Biological information detection system, and biological information detection method

Abstract

To provide a biological information detection system capable of improving detection accuracy of biological information while detecting the biological information in a non-contact manner.SOLUTION: A biological information detection system 1 includes an information acquisition part 41, an evaluation part 64, a signal selection part 65, and an estimation part 66. The information acquisition part 41 acquires a plurality of signal information showing each of a plurality of reflection waves. The plurality of reflection waves are reflected at a plurality of mutually different positions. The evaluation part 64 evaluates each periodicity of the plurality of signals based on each wave information of the plurality of signals. The signal selection part 65 selects from a plurality of signals a signal determined to secure reliability showing biological information on the basis of the evaluation result by the evaluation part 64. The estimation part 66 uses the signal selected by the signal selection part 65 and estimates biological information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a biological information detection system and a biological information detection method. [Background technology]

[0002] There is known a technology for contactlessly detecting biometric information relating to a living body such as a human or animal (for example, Patent Document 1). Patent Document 1 describes acquiring signal information relating to the movement of the living body, and detecting the biometric information contactlessly based on the acquired signal information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-127398 Summary of the Invention [Problem to be solved by the invention]

[0004] A technology has been developed to detect biological information by irradiating a living body with a pulse wave as a transmission wave, acquiring signal information based on the wave reflected from the living body, and processing the acquired signal information. The "living body" includes, for example, humans and animals. For example, it has been considered to detect the living body's heartbeat, breathing, or the like as biological information by acquiring a Doppler signal from the living body using a Doppler sensor.

[0005] However, the non-contact detection of biometric information as described above is more susceptible to noise than the contact detection of biometric information, making it difficult to ensure the accuracy of the detection of biometric information. For example, noise occurs due to the propagation of transmitted and reflected waves between the sensor and the living body. This noise or the posture of the living body may reduce the accuracy of the detection of biometric information from the signal information.

[0006] Furthermore, in detecting the above-mentioned biometric information, it is difficult to determine which reflected wave information from the living body should be used to derive the biometric information. If the biometric information is not derived based on appropriate reflected wave information, the detection accuracy of the biometric information decreases. For example, if the position of the living body is not known in advance, even if information on multiple reflected waves reflected at different positions is acquired, it is difficult to determine the reflected wave information to be used to derive the biometric information. Even if the position of the living body before detection of the biometric information is known, the reflected wave information suitable for deriving the biometric information may change over time due to body movement, changes in the living body's posture, etc.

[0007] An object of one aspect of the present invention is to provide a biometric information detection system that can improve the detection accuracy of biometric information while detecting biometric information in a non-contact manner.An object of another aspect of the present invention is to provide a biometric information detection method that can improve the detection accuracy of biometric information while detecting biometric information in a non-contact manner. [Means for solving the problem]

[0008] A biological information detection system according to one aspect of the present invention includes an information acquisition unit, an evaluation unit, a signal selection unit, and an estimation unit. The information acquisition unit acquires information on a plurality of signals each representing a plurality of reflected waves. The plurality of reflected waves are reflected waves reflected at a plurality of different positions. The evaluation unit evaluates the periodicity of each of the plurality of signals based on waveform information of each of the plurality of signals. The signal selection unit selects, from the plurality of signals, a signal that is determined to have sufficient reliability to indicate biological information based on the evaluation result by the evaluation unit. The estimation unit estimates the biological information using the signal selected by the signal selection unit.

[0009] A biological information detection method according to another aspect of the present invention includes the steps of: acquiring information on a plurality of signals each representing a plurality of reflected waves; evaluating the periodicity of each of the plurality of signals based on the waveform information of each of the plurality of signals; selecting a signal from the plurality of signals that is determined to have sufficient reliability to represent biological information based on the evaluation result of the periodicity of each of the plurality of signals; and estimating the biological information using the selected signal. The plurality of reflected waves are reflected waves reflected at a plurality of different positions. [Effects of the Invention]

