place the heat flow pad Th around the sternum C, which is relatively flat at the top, and around the bottom of the ribs, which is relatively flat at the bottom. In the example of Fig. 14(a), the ECG electrode pad E and the heat flow pad Th are arranged so as not to overlap, but it is also possible to store the ECG electrode pad E and the heat flow pad Th in one package and combine both functions.

[0144] Subcutaneous fat reduces the heat flow and increases the thermal time constant. It also reduces the sensitivity of the heat flow meter and slows down the response speed. Furthermore, based on the analogy of the electric field lines of a parallel plate capacitor, the greater the distance between the parallel plates, the more the surrounding flux bends (three-dimensional effect), and the greater the distance from the depths to the heat flow meter, the more susceptible it becomes to the effects of environmental temperature.

[0145] On the front of the body, the area around the sternum C has relatively little subcutaneous fat, so for people with thick subcutaneous fat, it is good to choose the area around the sternum C. Also, since the back of the body often has less subcutaneous fat than the front, you can also choose the back area mentioned above.

[0146] It is preferable to secure a large area for the ground electrode G because artifacts also occur. In order not to disturb the above-mentioned electrocardiographic potential distribution, it is preferable to secure a large area on the back side where the potential is relatively small, especially around the lower neck and around the lower back where the potential is also small.

[0147] The signal processing circuit P is equipped with a wireless circuit for communicating with the outside. In order to extend the communication distance, it is preferable to raise the height of the antenna above the ground. Furthermore, depending on the type of exercise, the user may place their back on the ground, so it is preferable for the user to have the option of not having the signal processing circuit interfere with their exercise.

[0148] From these perspectives, it is preferable to appropriately position the signal processing circuit P on the back, or even on the front, around the neck. The signal processing circuit P can be made thin and small by using technologies such as SiP (System in Package) and COP (Chip on Board), and the signal processing and battery can be placed in different locations and connected by wiring.

[0149] A thin laminated battery can be detachably arranged, for example, at the position shown in B of Fig. 14a. This can reduce the thickness and area of ​​the signal processing circuit P. It can also reduce the weight and thickness around the neck.

[0150] Next, referring to Figures 15(a) to (c), a method for reducing the effects of static electricity, electromagnetic induction, electrostatic coupling, and sweat, which are factors that cause artifacts, will be described for the GND (ground) wiring 410 that is wired on the garment W to connect the ECG electrode pads E(+), E(-) and each heat flow pad Th to the signal processing circuit P.

[0151] 15(c) shows details of the GND wiring 410. According to this, the GND wiring 410 is formed by sequentially laminating on the garment fabric 401 a coated conductor 411 serving as a signal line, a first insulating sheet 412a, a GND conductor 413 serving as a GND electrode, and a second insulating sheet 412b.

[0152] It is preferable that the wear fabric 401 has a characteristic of being less susceptible to static electricity while maintaining comfort, breathability, and a holding ability with compression. However, it is difficult to reduce static electricity to zero, so measures against static electricity are necessary. In addition, it is necessary to reduce induction noise from AC power sources such as AC100V power sources and electrostatic noise caused by capacitive coupling between the human body and surrounding objects.

[0153] By using the coated conductor 411 as the signal line, when the wear fabric 401 absorbs sweat, it is possible to prevent a short circuit with other wiring caused by salt in the sweat. In the heat flow pad Th, it is preferable to use two coated conductors as a stranded wire (twisted pair). By making the signal line from the thermometer (e.g., a thermistor) a twisted pair, common mode noise can be more effectively removed when the signal is processed as a differential signal in the signal processing circuit P.

[0154] The (sandwich) structure in which the GND conductor 413 is disposed between the first insulating sheet 412a and the second insulating sheet 412b prevents the GND conductor 413 from shorting out to other GND wiring through the garment fabric 401 due to sweat. The GND conductor 413 is preferably grounded at one point at the signal processing circuit P.

[0155] The GND conductor 413 is made wide enough to sufficiently cover the coated conductor 411, which is the signal line. For example, a width of about 10 mm is preferable in terms of suppressing induction noise and static electricity noise.

