Biological information acquisition device and biological state warning system using the same

Abstract

To inexpensively provide a biological information acquisition device that can accurately measure biological signals without interfering with daily life.SOLUTION: A biological information acquisition device 1 acquires biological information about a measured person H1 and comprises: a pair of measurement pad parts 3 that can measure biological signals; and a body frame 2 that applies the same urging force in a direction where the measurement pad parts 3 get close to each other in a state of being applied to each indent E1 at the back of the ear of the subject H1. A biological signal processing unit 4 is connected to each of the measurement pad parts 3. The biological signal processing unit 4 performs computation processing on the biological signals measured by the respective measurement pad parts 3 and extracts biological information.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a biometric information acquisition device that acquires the biometric information of a person being measured, and in particular to a biometric information acquisition device that calculates a stress index by accurately and simultaneously acquiring multiple pieces of biometric information such as the person being measured's heart rate and respiratory rate, and monitors the person's physical and mental condition, and a biometric condition warning system using the same. [Background technology]

[0002] Conventionally, there has been known a bioinformation acquiring device that measures bioinformation to monitor the mental and physical state of a person to be measured. For example, a bioinformation acquiring device disclosed in Patent Document 1 is configured to insert a measuring tool with a built-in bone-flesh-conducted sound sensor (microphone) into the external ear canal of a person to be measured, and acquire bone-flesh-conducted sound, which is a biosignal, with the bone-flesh-conducted sound sensor. The bone-flesh-conducted sound includes blood vessel sounds caused by the beating of the person's heart and respiratory sounds caused by the respiratory movement of the lungs, and the blood vessel sounds and respiratory sounds are extracted from the bone-flesh-conducted sound to check the mental and physical state of the person to be measured.

[0003] However, the biological information acquiring device of Patent Document 1 needs to insert a measurement tool into the left and right ear canals of the subject. Therefore, when biological information is acquired over a long period of time, the subject may have difficulty hearing external sounds due to the measurement tool inserted into the ear canal, which may cause inconvenience in daily life.

[0004] To avoid this, the measurement tool of Patent Document 1 includes a tool body with a hollow portion formed therein that facilitates the transmission of external sound, and an outside air-conducted sound microphone and an outside air-conducted sound speaker are attached to the tool body. The outside sound collected by the outside air-conducted sound microphone is output from the outside air-conducted sound speaker, so that the outside sound can be transmitted to the subject even when the measurement tool is inserted into the ear canal. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2020-121120 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, in Patent Document 1, the incorporation of an air-conducted sound microphone and the like into the measurement tool increases the number of parts and complicates the structure, resulting in problems of increased costs.

[0007] In addition, since the measurement tool of Patent Document 1 is simply inserted into the ear canal during measurement, it is difficult to fix the measurement position of the measurement tool, and the relative positional relationship between the measurement tool and the ear canal is likely to vary. Therefore, the signal strength of the biosignal measured in the ear canal is likely to change, making it difficult to obtain accurate measurement data.

[0008] Furthermore, in Patent Document 1, a measurement tool must be inserted into the ear canal during measurement, and the measurement act itself may be stressful for the person being measured, which may result in failure to obtain accurate measurement data on vascular sounds and respiratory sounds that should be obtained.

[0009] The present invention has been made in view of the above-mentioned circumstances, and an object of the present invention is to provide an inexpensive bioinformation acquiring device capable of accurately measuring biosignals without interfering with daily life. [Means for solving the problem]

[0010] In order to achieve the above object, the present invention is characterized in that a biosignal is measured while applying the same biasing force to the left and right eye.

[0011] Specifically, the present invention is directed to a biological information acquiring device that acquires biological information of a subject, and the following solution has been taken.

[0012] That is, the first invention is characterized by comprising a pair of measurement pad parts capable of measuring a biosignal, a force application part which applies the same force in a direction in which the measurement pad parts approach each other while being placed against each of the subject's shadows, and a biosignal processing part which is connected to each of the measurement pad parts and performs arithmetic processing of the biosignal measured by each of the measurement pad parts to extract the bioinformation.

[0013] In the second invention, in the first invention, the measurement pad section includes a body-conducted sound sensor capable of measuring a body-conducted sound signal, and the biological signal processing section includes a low-pass filter section that passes only signals having a frequency lower than a predetermined frequency of the body-conducted sound signal measured by the body-conducted sound sensor and extracts them as heart rate fluctuations (heart rate fluctuations), and a high-pass filter section that passes only signals having a frequency higher than the predetermined frequency and extracts them as respiratory rate fluctuations (respiratory fluctuations).

[0014] In a third invention, in the second invention, the biological signal processing unit is configured to calculate a stress index SI at every preset time T by SI=σRR / σHR, where σHR is the fluctuation in heart rate extracted by the low-pass filter unit and σRR is the fluctuation in respiratory rate extracted by the high-pass filter unit, and to output a stress index matrix M in which the stress index SI and the evaluation value W of the subjective evaluation item input in advance by the subject for each time T are arranged in rows in order, and the time axis is arranged as columns.

[0015] In a fourth invention, in the third invention, the measurement pad section is provided with a temperature sensor capable of measuring the surface temperature (body temperature) of the person being measured, and the biological signal processing section is configured to arrange the surface temperatures (body temperatures) measured by the temperature sensor every time T elapses as rows in the stress index matrix M, and to output the time axis as columns.

[0016] The present invention is also directed to a biological condition warning system for displaying the stress states of a plurality of subjects, and provides the following solutions.

[0017] That is, the fifth invention is characterized in that it comprises a plurality of biometric information acquisition devices described in the third invention which are respectively worn by a plurality of subjects, an artificial intelligence or an external database which outputs an estimated stress state of each subject based on each stress index matrix M, and a management server which is connected to each of the biometric information acquisition devices and the artificial intelligence or external database via a communication network, judges the stress state of each subject based on each stress index matrix M received from the biometric information acquisition device and each estimated stress state input by the artificial intelligence or external database, generates biometric state information according to the judgment results, and transmits each biometric state information to the corresponding biometric information acquisition device via the communication network.

[0018] In a sixth invention, in the fifth invention, the biometric information warning system further includes an identity verification means capable of verifying whether the person being measured is the person in question, and when the identity verification means confirms that the person is the person in question, the management server transmits the biometric status information to the corresponding biometric information acquisition device.