[0010] One aspect of the present invention provides a biometric information detection system that can improve the detection accuracy of biometric information while detecting biometric information in a non-contact manner. Another aspect of the present invention provides a biometric information detection method that can improve the detection accuracy of biometric information while detecting biometric information in a non-contact manner. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a block diagram of a biological information detection system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a schematic diagram of a biological information detection system. [Figure 3] 10A and 10B are diagrams illustrating an example of the relationship between a transmitted wave signal and a received reflected wave signal. [Figure 4] FIG. 4 is a diagram illustrating the relationship between a reflected wave and a signal receiving unit. [Figure 5] FIG. 1 illustrates a data set. [Figure 6] FIG. 10 is a diagram showing pixels corresponding to a plurality of selected regions. [Figure 7] FIG. 10 is a diagram showing a correlation information image. [Figure 8] FIG. 10 is a diagram showing a correlation information image. [Figure 9] FIG. 10 is a diagram illustrating an example of an autocorrelation function. [Figure 10] FIG. 2 is a diagram illustrating an example of a hardware configuration of a signal processing unit of the biological information detection system. [Figure 11]10 is a flowchart illustrating an example of a biological information detection method. [Figure 12] 10 is a flowchart illustrating an example of a biometric information derivation process. [Figure 13] 10 is a flowchart illustrating an example of a signal evaluation process. [Figure 14] 10A and 10B are diagrams illustrating verification results of the biological information detection system according to the present embodiment. [Figure 15] 10A and 10B are diagrams illustrating verification results of the biological information detection system according to the present embodiment. [Figure 16] 10A and 10B are diagrams illustrating verification results of the biological information detection system according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] [1] A biological information detection system according to an embodiment of the present disclosure includes an information acquisition unit, an evaluation unit, a signal selection unit, and an estimation unit. The information acquisition unit acquires information on a plurality of signals each representing a plurality of reflected waves. The plurality of reflected waves are reflected waves reflected at a plurality of different positions. The evaluation unit evaluates the periodicity of each of the plurality of signals based on waveform information of each of the plurality of signals. The signal selection unit selects, from the plurality of signals, a signal determined to have sufficient reliability to indicate biological information based on the evaluation result by the evaluation unit. The estimation unit estimates the biological information using the signal selected by the signal selection unit.

[0013] In the biometric information detection system in [1] above, the periodicity of each of the plurality of signals is evaluated based on waveform information of each of the plurality of signals, and a signal is selected from the plurality of signals based on the evaluation result. The selected signal is a signal that is determined to have a reliability that indicates biometric information. The estimation unit estimates the biometric information using the selected signal. In this case, since the periodicity has been evaluated, the accuracy of selecting a signal with a reliability that has been ensured can be improved. As a result, the accuracy of detecting the biometric information can be improved while detecting the biometric information without contact.

[0014] [2] In the biometric information detection system of [1] above, the evaluation unit may include a peak detection unit that detects peaks in the signals. The evaluation unit may evaluate the periodicity of each of the multiple signals based on the detection results of the peak detection unit. In this case, the detection accuracy of the biometric information can be further improved.

[0015] [3] In the biological information detection system of [1] or [2] above, the evaluation unit may acquire an autocorrelation function of each of the plurality of signals based on waveform information of each of the plurality of signals. The evaluation unit may evaluate the periodicity of each of the plurality of signals based on the autocorrelation function. In this case, the detection accuracy of the biological information can be further improved.

[0016] [4] In the biometric information detection system of [3] above, the evaluation unit may include a peak detection unit that detects peaks in the autocorrelation function. The evaluation unit may evaluate the periodicity of each of the multiple signals based on the detection results of the peak detection unit. In this case, the detection accuracy of the biometric information may be further improved.

[0017] [5] In the biometric information detection system of [2] or [4] above, the peak detection unit may detect a peak within a predetermined time range for each of the multiple signals. If only one peak is detected within the predetermined time range, the signal selection unit may select the signal from which only one peak was detected as a signal determined to have sufficient reliability to represent biometric information. In this case, the detection accuracy of the biometric information can be further improved.

[0018] [6] In the biometric information detection system of [5] above, the peak detection unit may detect peaks within a predetermined time range for each of the multiple signals. When multiple peaks are detected within the predetermined time range, the signal selection unit may compare a second peak with a first peak within the predetermined time range. When the comparison results in the second peak being smaller than the first peak and the value obtained by dividing the second peak by the first peak being smaller than a predetermined value, the signal selection unit may select the signal in which the multiple peaks are detected as a signal determined to have sufficient reliability to represent biometric information. In this case, the detection accuracy of the biometric information can be further improved.

[0019] [7] In the bioinformation detection system according to any one of [1] to [6] above, each of the plurality of signals may be a reconstructed signal obtained by decomposing each of a plurality of input signals, each representing a plurality of reflected waves, into a plurality of decomposed signals, and reconstructing the decomposed signals based on the energy of each decomposed signal. In this case, the detection accuracy of the bioinformation can be further improved.

[0020] [8] In the biometric information detection system of [7] above, the input signal may be an I / Q signal. The decomposed signal may be an IMF signal. In this case, the detection accuracy of the biometric information can be further improved.

[0021] [9] The biometric information detection system according to any one of [1] to [8] above may further include a biometric information selection unit and a biometric information acquisition unit. When a plurality of signals are selected by the signal selection unit, the biometric information selection unit may select the biometric information estimated by the estimation unit. The biometric information acquisition unit may acquire the biometric information selected by the biometric information selection unit. In this case, the detection accuracy of the biometric information may be further improved.