[0156] It is preferable to place these coated conductors 411, GND conductor 413, and insulating sheets 412a, 412b on the environment side (the side opposite the skin) of the clothing fabric 401 in order to suppress external induced noise and electrostatic noise, but they can also be placed on the skin side of the clothing fabric 401 depending on the required SNR and clothing design, etc.

[0157] 16(a) and 16(b), the structure of the ECG electrode pad E will be described. The ECG electrode pad E has a laminate of an ECG electrode 421, a first insulating sheet 422a, and a spring material 423 on the side of the wear fabric 401 that faces the skin, and has a laminate of a second insulating sheet 422b, a GND conductor 424, and a third insulating sheet 422c on the environmental side of the wear fabric 401 (the side opposite the skin).

[0158] The ECG electrodes 421 are placed so as to contact the skin surface. As described above, the ECG electrodes 421 can be made of Ag / AgCl, a metal mainly composed of Ag, or conductive plastic. There is a trade-off as described above for the electrode area, and it is preferable that the area be about 100 to 500 mm2.

[0159] A first insulating sheet 422a is placed on the ECG electrode 421 so as to overhang from the ECG electrode. This is to prevent the ECG electrode 421 from shorting out with other ECG electrodes 421 via the garment W when the garment fabric 401 absorbs sweat. When sweating, it is preferable to ensure that the resistance value with other ECG electrodes is 100 kΩ or more, and the overhanging length is preferably about 5 to 10 mm.

[0160] The spring material 423 plays the role of a spring that maintains contact between the ECG electrode 421 and the skin. The skin surface has unevenness, and the height of the peaks and valleys changes with breathing and movement. Some parts of the skin surface become concave, and the surrounding convex parts support the garment fabric.

[0161] If the ECG electrodes 421 hanging from the clothing fabric 401 are left as is, they will come off the skin and the contact pressure will change, which will cause the aforementioned chemical potential to change, becoming a major cause of artifacts.

[0162] The spring material 423 serves to press the ECG electrodes 421 against the skin with a constant pressure even when the skin surface is recessed. Functionally, it has a structure in which many small springs are arranged in a planar shape. Such materials can be sponge, cushion, foam material, bubble cushioning material, etc. Plastics such as cotton and polyurethane can also be used. It is preferable that the thickness is about several mm to 10 mm when no pressure is applied. The top and bottom relationship of the spring material 423 and the insulating sheet 422a may be reversed.

[0163] In order to minimize the intrusion of electrostatic noise and inductive noise into the ECG electrode 421, a GND region is provided on the opposite side of the ECG electrode 421 across the garment fabric 401. Similar to the above-mentioned GND wiring 410, a structure in which a conductor 424 serving as GND is sandwiched between second and third insulating sheets 422b, 422c is arranged to protrude from the ECG electrode 421.

[0164] It is preferable that the GND conductor 424 is disposed so as to protrude by about 5 to 10 mm from the periphery (four sides) of the ECG electrode 421. A GND laminate in which the GND conductor 424 is sandwiched between insulating sheets 422b and 422c can also be disposed on the spring material 423 and under the garment fabric 401.

[0165] 17(a) and 17(b), a coated conductor 411 in a GND wiring 410 is connected to an ECG electrode 421, and the ECG electrode 421 is connected to a signal processing circuit P via the coated conductor 411.

[0166] The coated conductor 411 is drawn out from the environment side of the garment fabric 401 through the garment fabric 401 , the spring material 423 and the insulating sheet 422 a , and is connected to the ECG electrode 421 via a contact 425 .

[0167] The contact 425 may be a rivet-like metal fitting that mechanically clamps the ECG electrode 421 from above and below. Since the coated conductor 411 penetrates the insulating sheet 422a, it is preferable to provide a gasket 426 at the penetration point of the insulating sheet 422a where the coated conductor 411 penetrates so that moisture such as sweat that has soaked into the garment fabric 401 does not reach the ECG electrode 421. The gasket 426 may be an adhesive or a ring-shaped plastic.

[0168] 18(a) and 18(b), the heat flow pad Th will be described. A first insulating sheet 431a is placed so as to contact the skin surface, and a heat insulator 432 equipped with thermometers 11a and 11b is placed thereon.