[0019] A seventh invention is the sixth invention, characterized in that the personal identification means is a face authentication system using an image captured by a camera. Effect of the Invention

[0020] In the first invention, the measurement pads are applied to the subject's respective slits to measure the biosignals, so there is no need to insert a measurement tool into the ear canal as in Patent Document 1, and there is no need to cover the ears. Therefore, the subject does not have difficulty hearing sounds during the measurement of the biosignals, and even if the measurement is performed for a long period of time, it does not interfere with the subject's life, and the measurement act itself does not cause stress to the subject, so that a biosignal that is less affected by disturbances can be obtained. In addition, since there is no need to incorporate an air-conducted sound speaker or an air-conducted sound microphone into the measurement part, or to provide a cavity in the measurement part, the number of parts can be reduced to make the structure simple, and the device can be provided at a low cost. Furthermore, the biasing force applying part applies the same biasing force to each measurement pad in the direction of approaching each other to the subject's slits, so that the measurement positions of each measurement pad are fixed with a constant pressure and are not easily displaced. Therefore, the measurement signal strength of the obtained biosignal becomes constant, and the measurement accuracy can be improved.

[0021] In the second aspect of the present invention, the heart rate and respiratory rate fluctuations of the subject are obtained in time series, so that the condition of the subject can be evaluated using the obtained heart rate data and respiratory rate data.

[0022] In the third invention, stress is displayed quantitatively, and it is possible to check the subject's stress state and the subject's subjective assessment in a time series manner by checking the stress index matrix M. Therefore, it becomes easier to evaluate the subject's stress state, and the subject's time series state can be evaluated comprehensively.

[0023] In the fourth invention, the subject's heart rate and respiration rate data are measured, and at the same time, the subject's surface temperature is also measured. Therefore, by examining the correlation between the subject's heart rate and respiration rate data and the surface temperature, abnormal measurement data can be eliminated, and measurement accuracy can be improved. In addition, the subject's surface temperature data can be output in chronological order to the matrix elements of the stress index matrix M that quantitatively displays stress and pain, so that stress evaluation can be performed in more dimensions, and the subject's stress state can be accurately determined.

[0024] In the fifth invention, the stress index matrix M of the subjects can be transmitted to the management server via a communication network, so that the management server can simultaneously determine the stress state of each subject every time T elapses based on the received stress index matrix M of the subjects. In addition, the management server is connected to an artificial intelligence or an external database that outputs an estimated stress state of each subject based on the stress index matrix M of each subject, so that it generates biological state information according to the stress state determination result based on the output of the estimation. Then, the management server can transmit each biological state information to a corresponding biological information acquisition device via the communication network. Therefore, each subject wearing a biological information acquisition device can receive appropriate biological state information at an optimal timing via the communication network.

[0025] In the sixth aspect of the present invention, only when the identity verification means verifies that the subject is the subject, the management server transmits the biological condition information to the corresponding biological information acquisition device. Therefore, the biological condition information is not transmitted to a biological information acquisition device other than the subject by mistake, so that the personal information of the subject is not leaked to a third party other than the subject, and the personal information and privacy of the subject can be protected.

[0026] In the seventh invention, a face recognition system using an image captured by a camera is used as the identity verification means, making it possible to reliably and inexpensively verify the identities of multiple subjects with a relatively simple configuration. [Brief description of the drawings]

[0027] [Figure 1] FIG. 1 is a diagram illustrating a state in which a biometric information acquiring device according to a first embodiment of the present invention is used. [Diagram 2] FIG. 1 is a perspective view of a measuring device in a biological information acquisition device according to a first embodiment of the present invention. [Diagram 3] 1 is a block diagram of a biological information acquiring device according to a first embodiment of the present invention. [Figure 4] 3 is a diagram showing a stress index matrix calculated by the biological information acquiring device according to the first embodiment of the present invention. FIG. [Diagram 5] FIG. 4 is a diagram showing an operation flow of the biometric information acquiring device according to the first embodiment of the present invention. [Figure 6] FIG. 11 is a diagram showing a stress warning system according to a second embodiment of the present invention. [Figure 7] FIG. 11 is a conceptual diagram of artificial intelligence in a stress warning system according to a second embodiment of the present invention. [Figure 8] FIG. 11 is a diagram showing an example in which a biometric information acquisition device according to embodiment 3 of the present invention is applied to a COVID-19 detection system. [Figure 9] FIG. 11 is a diagram showing an example of an evaluation result obtained by a COVID-19 detection system to which a biometric information acquisition device according to embodiment 3 of the present invention is applied. [Figure 10] FIG. 13 is a diagram showing a stress index matrix in a COVID-19 detection system to which a biometric information acquisition device according to embodiment 3 of the present invention is applied. [Figure 11] FIG. 10 is a view corresponding to FIG. 1 according to a fourth embodiment of the present invention. [Figure 12] FIG. 11 is a diagram showing an online medical consultation system according to a fifth embodiment of the present invention. [Figure 13] FIG. 13 is a diagram showing a death time prediction system according to a sixth embodiment of the present invention. [Figure 14] FIG. 13 is a conceptual diagram of artificial intelligence in a death time prediction system according to embodiment 6 of the present invention. [Figure 15]FIG. 13 is a diagram illustrating a death time prediction system according to a sixth embodiment of the present invention. [Figure 16] FIG. 13 is a diagram showing a disaster occurrence reporting system according to a seventh embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, in which: It should be noted that the following description of the preferred embodiments is merely exemplary in nature.

[0029] First Embodiment of the Invention 1 to 3 show a bioinformation acquisition device 1 according to a first embodiment of the present invention. The bioinformation acquisition device 1 calculates a stress index for monitoring the mental and physical state of a subject H1 based on a plurality of biosignals acquired from each eye E1 of the subject H1, and includes a measurement device 10A that measures the biosignals, and an information processing terminal 10B that is wirelessly connected to the measurement device 10A.

[0030] The measuring device 10A has a generally horseshoe-shaped flexible main body frame 2 (biasing force application part). The main body frame 2 is formed by covering a metal spring with resin, or by a resin spring, etc., and when one end portion and the other end portion are separated from each other, the same biasing force is applied in the direction of approaching each other.

[0031] A gravity sensor 2a capable of detecting the direction of gravity is embedded in the middle of the main body frame 2, and the gravity sensor 2a is adapted to detect the inclination angle of the main body frame 2.

[0032] A pair of measurement pads 3 capable of measuring a biosignal of a subject are embedded in opposing portions at one end and the other end of the main body frame 2.