[0022]

[10] In the biometric information detection system of [9] above, the biometric information selection unit may select the biometric information estimated by the estimation unit using the signal with the maximum energy from among the biometric information estimated by the estimation unit using each of the multiple signals. In this case, the detection accuracy of the biometric information can be further improved.

[0023]

[11] In the biometric information detection system of [9] or

[10] above, when the estimation unit estimates biometric information a predetermined number of times or more for signals at different times, the biometric information selection unit may select an average value of the biometric information most recently estimated by the estimation unit. In this case, the detection accuracy of the biometric information can be further improved.

[0024]

[12] A biological information detection method according to an embodiment of the present disclosure includes acquiring information on a plurality of signals each representing a plurality of reflected waves, evaluating the periodicity of each of the plurality of signals based on the waveform information of each of the plurality of signals, selecting a signal from the plurality of signals that is determined to have sufficient reliability to represent biological information based on the evaluation result of the periodicity of each of the plurality of signals, and estimating the biological information using the selected signal. The plurality of reflected waves are reflected waves reflected at a plurality of different positions. [Details of the embodiments of the present disclosure]

[0025] Hereinafter, an embodiment of the biological information detection system of the present invention will be described in detail with reference to the drawings. In the description of the drawings, the same or corresponding parts will be given the same reference numerals, and duplicated explanations will be omitted. First, with reference to Figs. 1 to 9, a schematic configuration of the biological information detection system of the embodiment of the present invention will be described. Fig. 1 is a block diagram of the biological information detection system of this embodiment. Fig. 2 is a schematic diagram of the biological information detection system.

[0026] The biometric information detection system 1 detects biometric information related to a living organism in a non-contact manner. The "biometric information" refers to information about periodically repeated movements of the living organism, including, for example, heartbeat and breathing information. The biometric information detection system 1 irradiates the living organism with electromagnetic waves or sound waves and acquires information about multiple reflected waves from the living organism. The electromagnetic waves may include visible light. The "information about the reflected waves" refers to information indicating phase changes in the reflected waves. In other words, the "information about the reflected waves" refers to information indicating changes in the amplitude of the reflected waves over time. The biometric information detection system 1 detects biometric information by utilizing the diversity effect of the multiple reflected waves based on the acquired information about the multiple reflected waves. The biometric information detection system 1 detects biometric information by estimating multiple peaks indicating periods of time-varying biometric information based on the information about the multiple reflected waves. The "period of time-varying biometric information" refers to, for example, the period of the living organism's movements. For example, the period of the heartbeat or breathing is detected as biometric information. The biometric information detection system 1 includes a signal control unit 2 and a signal processing unit 3.

[0027] As shown in FIG. 2, the signal control unit 2 includes a sensor, such as a MIMO (Multiple-Input Multiple-Output) radar. The sensor is, for example, a MIMO FMCW (Frequency Modulated Continuous Wave radar) radar. The FMCW radar transmits microwaves toward an object and acquires a phase change of the microwaves according to the distance from the FMCW radar to the object. As a result, the distance from the FMCW radar to the object can be measured. The object includes a living body to be detected. The signal control unit 2 performs beamforming. The signal control unit 2 irradiates a transmission wave T, such as an electromagnetic wave or a sound wave, toward the living body and acquires information about a reflected wave R from the living body. The signal control unit 2 acquires information about a plurality of different reflected waves R.

[0028] The signal control unit 2 may be, for example, a Doppler radar. In this case, the signal control unit 2 detects biological information by observing a frequency shift caused by the Doppler effect. The signal control unit 2 includes a signal transmission unit 11 and at least one signal reception unit 12.

[0029] The signal transmitting unit 11 transmits a transmission wave T. The transmission wave T is, for example, an unmodulated continuous wave (CW). As shown in FIG. 2, the signal transmitting unit 11 includes a source 21, a power amplifier 22, and a transmitting antenna 23. The source 21 generates a signal of the transmission wave T to be transmitted from the transmitting antenna 23. The source 21 is an oscillation source that generates the signal of the transmission wave T. The power amplifier 22 amplifies the signal generated in the source 21. The transmitting antenna 23 converts the signal from the power amplifier 22 into a transmission wave T and transmits it toward the living body M.