[0169] One thermometer 11a is placed on the lower surface (skin side) of the thermal insulation material 432, and the other thermometer 11b is placed on the environmental side (opposite the skin side) of the thermal insulation material 432. Thermometers 11a and 11b are preferably placed in overlapping positions in the center of the thermal insulation material 432. Insulating sheet 431a prevents sweat from the skin from reaching thermometer 11a on the lower surface side.

[0170] Thermometers 11a and 11b measure the heat flow from the skin to the environment. The temperature difference generated by multiplying the heat flow by the thermal resistance of insulation 432 is detected by thermometers 11a and 11b, and the heat flow can be calculated (heat flow meter by SHF).

[0171] Normally, skin temperature is around 30°C, but when a gap is created, heat exchange with the environmental temperature occurs instantly, and even if contact is restored, it takes tens to hundreds of seconds for the temperature to return to thermal equilibrium, meaning that deep body temperature measurements during this time will be subject to large errors.

[0172] A spring material 433 is disposed between the wear fabric 401 and the insulating material 432. Similar to the spring material 423 in the ECG electrode pad E, the spring material 433 has the effect of preventing loss of contact between the skin and the heat flow measurement structure (insulating material + thermometer).

[0173] In addition, by placing a GND laminate consisting of a GND conductor 434 sandwiched between second and third insulating sheets 431b, 431c on the environmental side of the clothing fabric 401, it is possible to suppress the intrusion of noise that is superimposed on the thermometer signal (resistance change in the case of a thermistor).

[0174] Next, the wiring connection to the thermometers 11a and 11b will be described with reference to Figures 19(a) and (b). Note that the first insulating sheet 431a, the heat insulating material 432 having the thermometers 11a and 11b, and the spring material 433 are omitted from Figure 19(b).

[0175] The coated conductor 411 of the GND wiring 410, which has passed from the signal processing circuit P through the environment side of the wear fabric 401, is passed to the skin side to be connected to the thermometers 11a and 11b. The wiring is a twisted pair wiring 411a for the thermometer 11a and a twisted pair wiring 411b for the thermometer 11b, which are connected to the thermometer 11a on the lower surface side of the insulating material 432 and the thermometer 11b on the upper surface side of the insulating material 432, respectively. Note that it is also possible to connect one terminal of the thermometer 11a to one terminal of the thermometer 11b, making the wiring three-wire. It is also possible to use a three-wire stranded structure.

[0176] Next, a configuration example of a heat flow pad Th using the DHF method having two sets of heat flow meters will be described with reference to Fig. 20(a) and (b). In this case, four thermometers 11a to 11d and two heat insulating materials 432a and 432b are used. The other configuration may be the same as that of the heat flow pad described in Fig. 18.

[0177] Of these, thermometers 11a and 11b are arranged on the lower and upper sides of one insulating material 432a as a thermometer pair TP1, and thermometers 11c and 11d are arranged on the lower and upper sides of the other insulating material 432b as a thermometer pair TP2.

[0178] In this way, two heat flows can be measured by providing two pairs of thermometers TP1 and TP2. By changing the thermal resistance of the insulating materials 432a and 432b, heat flows of different magnitudes can be created, and the unknown thermal resistance under the skin can be calculated to calculate the core body temperature.

[0179] 21(a) and (b), the wiring connections to the thermometers 11a to 11d will be described. Note that in FIG. 21(b), the first insulating sheet 431a, the heat insulating material 432a having the thermometers 11a and 11b, the heat insulating material 432b having the thermometers 11c and 11d, and the spring material 433 are not shown.

[0180] The thermometers 11a to 11d are each connected to a signal processing circuit P via two sets of wiring 410A made of coated conductors 411 leading to the thermometer pair TP1 and two sets of wiring 410B also made of coated conductors 411 leading to the thermometer pair TP2.

[0181] If one terminal of each thermometer is combined into one wire, the total number of wires can be reduced to five. Also, the number of wires can be reduced by providing each heat flow pad with a semiconductor switch, for example, to selectively switch the thermometers.

[0182] Next, a heat insulating material suitable for the heat flow pad for DHF explained in Figs. 20 and 21 will be explained with reference to Figs. 22(a) to (c).