[0033] The measurement pad portion 3 is provided with a temperature sensor 3b which is a thermistor that comes into contact with each of the shadows E1 of the person to be measured H1 during measurement, and the temperature sensor 3b has a substantially disk-like and lid-like shape.

[0034] A measurement opening 3d communicating with the inside is formed on the mutually opposing surfaces of each temperature sensor 3b.

[0035] The temperature sensor 3b accommodates a body-conducted sound sensor 3a having an electret condenser microphone (ECM) and a wireless transceiver unit 3c connected to the body-conducted sound sensor 3a, the temperature sensor 3b, and the gravity sensor 2a. In other words, the temperature sensor 3b covers the body-conducted sound sensor 3a, the body-conducted sound sensor 3a, the temperature sensor 3b, and the gravity sensor 2a.

[0036] The wireless transceiver unit 3c is configured to wirelessly transmit and receive signals between the biological signal processing unit 4, and is configured to transmit, for example, each sensor signal measured by the body-conducted sound sensor 3a, the temperature sensor 3b, and the gravity sensor 2a through the measurement opening 3d to the information processing terminal 10B.

[0037] 1, when the main frame 2 is attached to the subject H1 so as to surround the back of the head and each measurement pad section 3 is applied to each of the shadows E1, the main frame 2 applies the same biasing force to each of the measurement pad sections 3 toward each of the shadows E1 of the subject H1. Note that the main frame 2 may be attached to the subject H1 so as to surround the lower jaw from the front of the head, and each measurement pad section 3 may be applied to each of the shadows E1.

[0038] As shown in FIG. 3, the information processing terminal 10B includes a biosignal processing unit 4 that performs arithmetic processing of each biosignal acquired by the measurement pad unit 3, an input unit 8 that is connected to the biosignal processing unit 4 and that can input necessary information via an electrostatic induction touch panel, an output unit 9 that is connected to the biosignal processing unit 4 and that can display evaluation results, etc. on a display, and a communication interface unit 11 that performs communication between the biosignal processing unit 4 and an external server.

[0039] The input unit 8 allows the subject H1 to input an evaluation value W of a subjective evaluation item such as stress, pain, etc. Examples of subjective evaluation items include a visual analog scale (VAS), a numeric rating scale (NRS), and a 10-point evaluation of mood.

[0040] The biological signal processing unit 4 has a wireless transceiver unit 5 that transmits and receives signals with the wireless transceiver unit 3c of the measurement pad unit 3, a body-conducted sound signal processing unit 6 that processes the body-conducted sound signal acquired by the body-conducted sound sensor 3a, and a stress index matrix calculation unit 7 that outputs a stress index matrix M that can grasp the stress state of the person being measured.

[0041] The wireless transmitting / receiving section 5 is wirelessly connected to the wireless transmitting / receiving section 3c of the measurement pad section 3, and is adapted to receive, for example, a sensor signal transmitted by the wireless transmitting / receiving section 3c.

[0042] When the inclination angle of the measurement pad portion 3 detected by the gravity sensor 2a is within a predetermined threshold, the biological signal processing portion 4 determines that the measuring device 10A is attached to the subject H1 in the correct posture and outputs a measurement start signal to each measurement pad portion 3 to measure the body-conducted sound signal and the body temperature signal.

[0043] The body-conducted sound signal processing unit 6 includes an acoustic heart rate measuring unit 61 and an acoustic respiration rate measuring unit 62 connected to the wireless transmitting / receiving unit 5 and the stress index matrix calculating unit 7, respectively.

[0044] The acoustic heart rate measurement unit 61 includes a low-pass filter unit 61a that passes only low frequency components of the waveform output from the wireless transmission / reception unit 5, and an acoustic heart rate calculation unit 61b that extracts the heart rate and its fluctuations from the output waveform obtained by the low-pass filter unit 61a. The acoustic heart rate calculation unit 61b outputs the extracted heart rate and its fluctuations to the stress index matrix calculation unit 7 as output σHR.

[0045] The acoustic respiration rate measurement unit 62 includes a high-pass filter unit 62a that passes only high frequency components of the waveform output from the wireless transceiver unit 5, and an acoustic respiration rate calculation unit 62b that extracts the respiration rate and its fluctuations from the output waveform obtained by the high-pass filter unit 62a. The acoustic respiration rate calculation unit 62b outputs the extracted respiration rate and its fluctuations as output σRR to the stress index matrix calculation unit 7.

[0046] The stress index matrix calculation section 7 receives the output σHR from the acoustic heart rate calculation section 61b and the output σRR from the acoustic respiration rate calculation section 62b, and calculates the stress index SI according to SI=σRR / σHR.

[0047] In addition, the stress index matrix calculation unit 7 outputs a stress index matrix M to the output unit 9 based on the calculated stress index SI and the subjective assessment value W input by the input unit 8, and the output unit 9, having received the stress index matrix M, displays the stress index matrix M on the display.

[0048] Furthermore, the stress index matrix calculation unit 7 outputs the stress index matrix M to an external server via the communication interface unit 11.

[0049] As shown in FIG. 4, the stress index matrix M is a matrix in which objective evaluation items including the stress index SI for the subject's stress, pain, etc. at each time T and the subjective evaluation item evaluation value W input by the subject himself / herself at each time T are arranged in order as rows in a vertical vector, and the vertical vector is arranged in columns in the horizontal direction of the time axis. The objective evaluation items are not limited to the stress index SI, and may include, for example, the subject's blood pressure and body temperature. By increasing the evaluation items, multidimensional evaluation of stress and pain becomes possible, and more precise evaluation can be performed. For example, the stress index matrix M in FIG. 4 is a matrix in which the subjective evaluation value VAS, the 10-point mood evaluation, the stress index SI, the blood pressure, the body temperature, and the evaluation values ​​W of the quantified behavior and observation items at each time t, t1, t2, ... are arranged as rows, and the vertical vector is arranged in the horizontal direction in the order of time t, t1, t2, ....

[0050] Next, the operation of the biometric information acquiring device 1 according to the first embodiment of the present invention will be described in detail with reference to FIG.

[0051] First, the subject H1 wears the measuring device 10A so that the measuring pads 3 are in contact with the left and right shadows E1, and starts the biometric information acquisition device 1. Then, the gravity sensor 2a detects the inclination angle of the measuring device 10A with respect to the subject H1 (S1). For example, when the measuring pads 3 are correctly attached to the left and right shadows E1 of the subject H1, the gravity sensor 2a detects the gravity of the vertical downward direction in the negative direction of the Z axis of the gravity sensor 2a. However, when the subject H1 wears the measuring device 10A so that the left and right shadows E1 are reversed, the up and down of the main frame 2 are reversed, so the gravity sensor 2a detects the direction of gravity in the positive direction of the Z axis. In this way, the left and right attachment states of the measuring pads 3 can be known from the gravity sensor value detected by the gravity sensor 2a.