[0030] The signal receiving unit 12 receives a reflected wave R of the transmitted wave T. The signal receiving unit 12 receives the reflected wave R from a living body M. The reflected wave R is modulated according to the biological information of the living body M. The signal receiving unit 12 includes a receiving antenna 31, a regulator 32, a mixer 33, a band-pass filter 34, a voltage gain control amplifier 35, and an AD converter 36. The receiving antenna 31 converts the modulated reflected wave R into a signal. The regulator 32 performs processing such as noise removal from the signal converted from the reflected wave R. The mixer 33 mixes the signal generated by the source 21 with the signal output from the regulator 32. The band-pass filter 34 removes noise from the signal generated by the mixer 33. The voltage gain control amplifier 35 amplifies the signal output from the band-pass filter 34. The AD converter 36 converts the signal output from the voltage gain control amplifier 35 from an analog signal to a digital signal. As a result, a digital signal containing information about the received signal is output from the signal receiving unit 12. The signal receiving unit 12 outputs the digital signal to the signal processing unit 3 .

[0031] FIG. 3 shows an example of the relationship between the transmission wave T transmitted from the signal transmitting unit 11 and the reflected wave R received by the signal receiving unit 12. For example, as shown in FIG. 3, the signal transmitting unit 11 linearly sweeps the frequency of the transmission wave to be transmitted. In FIG. 3, "f c " is the minimum sweep frequency, "B" is the bandwidth of the chirp, and "T c ” is the sweep duration, and “t d " is the time from transmitting the transmitted wave T to receiving the reflected wave R, and "f b " is the frequency difference between the transmitted wave T transmitted at a specified time and the reflected wave R received at the same specified time. In this case, the transmitted wave T transmitted from the signal transmitting unit 11 is expressed by equation (1). "s(t)" is information indicating the transmitted wave T, "A" is the signal strength, "t" is time, and "φ(t)" is an arbitrary parameter indicating the phase shift.

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[0032] The transmitted wave T is reflected by an obstacle such as a living body. The reflected wave R reflected by this obstacle is received by the signal receiving unit 12. The reflected wave R is expressed by equation (2). "r(t)" is information indicating the reflected wave R.

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[0033] “t d " is expressed by equation (3). "R(t)" is the distance between the signal control unit 2 and the position where the transmitted wave T is reflected. For example, "R(t)" is the distance between the FMCW radar and the position where the transmitted wave T is reflected.

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[0034] The signal receiving unit 12 applies a quadrature mixer to the signal corresponding to the received reflected wave R to obtain an in-phase signal and a quadrature signal. The in-phase signal and the quadrature signal have a phase difference of π / 2 relative to each other. The in-phase signal and the quadrature signal can be expressed as complex signals as shown in equation (4). "y(t)" is information indicating an I / Q signal. The I signal is a signal having an in-phase component that is in phase with the phase of the signal that generates the transmission wave T. The Q signal is a signal having a quadrature component that is orthogonal to the phase of the signal that generates the transmission wave T. "y(t)" is information indicating a complex signal that includes an in-phase component and a quadrature component.

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[0035] Here, the following equations (5) to (7) hold for "fb", "Φ(t)", and "Δφ(t)", respectively.

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[0036] "R(t)" is "R const " and "R l " is approximately expressed by the following equation (8). l " is the relative displacement between the signal control unit 2 and the living body, and corresponds to, for example, the movement of the chest due to heartbeat, breathing, etc. const " is the distance from the signal control unit 2 to the reference position of the living body. For example, "R l " is the relative displacement between the FMCW radar and the living body M, and "R const ” is the distance from the FMCW radar to the reference position of the living body. The relative displacement “R l" corresponds to fluctuations of the living body M, such as fluctuations in the chest wall caused by the heartbeat or breathing of the living body M. The reference position of the living body M is a position that serves as a reference for the above-mentioned relative displacement, and is, for example, the distance between the FMCW radar and the living body when there is no relative displacement.

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[0037] For this reason, “R const " can be estimated, information on the phase change of the reflected wave R due to the relative displacement of the living body M can be obtained.

[0038] FIG. 4 is a diagram showing the relationship between the reflected wave R and the signal receiving unit 12. As shown in FIGS. 2 and 4, for example, the transmitting antenna 23 and the multiple receiving antennas 31 are arranged in a straight line. In this case, a phase shift occurs in the received reflected wave R depending on the positions of the multiple receiving antennas 31. In FIG. 4, "θ" is the incident angle of the reflected wave R, "K" is the number of arranged receiving antennas 31, "k" is a variable indicating an arbitrary receiving antenna 31, and "d k " is the distance from the reference point P to the k-th receiving antenna 31 in the arrangement direction of the multiple receiving antennas 31. k (t)” is information indicating the reflected wave R received by the kth receiving antenna 31, and “w k " is the weight of the beamforming, and "Y(t)" is information indicating the reflected wave R corresponding to a specific beam direction. In this case, "y k (t)" is expressed by the following equation (9).