[0183] First, in the example of Figure 22(a), a number of air bubbles (hollow cylindrical air bags in this example) B serving as bubble cushioning material are arranged on a lower film 441 of a size (area) equivalent to the combined size of the insulation materials 432a and 432b, and the gas enclosed in the air bubbles Ba in one of the insulation materials 432a and the gas enclosed in the air bubbles Bb in the other insulation material 432b are different.

[0184] Furthermore, the top film 442 and the side film 443 are bonded together to form an airtight gas mat, and the inside of the gas mat is divided by a partition film 444 into a gas chamber Ra on the insulating material 432a side and a gas chamber Rb on the insulating material 432b side, and a different gas is sealed in each of them.

[0185] The gas filled in the bubbles Ba on the insulating material 432a side and the gas chamber Ra may be the same gas, and the gas filled in the bubbles Bb on the insulating material 432b side and the gas chamber Rb may be the same gas.

[0186] By changing the thermal conductivity of the gas sealed in the bubble Ba and gas chamber Ra on the insulation 432a side and the gas sealed in the bubble Bb and gas chamber Rb on the insulation 432b side, insulations 432a, 432b with two types of thermal resistance can be constructed.

[0187] Gases with high thermal conductivity (each value is expressed in W / mK) can be hydrogen at 0.3, helium at 0.14, etc. In contrast, gases with low thermal conductivity (each value is expressed in W / mK) can be air at 0.026, argon at 0.016, and carbon dioxide at 0.015.

[0188] The overall area of ​​the heat insulator 432, including the heat insulators 432a and 432b, is determined so as to reduce the three-dimensional effect caused by the subcutaneous thickness described above. The shape of the heat insulator 432 may be cylindrical. For example, the length and width of each dimension in plan view may be several tens of mm (several tens of mm in diameter), preferably 30 mm or more. The subcutaneous thickness is usually 5 mm or more, which has the effect of suppressing the effect of changes in environmental temperature.

[0189] The thickness of the heat insulating material 432 is preferably several mm, and more preferably 2 mm or more. By making it thicker, the sensitivity of the heat flow measurement increases, but the thickness of the garment increases, so comfort and heat dissipation decrease. Also, if it is too thin, there is a risk that the bottom and top of the foam may come into contact when the body surface is displaced, and thickness fluctuations are likely to appear as errors, so this is not preferable.

[0190] As mentioned above, if a gap occurs between the heat flow pad Th and the skin, it will result in a large error. The foam B deforms to fit the contours of the body. It is pressed against the surface of the body by the compression of the spring material or clothing, preventing gaps from occurring even during exercise. Even if the shape of the foam B changes microscopically, it is acceptable as long as the change in thermal resistance of the insulating material 432 as a whole is within the range of allowable error. Gas has a lower thermal conductivity than liquids and solids, which increases the sensitivity of the heat flow meter.

[0191] A similar structure may be one in which adjacent gas bubbles B are separated by a partition, as shown in Fig. 22(b). Note that instead of gas, a collection of small beads may be enclosed within the gas bubbles B or the film.

[0192] 22(c), synthetic resin sheets 451, 452 with different thermal resistivities may be used as the heat insulating material 432. The synthetic resin is preferably a material capable of changing its shape, such as a rubber material or a foam material. By changing the composition, additives, and foaming ratio of these materials, it is possible to give them two types of thermal resistance.

[0193] Fifth embodiment -First aspect- The fifth embodiment is an embodiment for quantifying and correcting temperature artifacts, and the first aspect has, as its basic configuration, a heat flow measuring unit 500, a deep temperature calculating unit 510, a noise calculating unit 520, and a deep temperature output unit 540, as shown in FIG. 23.

[0194] The heat flow measuring unit 500 measures one or more heat flows flowing from the living body to the surrounding environment by the SHF method, DHF method, or the like. The deep temperature calculating unit 510 calculates the deep temperature using the heat flow, the subcutaneous thermal resistance, and the temperature of the epidermis (body surface). The noise calculating unit 520 calculates the noise superimposed on the deep temperature. The deep temperature output unit 540 processes the deep temperature according to the calculated noise and outputs the result.