[0052] When the gravity sensor value by the gravity sensor 2a is within a predetermined threshold value (for example, Z<0), the biosignal processor 4 determines that each measurement pad unit 3 is normally attached to the subject H1, and outputs a measurement start signal to the body-conducted sound sensor 3a and the temperature sensor 3b. Then, the body-conducted sound sensor 3a and the temperature sensor 3b execute waveform acquisition of the body sound and body temperature of the subject H1. On the other hand, when the biosignal processor 4 determines that each measurement pad unit 3 is not normally attached to the subject H1, the biosignal processor 4 does not output a measurement start signal to the body-conducted sound sensor 3a and the temperature sensor 3b, and waveform acquisition by the body-conducted sound sensor 3a and the temperature sensor 3b is not executed (S2). In this way, only the waveform data of the body sound and body temperature acquired when the measuring device 10A is normally attached to the subject H1 is transmitted to the biosignal processor 4 by the wireless transceiver 3c.

[0053] The acquired waveform data of the body sound is input to the body-conducted sound signal processing unit 6 via the wireless transmission / reception unit 5. From the acquired body sound, a low-pass signal (signal similar to heart sound) is extracted by the low-pass filter unit 61a in the acoustic heart rate measurement unit 61, while a high-pass signal (signal similar to respiratory sound) is extracted by the high-pass filter unit 62a in the acoustic respiratory rate measurement unit 62. That is, the waveform data of the body sound is separated into waveform data of the heart rate and the respiratory rate (S3). After that, the acoustic heart rate calculation unit 61b performs envelope detection and waveform peak acquisition from the low-frequency passing signal, and calculates the acoustic heart rate and its fluctuation σHR from its period. Also, the acoustic respiratory rate calculation unit 62b performs envelope detection and respiratory start point detection from the high-frequency passing signal to calculate the acoustic respiratory rate and its fluctuation σRR (S4).

[0054] Next, the subject H1 operates the touch panel of the input unit 8 to input an evaluation value W using a visual analog scale (VAS), a numerical rating scale (NRS), and a mood rating scale as subjective evaluation items of the subject H1's stress and pain at preset intervals T (S5).

[0055] Thereafter, in the stress index matrix calculation unit 7, a stress index SI is calculated as SI=σRR / σHR for the acoustic heart rate fluctuation (heart rate fluctuation) σHR and the acoustic respiration rate fluctuation (respiration fluctuation) σRR calculated every time T passes. In addition, the stress index SI, the evaluation value W input by the input unit 8, and the subject's body temperature measured by the temperature sensor 3b are arranged in order as rows in a vertical vector, and a stress index matrix M is calculated by arranging the vertical vectors as columns in the horizontal direction of the time axis (S6).

[0056] Then, the calculated stress index matrix M is displayed on the display by the output unit 9 (S7).

[0057] Thereafter, if the acquisition of the biometric information is to be completed, the biometric information acquisition device 1 is shut down. On the other hand, if the acquisition of the biometric information is not to be completed, the process returns to S1 and the above operations are repeated (S8).

[0058] Thus, according to the first embodiment of the present invention, the measurement pads 3 are applied to the respective shadows E1 of the subject H1 to measure the biosignals, so there is no need to cover the ears. Therefore, the subject H1 does not have difficulty hearing sounds during the measurement of the biosignals, and even if the measurement is performed for a long period of time, it does not interfere with the subject's life, and the measurement act itself does not cause stress to the subject H1, so that a biosignal that is less affected by disturbances can be obtained. In addition, since it is not necessary to incorporate an outside air conduction sound speaker or an outside air conduction sound microphone in the measurement part, or to provide a cavity in the measurement part, the number of parts can be reduced to make the structure simple, and the device can be provided at a low cost. Furthermore, the main frame 2 applies the same biasing force to the respective shadows E1 of the subject H1 in the direction of approaching each other, so that the measurement positions of the measurement pads 3 are fixed with a constant pressure and are not easily displaced. Therefore, the measurement signal strength of the obtained biosignal becomes constant, and the measurement accuracy can be improved.

[0059] In addition, since the main frame 2 is equipped with a gravity sensor 2a, the inclination angle of each measuring pad section 3 worn by the subject H1 can be known. Therefore, it is possible to know whether the measuring pad section 3 is correctly measuring the left and right shadows E1 of the subject H1, and it is possible to prevent erroneous measurement of the biosignal. In addition, since the posture of the subject H1 wearing the measuring pad section 3 can be known, measurement data when the posture of the subject H1 is abnormal can be removed, and the measurement accuracy can be improved.

[0060] In addition, since the measurement pad unit 3 includes the body-conducted sound sensor 3a, the heart rate and respiratory rate of the subject H1 can be obtained in time series. Therefore, the condition of the subject H1 can be evaluated using the obtained heart rate data and respiratory rate data.

[0061] Furthermore, since the biological signal processor 4 calculates the stress index matrix M, stress is displayed quantitatively, and it is possible to check the stress state of the subject H1 and the subject's subjective assessment in a time series manner together by checking the stress index matrix M. Therefore, it becomes easier to evaluate the stress state of the subject H1, and it is possible to comprehensively evaluate the time series state of the subject H1.

[0062] In addition, the input unit 8 of the biological signal processing unit 4 enables easy input of subjective evaluation items, which are part of the stress index matrix M, from a visual analog scale (VAS), a numerical rating scale (NRS), and a mood rating scale, making it easy to grasp the stress and pain of the subject H1.

[0063] In addition, since the measurement pad section 3 is equipped with a temperature sensor 3b, the body temperature of the subject H1 can be measured at the same time as the heart rate and respiration rate data of the subject H1 are measured. Therefore, by examining the correlation between the heart rate and respiration rate data of the subject H1 and the body temperature, abnormal measurement data can be eliminated, and the measurement accuracy can be improved. In addition, since the body temperature data of the subject H1 can be output in chronological order to the matrix elements of the stress index matrix M that quantitatively indicates stress and pain, stress evaluation can be performed in more dimensions, and the stress state of the subject H1 can be accurately determined.