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[0039] "λ" is the wavelength of the reflected wave R. "Y(t)" is expressed by the following equation (10).

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[0040] Based on the above, “Rconst By specifying " and "θ", "R l In other words, if the distance from the signal control unit 2 to the reference position of the living body M and the incident angle of the reflected wave R are specified, the relative displacement between the signal control unit 2 and the living body M based on this reflected wave R can be calculated. For example, the distance "R(t)" between the FMCW radar and the position where the transmitted wave T is reflected can be calculated by frequency analysis of information Y(t) indicating the reflected wave R corresponding to a specific beam direction. By calculating "R(t)" at each predetermined time, the fluctuation "R l " can be calculated.

[0041] The signal transmitting unit 11 of the signal control unit 2 transmits the transmission wave T into space within a predetermined range. For example, the signal transmitting unit 11 transmits the transmission wave T in an azimuth at a predetermined angle in the up and down direction, with the part of the signal control unit 2 from which the transmission wave T is transmitted as the origin. In this embodiment, the signal transmitting unit 11 transmits the transmission wave T in an azimuth ranging from +45° to -45° in the up and down direction, with the transmitting antenna 23 of the signal control unit 2 as the origin. The up and down directions are both parallel to the vertical direction.

[0042] Similarly, the signal transmitter 11 transmits a transmission wave T in a direction at a predetermined angle in the left-right direction with the transmitting antenna 23 as the origin. The left and right directions are both orthogonal to the vertical direction and intersect with the propagation direction of the transmission wave T. For example, the transmission wave T is a single signal wave propagating in a space within a predetermined range. The signal transmitter 11 may transmit multiple signal waves independently at different angles or at different times. In this case, each of the multiple signal waves may be transmitted to a different range within the predetermined range.

[0043] The signal receiving unit 12 receives multiple reflected waves R. The multiple reflected waves R refer to, for example, received waves that reach the signal receiving unit 12 via different paths. For example, the multiple reflected waves R are reflected at different real space positions. Hereinafter, "real space positions" may also be simply referred to as "positions." The multiple reflected waves R reach the signal receiving unit 12 from, for example, different azimuths. In other words, the multiple reflected waves R have different angles of incidence with respect to the receiving antenna 31 of the signal receiving unit 12. The signal receiving unit 12 receives multiple reflected waves R that reach the receiving antenna 31 from a predetermined range of space. For example, the signal receiving unit 12 receives reflected waves R from azimuths at a predetermined angle in the vertical direction, with a reference point P as the origin. The reference point P is, for example, the center of gravity of the multiple receiving antennas 31. In this embodiment, the signal receiving unit 12 receives reflected waves R from azimuths ranging from +45° to -45° in the vertical direction, with the reference point P as the origin. In other words, the signal receiving unit 12 receives reflected waves R whose incident angles with respect to the receiving antenna 31 are in the range of +45° to −45° in both the vertical and horizontal directions.

[0044] Each reflected wave R is received, for example, by a plurality of different receiving antennas 31. For example, when the signal transmitting unit 11 transmits a plurality of transmission waves T having different frequencies, when the signal transmitting unit 11 transmits a plurality of transmission waves T at different times, or when the signal transmitting unit 11 transmits a plurality of transmission waves T to different positions, the plurality of reflected waves R may be received by a single receiving antenna 31. For example, the reflected wave R is modulated in accordance with the fluctuation x(t) of the chest wall caused by the heartbeat or breathing of the living body M. The fluctuation x(t) can be calculated by the above-mentioned "R l " is equivalent to

[0045] The signal processing unit 3 acquires information indicating biological information based on the signal acquired from the signal receiving unit 12. For example, the signal processing unit 3 processes the signal acquired by the signal receiving unit 12 to generate information indicating the biological information of the living organism M. As shown in FIG. 1 , the signal processing unit 3 includes an information acquiring unit 41, a correlation information calculating unit 42, an information selecting unit 43, and a biological information deriving unit 44.

[0046] The information acquiring unit 41 acquires information output from the signal receiving unit 12. For example, the information acquiring unit 41 performs various processes on the information acquired from the signal receiving unit 12 to generate a signal according to a frequency component corresponding to the detection target, and acquires information on the generated signal (hereinafter also referred to as "signal change information"). The information acquiring unit 41 acquires information on the reflected wave R selected by the information selecting unit 43. The information on the reflected wave R acquired from the information selecting unit 43 corresponds to information on a plurality of signals respectively indicating a plurality of reflected waves R reflected at a plurality of different positions. The information on the reflected wave R corresponds to information on a signal corresponding to the reflected wave R. The information on the reflected wave R corresponds to, for example, information on an I / Q signal corresponding to the reflected wave R.