[0195] -Second aspect- Preferably, as a second aspect, as shown in FIG. 24, a noise comparison section 530 is further provided after the noise calculation section 520, and data of the noise period calculated by the noise calculation section 520 is removed.

[0196] In this example, the heat flow measuring unit 500 employs the DHF method, and as described above in FIG. 20(b), is provided with two pairs of thermometers TP1, TP2, and as shown in FIG. 25, the thermometer pairs TP1, TP2 measure two heat flows Ith1, Ith2, while the skin surface side thermometers included in the thermometer pairs TP1, TP2 measure skin temperatures Tsk1, Tsk2.

[0197] The deep body temperature calculation unit 510 calculates Rthbody, which is the internal thermal resistance from the deep tissues of the living body to the body surface, from (Tsk2-Tsk1) / (Ith1-Ith2), and then obtains a time series of the deep body temperature Tc of the living body from (Ith1×Rthbody+Tsk1) or (Ith2×Rthbody+Tsk2).

[0198] The noise calculation unit 520 has a high-pass filter (HPF) and receives the deep temperature Tc as an input to output components of a specific frequency or higher. As the high-pass filter, for example, a first-order filter can be set, and a frequency of about 0.001 Hz can be set as the specific frequency (cutoff frequency).

[0199] This allows temperature fluctuation components with periods of 160 seconds or less to pass through as calculated noise with almost no attenuation. The noise amount can be output as the moving average of the squares, that is, the effective value.

[0200] In addition, temperature noise may appear in certain body postures. For example, the inventors have observed a phenomenon in which, when lying on one's left side with a heat flow pad Th attached to the left side of the abdomen, if the tension of the belt fixing the heat flow pad Th loosens or the body surface is displaced, a gap forms between the skin and the heat flow pad Th, causing large temperature noise.

[0201] Changes in body posture can be detected by an acceleration sensor. Since temperature noise occurs later than changes in posture, once a specific posture is detected, it is possible to generate pseudo temperature noise that is easy to remove and output it as calculated noise.

[0202] The noise comparison unit 530 compares the temperature noise calculated by the noise calculation unit 520 with a predetermined threshold value. The threshold value can be determined depending on the required temperature error, and can be set to a value of, for example, about several tens to several hundreds of m°C.

[0203] The deep temperature output unit 540 outputs the deep temperature Tc if, for example, the effective noise value is less than the threshold value. In other words, the output of the deep temperature Tc is stopped during the period when the calculated noise is equal to or greater than the threshold value. The output stop portion is blank, but by displaying, for example, as a user interface (UI), connecting the points immediately before and after the blank, it is possible to prevent the user, other programs, and systems from making erroneous judgments due to noise.

[0204] Since an error occurs in the line connecting the threshold values, the effect of the error can be reduced by masking the noise generation period by expanding it both before and after the period.

[0205] -Third aspect- In the third aspect, as shown in FIG. 26 , the heat flow measuring unit 500 includes a plurality of heat flow measuring units 500a, 500b, ..., a deep temperature calculation unit 510, a noise calculation unit 520, a noise / measurement unit comparison unit 531, a noise / threshold comparison unit 532, and a deep temperature output unit 540.

[0206] The deep temperature calculation section 510, the noise calculation section 520, and the deep temperature output section 540 may be the same as those in the above-mentioned first and second aspects. Moreover, the heat flow measurement sections 500a, 500b, ... employ the DHF method.

[0207] Referring to the operation explanatory diagram of Figure 27, there may be multiple deep temperature calculation units 510, but here each heat flow measuring unit 500a, 500b, ... is sequentially switched and connected to one arithmetic circuit, and as described above, the deep temperatures Tca, Tcb, ... of each part are calculated based on data such as the heat flow and skin temperature from each heat flow measuring unit 500a, 500b, ...

[0208] The noise calculation unit 520 calculates the temperature noise effective values ​​Nca, Ncb, . . . in each deep temperature, in the same manner as in the second embodiment.

[0209] The noise-measurement unit comparison unit 531 compares the temperature noise effective values ​​between the heat flow measurement units and selects the minimum temperature noise effective value.

[0210] The noise / threshold value comparison unit 532 compares the minimum temperature noise effective value with a predetermined threshold value.