[0064] In addition, since the temperature sensor 3b is a thermistor located in an area that comes into contact with each of the subject's shadows E1 during measurement, the sensitivity of the signal obtained from each of the subject's shadows E1 is improved, making it possible to know the stress state of the subject H1 in even more detail.

[0065] In addition, since the temperature sensor 3b is shaped like a lid, the temperature sensor 3b covers the body-conducted sound sensor 3a. This eliminates the need to attach an additional cover part to protect the body-conducted sound sensor 3a, making it possible to keep parts costs low.

[0066] Second Embodiment of the Invention 6 shows a stress warning system 100 (biological condition warning system) according to a second embodiment of the present invention using a biological information acquiring device 1. The same parts as those in the first embodiment are given the same reference numerals, and only the different parts will be described.

[0067] The stress warning system 100 is capable of simultaneously determining the stress state of multiple subjects A, B, and C who live far away from each other, and is composed of a bio-information acquisition device 1, a repeater 12, artificial intelligence 13, an external database 14, and a stress management server 15, with the stress management server 15 being connected to the repeater 12, the artificial intelligence 13, and the external database 14, and the repeater 12 being connected to the bio-information acquisition device 1 and the stress management server 15.

[0068] The biological information acquiring device 1 of the second embodiment is attached to each of the subjects A to C. For convenience, hereinafter, the biological information acquiring devices 1 attached to the subjects A to C will be referred to as biological information acquiring devices 1A, 1B, and 1C.

[0069] The artificial intelligence 13 and external database 14 are configured to input the stress index matrix M for each of the subjects A to C obtained by the bio-information acquisition device 1, and output the latest estimated stress state of the subjects A to C by learning based on the time series data or by comparing with similar data from the past.

[0070] The artificial intelligence 13 and the external database 14 may be neural networks. For example, the neural network in Fig. 7 includes an input layer that inputs objective data such as the subject's heart rate variability σHR, respiratory variability σRR, body temperature, blood pressure, social distance, dosage of medication, administration method, and other medication information, and subjective data such as cough and taste disorder, a two-layer hidden layer, and an output layer that outputs the need for a PCR test for COVID-19 infection.

[0071] The stress management server 15 is configured to determine the stress state of each of the subjects A to C based on each stress index matrix M obtained by the biometric information acquisition device 1 and the estimated stress state output by the artificial intelligence 13 or the external database 14.

[0072] In addition, the stress management server 15 generates stress warning information (biological condition information) according to the judgment results of each of the subjects A to C, and transmits the generated stress warning information to the repeater 12.

[0073] The repeater 12 is a hub device that transmits and receives data between the biometric information acquisition devices 1A, 1B, 1C and the stress management server 15, and transmits each stress index matrix M received from the biometric information acquisition devices 1A to 1C to the stress management server 15, while transmitting stress warning information received from the stress management server 15 to the biometric information acquisition devices 1A to 1C.

[0074] The repeater 12 may be a communication router or a switch.

[0075] Next, the operation of the stress warning system 100 according to the second embodiment of the present invention will be described. The biological information acquisition devices 1A, 1B, and 1C attached to the subjects A, B, and C respectively output the stress index matrix M for each time T as described above. The repeater 12 receives the stress index matrix M of the subjects A, B, and C via the communication interface unit 11 of each biological information acquisition device 1A, 1B, and 1C, and transmits it to the stress management server 15. The stress management server 15 inputs each received stress index matrix M to the artificial intelligence 13 or the external database 14. Then, the artificial intelligence 13 or the external database 14 calculates the estimated stress state of each subject A, B, and C based on each stress index matrix M, and outputs it to the stress management server 15. The stress management server 15 judges the stress state of each subject A, B, and C based on the estimated stress state and the stress index matrix M. Then, the stress management server 15 generates stress warning information corresponding to each of the judgment results of the subjects A to C, and then transmits each piece of stress warning information to the repeater 12. The repeater 12 transmits each piece of stress warning information received from the stress management server 15 to the biological information acquisition devices 1A, 1B, and 1C of the subjects A, B, and C, respectively.

[0076] Thus, according to the second embodiment of the present invention, the stress index matrix M of the subjects A, B, and C can be transmitted to the stress management server 15 via the repeater 12, so that the stress management server 15 can determine the stress state of each of the subjects A, B, and C every time time T elapses. In addition, the stress management server 15 is connected to the artificial intelligence 13 or the external database 14 that outputs the estimated stress state of each of the subjects A, B, and C based on the stress index matrix M of each of the subjects A, B, and C, so that it can generate stress warning information according to the stress state determination result based on the estimated output and transmit it to the repeater 12. Therefore, each of the subjects A, B, and C wearing the bioinformation acquisition device 1 can receive appropriate stress warning information at an optimal timing via the repeater 12.

[0077] Third Embodiment of the Invention 8 shows a part of a COVID-19 detection system 200 (biological condition warning system) including a biological information acquisition device 1 according to embodiment 3 of the present invention. The same parts as those in embodiment 1 are denoted by the same reference numerals, and only the different parts will be described.

[0078] The COVID-19 detection system 200 comprises a biometric information acquisition device 1 and a temperature sensor TS that can be attached to the forehead of the subject H1, and is configured to measure the body temperature at the left and right sides of the subject H1 using a measuring instrument 10A of the biometric information acquisition device 1, and to measure the body temperature at the forehead of the subject H1 using the temperature sensor TS.

[0079] 9 shows the left and right overcast surface temperatures (body temperature) of subject H1 acquired by biometric information acquisition device 1, the left and right difference in the acquired overcast surface temperatures of subject H1, the forehead surface temperature (body temperature) of subject H1 measured by temperature sensor TS, and the subjective evaluation of pharyngeal discomfort, respectively, when subject H1 is a patient infected with COVID-19 and when he or she is a healthy person. For both subjects H1, the left and right overcast surface temperatures and the forehead surface temperature are close in value, so each measurement result can be determined to be valid.

[0080] It was found that COVID-19 patients (moderate I and mild severity) with a large difference in the left and right obscured air surface temperature reported feeling discomfort in the pharynx, while COVID-19 patients and healthy subjects with a small difference in the left and right obscured air surface temperature reported no discomfort in the pharynx. In other words, there was a correlation between the left and right difference in the obscured air surface temperature of subject H1 and the discomfort in the pharynx caused by COVID-19, and it was confirmed that observing the left and right difference in obscured air surface temperature is effective in detecting COVID-19 infection.