[0047] The information acquisition unit 41 includes, for example, a signal acquisition unit 46 and a change information calculation unit 47. The signal acquisition unit 46 acquires a signal related to a reflected wave R from real space. The change information calculation unit 47 calculates signal change information based on the signal acquired by the signal acquisition unit 46. The information acquisition unit 41 acquires information from the outside and inside of the signal processing unit 3. The information acquisition unit 41 acquires, for example, information output from the signal receiving unit 12. The information acquisition unit 41 acquires, for example, information output from the information selection unit 43.

[0048] The information acquisition unit 41 acquires a plurality of pieces of signal change information corresponding to each of a plurality of different regions in real space. The plurality of regions are included in a detection range. The information acquisition unit 41 acquires signal change information of signals related to a plurality of reflected waves R reflected in the different regions. The signal change information includes information related to phase changes of the reflected waves R. The signal related to the reflected waves R corresponds to, for example, a signal indicating the reflected waves R.

[0049] The signal change information corresponding to each of the plurality of regions is based on signals detected by a sensor. The plurality of regions are ranges that differ from each other in at least one of distance and direction from the sensor. The signal change information corresponding to a region includes information regarding the reflected wave R from the region. Hereinafter, "signal change information corresponding to a region" will also be simply referred to as "signal fragmentation information of a region." The signal change information includes information indicating that a detection target or obstacle is located in the region corresponding to the signal change information.

[0050] The signal change information includes, for example, region information and at least one of power information and phase information. The region information is information indicating the position of the region. The region information includes information indicating the distance of the region from a reference point and the orientation corresponding to the reference point. The region information may be information indicating the positional relationship between multiple regions. The power information is information regarding the power of a signal corresponding to the region. The power information is, for example, information indicating the power of a signal related to the reflected wave R from the region corresponding to the signal change information. The phase information is, for example, the curve length of the trajectory of the I / Q signal described below.

[0051] For example, the information acquisition unit 41 acquires a plurality of pieces of signal change information corresponding to each of the plurality of regions for each time segment based on the sweep time of the sensor. For example, the change information calculation unit 47 calculates a plurality of pieces of signal change information corresponding to each of the plurality of regions based on the acquired signals. These plurality of regions correspond, for example, to a predetermined range of space to which the transmission wave T is transmitted by the signal transmission unit 11. These plurality of regions correspond, for example, to a range of positions where the plurality of reflected waves R arriving at the plurality of receiving antennas 31 are reflected. These plurality of regions are, for example, ranges in which at least one of the distance from a reference point and the orientation relative to the reference point differs from one another. The orientation relative to the reference point corresponds to an orientation centered on the reference point. The orientation relative to the reference point corresponds, for example, to the angle of incidence of the plurality of reflected waves R to the receiving antenna 31. The reference point is set, for example, at an arbitrary position. The reference point is, for example, the position of the sensor.

[0052] The change information calculation unit 47 performs, for example, a short-time Fourier transform (STFT) on the acquired signal information. In this specification, the term "short-time Fourier transform" refers to creating information for multiple time segments from input information and performing a Fourier transform for each time segment. For example, in the short-time Fourier transform, information for multiple time segments is created by multiplying the input information by a window function while shifting it. As a result, the change information calculation unit 47 converts the input information from the time domain to the frequency domain for each time segment using the short-time Fourier transform. Each time segment has, for example, the same time width.

[0053] The change information calculation unit 47 performs a short-time Fourier transform on the acquired signal information. In other words, the change information calculation unit 47 performs a short-time Fourier transform on each piece of acquired signal information. For example, the change information calculation unit 47 performs a short-time Fourier transform on the signal information corresponding to each of the different regions.

[0054] For example, the change information calculation unit 47 performs a short-time Fourier transform on the input information to calculate information indicating the power of each frequency for each time segment. For example, the change information calculation unit 47 performs a fast Fourier transform on the acquired signal information for each receiving antenna 31. For example, the change information calculation unit 47 uses a fast Fourier transform to calculate the distance from each receiving antenna 31 to the position where the reflected wave R received by that receiving antenna 31 is reflected. The change information calculation unit 47 uses beamforming to calculate signal information in each direction relative to a reference point based on information on multiple signals acquired by multiple receiving antennas 31. As a result, the change information calculation unit 47 calculates signal change information for each of the different regions. For example, the change information calculation unit 47 calculates signal power information related to the reflected wave R for each of the different regions. For example, the change information calculation unit 47 calculates the amplitude of the signal acquired by the signal acquisition unit 46 as power information of the signal change information.