[0211] If the minimum temperature noise effective value is less than the threshold value, the deep temperature output unit 540 outputs the deep temperature Tc extracted by the measurement unit, and if the minimum temperature noise effective value is equal to or greater than the threshold value, it outputs a blank.

[0212] As with the synthesis of ECG signals, the effects of artifacts can be reduced by synthesizing signals from multiple heat flow measurement units according to the SNR. There may be an offset in the deep temperature between multiple heat flow pads. In that case, the offset can be recorded when there is little noise, and can be corrected when synthesizing.

[0213] -Fourth aspect- 28 and 29, in the fourth embodiment, a plurality of deep temperature calculation values ​​are weighted and synthesized according to noise. Therefore, a weight synthesis unit 533 is used instead of the noise-between-measurement unit comparison unit 531 and the noise-threshold comparison unit 532 in the third embodiment. The heat flow measurement units 500a, 500b, ..., the deep temperature calculation unit 510, and the noise calculation unit 530 perform the same processing as in the third embodiment.

[0214] The weight synthesis unit 533 multiplies the deep temperatures Tca, Tcb, ... measured by each heat flow measurement unit 500a, 500b, ... by the reciprocal of the calculated noise, adds up the multiplication results of each heat flow measurement unit, and then divides by the sum of the reciprocals of each heat flow measurement unit. The deep temperature output unit 540 outputs the above calculation result as the synthesized Tc. Tc is expressed by the following formula. Tc=(1 / Nca×Tca+1 / Ncb×Tcb) / (1 / Nca+1 / Ncb)

[0215] As a result, the measurement values ​​of the heat flow measurement units 500 (500a, 500b, ...) are overestimated and combined if the noise is small, and the results of each heat flow measurement unit can be effectively used. The combined SNR is approximately the sum of the SNRs of each heat flow measurement unit.

[0216] -Fifth aspect- As shown in FIG. 30, the fifth embodiment has, as its basic configuration, a heat flow measuring unit 500, an environmental temperature measuring unit 501, a false signal generating unit 502, a deep temperature calculating unit 503 and a deep temperature output unit 540, and corrects the false temperature signal.

[0217] The heat flow measuring unit 500 measures one or more heat flows flowing from the living body to the surrounding environment by the SHF method or the DHF method. The environmental temperature measuring unit 501 measures the environmental temperature. The false signal generating unit 502 creates a false signal from the environmental temperature. The deep temperature calculating unit 503 calculates the deep temperature using the heat flow, the subcutaneous thermal resistance, and the epidermal temperature. The deep temperature output unit 540 processes the deep temperature according to the generated false signal, and calculates and outputs a new deep temperature.

[0218] -Sixth aspect- As shown in FIG. 31, the sixth embodiment further comprises a pseudo signal remover 504 in addition to the components of the fifth embodiment, and the operation of the pseudo signal remover 504 will be described with reference to the schematic diagram of FIG.

[0219] The heat flow measurement by the heat flow measuring unit 500 is affected by changes in the environmental temperature because it measures the heat flow Ith that flows from the living body to the environment. The three-dimensional effect due to the subcutaneous thickness described above is one example of this. This can cause a large false signal in the deep temperature Tc.

[0220] The environmental temperature measuring unit 501 is a thermometer that measures the environmental temperature, and can be installed, for example, at the top of the case 310 described in the previous embodiment, or on the surface of the belt 301 or the garment W. Although it is possible to use a temperature acquired at a location close to the environment side of the heat flow measuring unit 500, a delay will occur if there is a thermal time constant, so it is preferable to acquire the temperature at a location with a small thermal time constant.

[0221] The false signal generator 502 acquires the relationship between the environmental temperature and the false signal in advance, and generates a false signal from the current environmental temperature according to the acquired result. The false signal has a certain time response with the environmental temperature as an input. This relational expression is acquired in advance by an experiment or the like.

[0222] For example, we consider the hot plate to represent the deep tissue and the silicone rubber to represent the subcutaneous tissue, and conduct an experiment in which the temperature of the hot plate is kept constant while the environmental temperature is changed. Since the thicker the silicone rubber, the larger the aliasing signal, we obtain the time response transfer coefficient of the aliasing signal by changing the thickness of the silicone rubber.