[0081] FIG. 10 shows a stress index matrix used in the COVID-19 detection system 200. The left and right side surface temperatures of the subject H1 can be input as components of the vertical vector of the stress index matrix. This makes it possible to evaluate stress and pharyngeal discomfort caused by COVID-19, and to detect whether the subject H1 is infected with COVID-19 without contact.

[0082] Furthermore, if it is necessary to protect the personal information and privacy of the subject H1, the identity of the subject H1 may be confirmed (authenticated) when connecting the biometric information acquisition devices 1A, 1B, and 1C to the stress management server 15. The stress management server 15 may confirm whether or not the subject H1 is the subject himself / herself, and upon receiving a confirmation signal indicating that the subject is the subject, receive the stress index matrix from the biometric information acquisition devices 1A, 1B, and 1C, detect whether or not the subject H1 is infected with COVID-19, and transmit the result of the determination as to whether or not a PCR test is required to the corresponding biometric information acquisition device.

[0083] In the third embodiment, the forehead of the subject H1 is measured by the temperature sensor TS. However, measuring the forehead of the subject H1 with the temperature sensor TS is not essential and is optional.

[0084] Fourth embodiment of the invention 11 shows a biometric information acquiring device 1 according to a fourth embodiment of the present invention. This biometric information acquiring device 1 is the same as that of the first embodiment except that an output unit 9 is provided on a main body frame 2. Therefore, the same parts as those of the first embodiment are denoted by the same reference numerals, and only the different parts will be described.

[0085] The output section 9 according to the fourth embodiment is composed of a red light emitting section Lr, a yellow light emitting section Ly, and a green light emitting section Lg provided on the surface of the main body frame 2 opposite to the side facing the subject H1.

[0086] The biological signal processor 4 according to the fourth embodiment is configured to make any one of the red light emitting unit Lr, the yellow light emitting unit Ly, and the green light emitting unit Lg emit light based on the result of comparing the stress index SI calculated by the stress index matrix calculator 7 with a preset threshold. For example, the red light emitting unit Lr emits light when the stress index SI of the subject H1 exceeds +20% of the preset threshold, while the green light emitting unit Lg emits light when the stress index SI of the subject H1 falls below -20% of the preset threshold. In addition, the yellow light emitting unit Ly emits light when the stress index SI of the subject H1 is in the range of -20% to 20% of the preset threshold, so that the magnitude of the stress index SI can be confirmed by the difference in the color of the emitted light. Therefore, the stress index SI of multiple subjects H1 can be accurately and simultaneously determined efficiently from a distant position.

[0087] In addition, the output section 9 of embodiment 4 allows the stress index SI of the subject H1 to be confirmed from a distant location by illuminating any one of the red light-emitting section Lr, the yellow light-emitting section Ly, and the green light-emitting section Lg, but is not limited to this. The stress index SI of the subject H1 may also be confirmed from a distant location by generating an alarm sound or voice.

[0088] Moreover, although the output section 9 in the fourth embodiment is provided on a part of the main body frame 2, it is not limited thereto, and may be provided on the entire surface of the main body frame 2 so that the entire main body frame 2 emits light.

[0089] Fifth embodiment of the invention FIG. 12 shows an online medical examination system 300 (biological condition warning system) according to the fifth embodiment of the present invention. The online medical examination system 300 uses a communication network 32 and camera-equipped communication terminals SA, SB, SC including a smartphone, tablet, etc. owned by each patient (subject) instead of a repeater 12 to connect an online medical examination server 15 and biological information acquisition devices 1A, 1B, 1C of each patient A, B, C. In addition, the online medical examination system 300 differs from the second embodiment in that identity confirmation (authentication) is possible using the cameras of the camera-equipped communication terminals SA, SB, SC, and SD owned by each patient A, B, C, and doctor I. Since the rest of the second embodiment is the same as the second embodiment, the same reference numerals are used for the same parts as the second embodiment, and only the other different parts will be described.

[0090] The communication interface unit 11 of the biometric information acquisition device 1 according to the fifth embodiment of the present invention is provided with a wireless communication circuit including Bluetooth (registered trademark) and NFC (Near Field Communication) circuits, and is configured to be connectable to a camera-equipped communication terminal having the same circuit. That is, the biometric information acquisition devices 1A, 1B, and 1C of the patients A, B, and C are uniquely connected to the camera-equipped communication terminals SA, SB, and SC of the patients A, B, and C via wireless communication. The camera-equipped communication terminals SA, SB, and SC of the patients A, B, and C are connected to the Internet via a communication network 32, while the online medical care server 15 is connected to the communication network 32 via the Internet, and is capable of acquiring the stress index matrix M from the biometric information acquisition devices 1A, 1B, and 1C of the patients A, B, and C via the communication network 32. Therefore, the online medical care system 300 does not need to provide a dedicated repeater 12 for connecting the biometric information acquisition devices 1A, 1B, and 1C to the online medical care server 15, and can be a simple and inexpensive system.

[0091] The camera-equipped communication terminal SD of doctor I is connected to the Internet via the communication network 32. When the biometric information acquisition devices 1A, 1B, 1C are connected to the online medical care server 15, the online medical care system 300 is capable of verifying the identity of each patient A, B, C using the camera-equipped communication terminals SA, SB, SC and the camera-equipped communication terminal SD of doctor I. That is, the online medical care server 15 receives a verification signal indicating the identity of the patient A, B, C and doctor I using a face authentication system that uses images of the patients A, B, C and doctor I taken by the cameras of the camera-equipped communication terminals. Upon receiving the verification signal, the online medical care server 15 receives the stress index matrix M from the biometric information acquisition devices 1A, 1B, 1C and transmits the generated biometric condition information to the corresponding biometric information acquisition devices 1A, 1B, 1C. The generated biometric condition information is not transmitted to a biometric information acquisition device other than the patient A, B, C, so that the personal information of each patient A, B, C is not leaked to a third party other than the patient A, B, C, and the patient's personal information and privacy can be protected. The face authentication system can use a known technology.

[0092] The communication network 32 may be the Internet. The communication network 32 may include a local area network, a mobile communication network, or a Virtual Private Network (VPN).

[0093] Furthermore, the biometric information acquisition devices 1A, 1B, 1C are adapted to acquire distance information between the camera-equipped communication terminals SA, SB, SC by wireless communication, and store this acquired distance information as social distance data between each of the patients A, B, C. Therefore, when the artificial intelligence 13 of the online medical treatment system 300 outputs an estimated stress state, the above-mentioned social distance data can be used as objective data.