[0055] For example, the change information calculation unit 47 decomposes the signal acquired by the signal acquisition unit 46 into multiple components and calculates, as phase information, a value related to the length of the signal trajectory in a space having each of the multiple components as its coordinate axis. For example, the information acquisition unit 41 calculates, as signal change information, the curve length of the I / Q signal trajectory based on the signal received by the signal reception unit 12. The I / Q signal trajectory corresponds to the line drawn when the time change of the I / Q signal is plotted in a plane space formed by an axis indicating the value of the I signal and an axis indicating the value of the Q signal. The I / Q signal trajectory corresponds to the trajectory of the signal phase change. The greater the phase deviation of the I / Q signal, the greater the curve length of the I / Q signal. The curve length of the I / Q signal based on the reflected wave R from the living body changes depending on the body movement of the living body. The curve length of the I / Q signal is expressed, for example, by the following equation (11). "TM" indicates the coherent processing interval.

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[0056] The change information calculation unit 47 calculates a signal data set DS1 for each time segment based on the acquired information of the multiple signals. As shown in FIG. 5, the signal data set DS1 includes multiple pieces of signal change information. The signal data set DS1 associates region information with at least one of power information and phase information. For example, the signal data set DS1 associates each region with phase information of the signal corresponding to that region. In this case, the change information calculation unit 47 creates a signal data set DS1 for multiple regions, associating each region with phase information. For example, the signal data set DS1 may associate each region with power information of the signal corresponding to that region.

[0057] The change information calculation unit 47 creates the signal data set DS1 based on, for example, a plurality of pieces of signal change information corresponding to reflected waves R from a predetermined range of directions in the left-right direction. In other words, the change information calculation unit 47 creates the signal data set DS1 by associating at least one of power information and phase information with each of a plurality of regions in a predetermined range of directions in the left-right direction. The change information calculation unit 47 creates the signal data set DS1 in a range of directions from +40° to −40° relative to a reference point, for example. As a variation of this embodiment, the change information calculation unit 47 may create the signal data set DS1 based on a plurality of pieces of signal change information in a predetermined range of directions in the up-down direction or a plurality of pieces of signal change information in a predetermined range of directions in the up-down and left-right directions.

[0058] The variation information calculation unit 47 creates the signal data set DS1 based on, for example, a plurality of pieces of signal variation information corresponding to reflected waves R from within a range of a predetermined distance from the reference point. In other words, the variation information calculation unit 47 creates the signal data set DS1 by associating at least one of power information and phase information with each of a plurality of regions within a range of a predetermined distance from the reference point. The variation information calculation unit 47 creates the signal data set DS1 based on, for example, a plurality of pieces of signal variation information corresponding to reflected waves R from within a range of 0 m to 9 m from the reference point.

[0059] The change information calculation unit 47 may form a signal information image V1 including a plurality of pixels, as shown in FIG. 5. The signal data set DS1 includes the signal information image V1. The signal information image V1 includes a plurality of pixels that are two-dimensionally arranged. The plurality of pixels of the signal information image V1 correspond to different regions in real space. The plurality of pixels of the signal information image V1 indicate signal change information in different regions in real space. Each pixel of the signal information image V1 corresponds to a piece of signal change information in the signal data set DS1. For example, the signal information image V1 indicates, for each pixel, signal change information of a signal related to a reflected wave R reflected in a region corresponding to the pixel.

[0060] The signal change information shown in each pixel of the signal information image V1 corresponds to, for example, the curve length of the trajectory of the I / Q signal described above. As a modification of this embodiment, the signal change information shown in each pixel may be power information indicating the energy or strength of the signal. Below, a case will be described in which the signal change information shown in each pixel is the curve length of the trajectory of the I / Q signal described above, and the curve length of the trajectory of the I / Q signal will be simply referred to as the "curve length."

[0061] The change information calculation unit 47 may create a traffic light information image V1 based on, for example, a signal data set DS1 created for each time segment. The change information calculation unit 47 may create multiple traffic light information images V1 for each time segment. In the traffic light information image V1, pixels with larger signal curve lengths are displayed brighter. In the traffic light information image V1, the vertical axis corresponds to the distance from the reference point, and the horizontal axis corresponds to the left-right orientation relative to the reference point.

[0062] The traffic light information image V1 shows the above-mentioned curve lengths at positions corresponding to a range of +40° to -40° in the left-right direction from the reference point as the origin. The traffic light information image V1 shows the above-mentioned curve lengths at positions corresponding to a range of 0 m to 9 m from the reference point as the origin.