[0223] Although a false signal occurs in the raw deep temperature calculation result due to a change in the environmental temperature, the false signal removal unit 504 removes the false signal by subtracting it from the raw deep temperature calculation result. The deep temperature output unit 540 outputs the above processing result to a user or administrator, or to another program or system.

[0224] Sixth Embodiment In the sixth embodiment, the measurement function is diagnosed by measuring noise in each unit. As a basic configuration for this purpose, as shown in Fig. 33, the device includes a vital sign measurement unit 610, an environment measurement unit 620, a noise diagnosis unit 630, and an output unit 640.

[0225] The biological signal measuring unit 610 measures electrical signals generated by the living body and other signals obtained by attaching the device to the living body according to the state of the living body. The environment measuring unit 620 measures the state of the environment surrounding the living body. The noise diagnosing unit 630 acquires noise contained in each measuring unit and diagnoses the state of the measuring function. The output unit 640 outputs the diagnosis result.

[0226] Next, a specific configuration will be described with reference to Fig. 34. The biological signal measuring unit 610 includes an ECG measuring unit 611, a heat flow measuring unit 612, and an acceleration measuring unit 613, which respectively measure the ECG, heat flow, and acceleration generated by the living body. Meanwhile, the environment measuring unit 620 measures the temperature, humidity, atmospheric pressure, wind speed, atmospheric composition, latitude, longitude, etc. surrounding the living body.

[0227] It should be noted that the ECG measurement unit 611 and the heat flow measurement unit 612 are not unique to the sixth embodiment, and the ECG measurement unit 611 may have the same configuration as the ECG measurement unit 110 described above, and the heat flow measurement unit 612 may have the same configuration as the heat flow measurement unit 500 described above.

[0228] The noise diagnosis section 630 includes an ECG / SNR comparison section 631 , a deep temperature / noise comparison section 632 , a movement determination section 633 , an environment determination section 634 , and a threshold generation section 635 .

[0229] The ECG·SNR comparison unit 631 compares the SNR of the ECG electrodes with the threshold generated by the threshold generation unit 635. As described above, the ECG electrodes are preferably made of Ag / AgCl or conductive plastic, but as measurements are repeated, they react with precipitates from the living body, oxidize, or are physically damaged. In addition, the belt 301 and wear W that support the ECG electrodes absorb sweat, and the insulating sheet deteriorates or is damaged.

[0230] These can result in increased noise or reduced signal even when stationary, degrading the SNR, and can also cause larger and more frequent artifacts during motion.

[0231] The deposits from the body can be removed to some extent by washing the ECG electrodes, belts, and clothing, and the initial functions may be restored. Even in heat flow measurements, the insulation may be deformed or physically damaged over time.

[0232] Also, if the calibrated state at the time of shipment is changed, an error may occur even with the same calibration parameters. Also, if sweat gets into the signal wiring from the thermometer to the signal processing circuit, an error may occur in the thermometer reading. If the GND pattern is disconnected, the desired shielding effect cannot be obtained, and noise may increase.

[0233] Another cause of noise and SNR degradation may be improper wearing technique: Different body sizes and belt or garment sizes may result in incomplete or no contact of the ECG electrodes or heat flow pads with the skin.

[0234] In particular, if the device is worn away from the heart, such as in the case of a belt, the ECG signal may become extremely small. In addition, the area around the shoulder blades undulates significantly with arm movement, and as a result, contact between the ECG electrodes and heat flow pads and the skin may be lost. The chest is affected by myoelectricity from the pectoral muscles and unevenness caused by fat and breasts. Twists or wrinkles in the belt or clothing can also cause noise and degradation of the SNR.

[0235] Also, the measurement may be unstable at the beginning. Depending on the material of the ECG electrodes, deposits from the skin may reduce the chemical potential between the skin and the ECG electrodes, and the SNR may remain low until the deposits accumulate. This may be improved by first applying water to the ECG electrodes.

[0236] In heat flow measurement, depending on the environmental temperature, large fluctuations such as overshoot and undershoot may occur when the sensor is attached.