[0094] In addition, by using images captured by the cameras of the camera-equipped communication terminals SA, SB, and SC of each patient A, B, and C, doctor I can check the light emission state of the output section 9 of the biometric information acquisition device 1 and the patient's complexion, etc. through the screen, allowing the online medical care server 15 to generate more appropriate biometric condition information.

[0095] In the above description, the identity verification means is a face authentication system that uses an image captured by the camera of the camera-equipped communication terminals SA, SB, SC, SD. However, the identity verification means is not limited to this, and other means may be used, such as a fingerprint authentication system using a fingerprint sensor (not shown) built into the camera-equipped communication terminal, a vein authentication system using a vein shape pattern using an infrared sensor (not shown), or a voiceprint authentication system using a human voiceprint using a voice sensor (not shown).

[0096] Sixth embodiment of the invention 13 shows a time of death prediction system 400 (biological condition warning system) according to embodiment 6 of the present invention. The time of death prediction system 400 is the same as embodiment 2 except that the stress management server 15, the artificial intelligence 13, and the external database 14 of embodiment 2 are replaced by a time of death prediction management server 45, an artificial intelligence 43, and an external database 44, respectively. Therefore, the same reference numerals are used for the same parts as embodiment 2, and only the different parts will be described.

[0097] The time of death prediction system 400 predicts the time of death for patients D, E, and F who are the diagnosis targets.

[0098] The artificial intelligence 43 and external database 44 are configured to input the stress index matrix M of each target patient obtained by the biometric information acquisition devices 1D, 1E, and 1F attached to the target patients D, E, and F, respectively, and output the latest estimated time of death (biological condition information) of the target patient by learning based on the time series data or by comparing with similar data from the past.

[0099] 14 shows an artificial intelligence 43, which is a neural network dedicated to predicting the time of death. The artificial intelligence 43 includes an input layer that receives objective data such as the heart rate variability σHR, respiratory variability σRR, gravity, velocity, angular velocity, body temperature, and biomagnetic force of the target patient, and subjective data such as the doctor's findings, a hidden layer consisting of three layers, and an output layer that outputs the estimated time of death.

[0100] Figure 15 shows a typical change over time in the stress index for a target patient. A correlation was observed in which the stress index SI for a target patient initially declines over time and then rises approximately 72 hours before the time of death, and it was confirmed that this is effective in estimating the time of death. Therefore, the artificial intelligence 43 can predict the time of death by inputting objective data including the stress index SI of the target patient and subjective data from the doctor.

[0101] According to the death time prediction system 400, by predicting the time of death of the target patients D, E, and F, it is possible to encourage anticipatory grieving for the patients' families and to alleviate psychological distress during the dying period.

[0102] Seventh embodiment of the invention 16 shows a disaster occurrence notification system 500 (biological condition warning system) according to the seventh embodiment of the present invention. The disaster occurrence notification system 500 is the same as the fifth embodiment except that the stress management server 15, the artificial intelligence 13, and the external database 14 of the fifth embodiment are replaced by a disaster occurrence notification management server 55, an artificial intelligence 53 dedicated to disaster occurrence notification, and an external database 54, respectively. Therefore, the same reference numerals are attached to the same parts as the fifth embodiment, and only the different parts will be described.

[0103] The disaster occurrence notification system 500 is configured to notify an emergency vehicle 56 of a request for rescue when a disaster or the like occurs to a person being measured.

[0104] The disaster occurrence report management server 55 is connected to an emergency vehicle 56 via the communication network 32 or a predetermined communication line.

[0105] Furthermore, the artificial intelligence 53 and the external database 54 are configured to receive the stress index matrix M of each of the subjects A, B, C obtained by the biological information acquisition devices 1A, 1B, 1C, and output the latest estimated disaster status (biological status information) of the subjects A, B, C to the disaster occurrence report management server 55 by learning based on the time series data or by comparing with similar past data. The disaster occurrence report management server 55 is also configured to determine the estimated disaster status of each of the subjects A, B, C, and transmit disaster occurrence information RQ including a rescue request according to the determination result to the emergency vehicle 56.

[0106] For example, when subjects A, B, C are affected by a disaster, the bioinformation acquisition devices 1A, 1B, 1C worn by subjects A, B, C transmit the stress index matrix M of subjects A, B, C to the disaster occurrence report management server 55 via the communication network 32 using the camera-equipped communication terminals SA, SB, SC uniquely connected by wireless communication. The disaster occurrence report management server 55 inputs the received stress index matrix M to the dedicated artificial intelligence 53 or the external database 54. The dedicated artificial intelligence 53 or the external database 54 then calculates the estimated disaster conditions of subjects A, B, C based on the stress index matrix M and outputs the calculated results to the disaster occurrence report management server 55. The disaster occurrence report management server 55 determines the rescue priority of subjects A, B, C based on the received estimated disaster conditions and performs a predetermined report operation.

[0107] For example, the disaster occurrence report management server 55 receives estimated disaster states from subjects A, B, and C, such as "Needs rescue 3" with low rescue priority, "Needs rescue 2" with medium rescue priority, and "Needs rescue 1" with high rescue priority. The disaster occurrence report management server 55 first transmits disaster occurrence information RQ about subject C with high rescue priority and location information of subject C by the camera-equipped communication terminal SC to the emergency vehicle 56. Next, the disaster occurrence report management server 55 transmits the same information about subject B with medium rescue priority to the emergency vehicle 56, and finally transmits the same information about subject A with low rescue priority to the emergency vehicle 56. In this way, the disaster occurrence report management server 55 can accurately transmit disaster occurrence information RQ promptly to the emergency vehicle 56 according to the rescue priority of the affected subjects A, B, and C.

[0108] Furthermore, the disaster occurrence report management server 55 transmits the report result to the emergency vehicle 56, including the disaster occurrence information RQ, to the biological information acquisition devices 1A, 1B, and 1C of the corresponding subjects A, B, and C.

[0109] According to embodiment 7 of the present invention, a disaster occurrence reporting system 500 can be provided that can send timely and accurate reports to multiple subjects A, B, and C when a disaster occurs using biological information acquisition devices 1A, 1B, and 1C.

[0110] Furthermore, by reconstructing the user's platform, this system can also be applied to online medical consultations based on contactless acquired biological status information, remote medical care, management of intractable diseases (such as triglyceride accumulation cardiovascular disease: TGCV), community-based comprehensive care systems, hospital ships (systems), and service provider selection systems.

[0111] In the bioinformation acquiring device 1 according to the first to seventh embodiments of the present invention, as shown in Figs. 2 and 3, the measurement pads 3 are integrally molded on both ends of the main body frame 2, and the other components, the biosignal processor 4, the input unit 8, the output unit 9, and the communication interface unit 11, are configured as separate housings, but they may be configured as the same housing. For example, by configuring the body-conducted sound signal processor 6 of the biosignal processor 4 as the same housing as the main body frame 2 and the measurement pad unit 3, it is not necessary to transmit and receive the sensor signal via the wireless transmitter-receivers 3c and 5. Therefore, the communication overhead required for transmitting the sensor signal to the biosignal processor 4 is not required, and the communication volume can be reduced, so that the communication band can be suppressed.

[0112] In addition, the biometric information acquisition device 1 has been described as being in contact with the left and right acupuncture points E1 of the subject H1, but this is not limited thereto, and the measurement pad portion 3 may be in contact with acupuncture points (acupuncture points) such as the acupuncture points on the left and right sides of the subject H1.

[0113] Further, the biometric information acquiring device 1 has been described as having a pair of measuring pad parts 3, but is not limited thereto, and may have one or three or more measuring pad parts 3, and each measuring pad part 3 may be in contact with one or three or more acupuncture points (pressure points). For example, the biometric information acquiring device 1 may have only one measuring pad part 3, and the measuring pad part 3 may be in contact with an acupuncture point (pressure point) such as Danzhong of the subject H1.

[0114] Furthermore, when the body-conducted sound signal processing unit 6 receives a sensor signal via the wireless transceiver unit 5, the body-conducted sound signal processing unit 6 may input a Fourier-transformed signal obtained by Fourier-transforming the sensor signal for a predetermined period of time (e.g., 30 seconds) to the acoustic heart rate measuring unit 61 and the acoustic respiration rate measuring unit 62. From the Fourier-transformed signal, a low-pass signal is output by the low-pass filter unit 61a, and a high-pass signal is output by the high-pass filter unit 62a. Since the low-pass signal and the high-pass signal are further subjected to an inverse Fourier transform to obtain respective periods, it is possible to extract the fluctuations in the heart rate and the fluctuations in the respiration rate based on the derived periods. [Explanation of symbols]

[0115] 1, 1A, 1B, 1C Biometric information acquisition device 2 Main body frame (biasing force application part) 2a Gravity sensor 3. Measuring pad section 3a Body-conducted sound sensor 3b Temperature Sensor 4. Biological signal processing section 12 Repeater 13. Artificial Intelligence 14 External Databases 15 Stress Management Server 32 Communication Network 43 Artificial Intelligence 44 External Databases 45 Death time prediction management server 53 Artificial Intelligence 54 External Database 55 Disaster occurrence report management server 61a Low-pass filter section 62a High-pass filter section 100 Stress warning system (biological condition warning system) 200 COVID-19 Detection System (Biological Status Warning System) 300 Online medical treatment system (biological condition warning system) 400 Time of Death Prediction System (Biological Condition Warning System) 500 Disaster occurrence notification system (biological condition warning system) SA, SB, SC, SD Camera-equipped communication terminal

Claims

1. A biometric information acquisition device that acquires biometric information of a subject from left and right eye contact, A pair of measurement pads capable of measuring a biological signal; a biasing force applying unit that applies the same biasing force in a direction in which the measurement pads approach each other while the measurement pads are placed against the respective shadows of the subject; a biological signal processing unit connected to each of the measurement pad units and processing the biological signals measured by each of the measurement pad units to extract the biological information; A biological information acquiring device characterized by predicting a time of death based on the biological information.

2. 2. The biometric information acquisition device according to claim 1, The biometric information acquisition device further includes a gravity sensor. The bioinformation acquisition device is characterized in that the biosignal processing unit outputs a measurement start signal to the measurement pad portion when the gravity sensor detects that the tilt angle of the measurement pad portion is within a predetermined threshold value.

3. 2. The biometric information acquisition device according to claim 1, The measurement pad unit includes a body-conducted sound sensor capable of measuring a body-conducted sound signal, The bio-information acquisition device is characterized in that the bio-signal processing unit includes a low-pass filter unit that passes only signals having a frequency lower than a predetermined frequency of the body-conducted sound signal measured by the body-conducted sound sensor and extracts them as heart rate fluctuations (heartbeat fluctuations), and a high-pass filter unit that passes only signals having a frequency higher than the predetermined frequency and extracts them as respiratory rate fluctuations (respiratory fluctuations).

4. 4. The biometric information acquisition device according to claim 3, The bio-information acquisition device is characterized in that the bio-signal processing unit is configured to calculate a stress index SI at every predetermined time T by SI = σRR / σHR, where σHR is the fluctuation in heart rate extracted by the low-pass filter unit and σRR is the fluctuation in respiratory rate extracted by the high-pass filter unit, and to output a stress index matrix M in which the stress index SI and the evaluation value W of the subjective evaluation item input in advance by the subject for each time T are arranged in rows in order, and the time axis is the column.

5. 5. The biometric information acquisition device according to claim 4, The measurement pad unit includes a temperature sensor capable of measuring a surface temperature of the person to be measured, The bioinformation acquisition device is characterized in that the biosignal processing unit is configured to arrange the surface temperatures measured by the temperature sensor every time the time T elapses as rows in the stress index matrix M, and output the time axis as columns.

6. The biological information acquiring device according to claim 5, which is attached to each of a plurality of subjects; An artificial intelligence or an external database that outputs an estimated stress state of each subject based on each stress index matrix M; A biological condition warning system comprising a management server that is connected to each of the biological information acquisition devices and the artificial intelligence or external database via a communication network, judges the stress state of each measured person based on each stress index matrix M received from the biological information acquisition device and each estimated stress state input by the artificial intelligence or external database, generates each biological condition information including a predicted time of death according to the judgment result, and transmits each biological condition information to the corresponding biological information acquisition device via the communication network.

7. 7. The biological condition warning system according to claim 6, The test subject may further include an identity verification means for verifying whether the subject is the subject himself / herself, A biological condition warning system, wherein the management server transmits the biological condition information to the corresponding biological information acquiring device when the identity of the person is confirmed by the identity confirmation means.

8. 8. The biological condition warning system according to claim 7, 2. A biological condition warning system, wherein the identity verification means is a face authentication system using an image captured by a camera.

9. In the biological condition warning system according to any one of claims 6 to 8, A biological condition warning system, characterized in that the predicted time of death is set to a time a predetermined time after the point in time when the stress index SI changes from a decrease to an increase over time.

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