[0237] Taking these factors into consideration, it is preferable to appropriately set in the threshold generating unit 635 a first threshold value "threshold value at the start of wearing," a second threshold value "threshold value when stationary," a third threshold value "threshold value during exercise," a fourth threshold value "threshold value due to high or low environmental temperature," etc.

[0238] For example, during exercise, SNR and noise degradation are likely to occur in the ECG and heat flow in the first place. The threshold value must be raised compared to when stationary, but it is necessary to detect SNR and noise degradation caused by deterioration of ECG electrodes, heat flow pads, belts, clothing, and other components that only appear during exercise. By detecting the amount of exercise while observing heart rate, deep temperature, acceleration, environmental temperature, etc., and changing the threshold value as appropriate, it is possible to determine whether to reattach the device or clean or replace it.

[0239] When stationary, the SNR and noise are relatively stable. By recording the SNR and noise when stationary each time a measurement is made and observing the changes during daily use, it is also possible to judge the deterioration of the aforementioned components over time. If cleaning is recommended at a certain frequency and the deterioration continues without recovery even after cleaning, observing such changes over time will enable accurate judgment of the deterioration that requires replacement.

[0240] Since the SNR and noise deteriorate at startup and when the environmental temperature changes, it is advisable to determine the first through fourth thresholds mentioned above by combining the values ​​of the ECG, heat flow pad, acceleration sensor, and environmental sensor.

[0241] The output unit 640 notifies the user or administrator of instructions to reinstall the part, or to encourage cleaning or replacement. Regarding part replacement, a notification can be sent to the customer support department to encourage the support department to take action.

[0242] Furthermore, if there is a problem such as frequent reattachment, it is possible to prompt support from customer support, such as checking the size, applying water to the ECG electrodes, etc. These can be performed by the user's administrator.

[0243] By looking at the operation history of each sensor unit, such as the ECG measurement unit 611 and the heat flow measurement unit 612, particularly the history when the sensor unit is stationary, it is possible to determine and predict changes over time, as described above, and this information can be included in notifications to users, administrators, and customer support. [Explanation of symbols]

[0244] 1,2,… ECG electrode 11(11a,11b) Thermometer 110,210 ECG measurement section 120,220 R wave extraction section 121 Signal Calculation Unit 122 Wave removal section 130,230 SNR calculation section 131 SNR comparison section 140,240 RRI output section 150,250 Frequency analysis section 231 SNR / electrode comparison section 232 SNR / Threshold Comparison Unit 233 Weight synthesis unit 234 R wave re-extraction section 301 Belt 310 cases 330 Substrate 401 Clothing Fabric 410 GND wiring 411 Coated conductor (signal line) 421 ECG electrode 423 Spring material 432 Insulation 500(500a,500b,…) Heat flow measurement section 510 Deep temperature calculation section 520 Noise Calculation Unit 530 Noise Comparison Section 531 Noise measurement section comparison section 532 Noise / Threshold Comparison Unit 533 Weight synthesis unit 540 Deep temperature output section

Claims

[Claim 1] An ECG measurement unit that acquires an electrocardiogram signal from a body surface of a living body; a heat flow measuring unit for measuring a heat flow between the inside of the living body and the environment; an acceleration measuring unit for measuring acceleration due to movement of a living body; an environmental measurement unit that measures an environmental condition surrounding the living body selected from temperature, humidity, atmospheric pressure, wind speed, atmospheric composition, and latitude and longitude; an ECG-SNR comparator that calculates a signal-to-noise ratio of the electrocardiogram signal and compares it with a predetermined first threshold value that is set at the start of wearing the device as an initial value; A deep temperature-noise comparison unit that calculates noise contained in the heat flow measured by the heat flow measurement unit and compares it with a predetermined second threshold value set when the living body is stationary as an initial value; a threshold generating unit that detects an amount of motion of the living body from the acceleration measured by the acceleration measuring unit and the environmental state measured by the environmental measuring unit when the living body is moving, and changes the first threshold value and / or the second threshold value according to the amount of motion; an output unit that outputs a notification signal based on the comparison results from the ECG-SNR comparison unit and the deep temperature-noise comparison unit; A biological signal processing device comprising:

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