[0063] The correlation information calculation unit 42 calculates correlation information between first signal change information selected from the plurality of signal change information and each of the plurality of second signal change information different from the first signal change information among the plurality of signal change information. The region corresponding to the first signal change information corresponds to the selected region. The region corresponding to the second signal change information corresponds to the reference region. The reference region is a region among the plurality of regions different from the selected region. In other words, the plurality of second signal change information corresponds to a plurality of reference regions among the plurality of regions different from the selected region corresponding to the first signal change information. The value of the correlation information is, for example, a correlation value. For example, the selected region and the reference region each correspond to one or more regions among the plurality of regions. For example, the plurality of reference regions are regions among the plurality of regions other than the selected region corresponding to the first signal change information. For example, the selected region corresponds to the first region, and the reference region corresponds to the second region.

[0064] The correlation information calculation unit 42 calculates a correlation map DS2 as shown in FIGS. 6 and 7. The correlation map DS2 includes correlation information for each region in the detection range. The correlation map DS2 includes a plurality of correlation values ​​between the selected first signal change information and a plurality of pieces of second signal change information that are different from the selected first signal information among the plurality of pieces of signal change information in the signal dataset DS1. In other words, the correlation map DS2 includes correlation values ​​between the first signal change information and each of the plurality of pieces of second signal change information that correspond to a plurality of reference regions that are different from the selected region among the plurality of regions. The correlation map DS2 associates each region with correlation information of the signal corresponding to that region.

[0065] For example, the correlation information calculation unit 42 determines a plurality of pieces of first signal change information from a plurality of pieces of signal change information included in the signal data set DS1. The correlation information calculation unit 42 calculates correlation information for each of the plurality of pieces of first signal change information. The correlation information calculation unit 42 calculates the correlation information based on, for example, the signal information image V1.

[0066] The correlation information calculation unit 42 determines, for example, multiple pieces of first signal change information from multiple pieces of signal change information in the signal dataset DS1 based on the signal change information for each region. For example, when the multiple pieces of signal change information in the signal dataset DS1 are sorted in descending order of signal change information value, the correlation information calculation unit 42 determines, as the first signal change information, the multiple pieces of signal change information having the top n signal change information values. In this case, n is a natural number. The number of pieces of first signal change information is smaller than the number of pieces of signal change information included in the signal dataset DS1. The multiple pieces of first signal change information indicate curve lengths that are greater than the curve lengths indicated by the signal change information other than the multiple first signal change information among the multiple pieces of signal change information included in the signal dataset DS1.

[0067] When multiple pieces of first signal change information are determined, the correlation information calculation unit 42 calculates multiple correlation maps DS2. Each of the multiple correlation maps DS2 includes multiple pieces of correlation information calculated for different pieces of first signal change information. In other words, the correlation information calculation unit 42 calculates a correlation map DS2 for each piece of first signal change information.

[0068] The calculation of correlation information will be described in further detail with reference to FIGS. 5 to 8. The signal data set DS1 includes a plurality of cells CE1 and CE2. For example, the cells CE1 and CE2 are arranged two-dimensionally. The correlation information calculation unit 42 selects at least one cell CE1 from the signal data set DS1. The cell CE1 includes signal change information corresponding to at least one region. The cell CE1 includes signal change information corresponding to one selected region. In other words, selecting the cell CE1 corresponds to selecting first signal change information. The cells CE1 and CE2 correspond, for example, to different regions.

[0069] For example, as shown in Fig. 5, the correlation information calculation unit 42 determines a plurality of mutually different cells CE1 from the signal data set DS1. The plurality of cells CE1 each contain signal change information of a mutually different selected region. Each cell CE1 contains, for example, at least one pixel in the signal information image V1. In the example shown in Fig. 5, each cell CE1 contains a plurality of pixels in the signal information image V1.

[0070] The correlation information calculation unit 42 calculates correlation information between the signal change information of the selected cell CE1 and the signal change information of the cell CE2. As shown in Fig. 6, the cell CE2 contains signal change information in the signal data set DS1 that is different from that of the selected cell CE1. The cell CE2 contains signal change information corresponding to at least one region. The cell CE2 contains signal change information corresponding to one reference region.

[0071] The correlation information calculation unit 42 calculates correlation information between the signal change information of the selected cell CE1 and the signal change information of each of the multiple cells CE2. The multiple cells CE2 each contain signal change information that is different from one another. Each of the multiple cells CE2 contains, for example, signal change information other than that of the selected cell CE1 in the signal data set DS1. The correlation information calculation unit 42 calculates correlation information for the selected cell CE1 for each cell CE2. Each cell CE2 contains, for example, at least one pixel in the signal information image V1. In the example shown in FIG. 6, each cell CE2 contains multiple pixels in the signal information image V1.

[0072] The correlation information calculation unit 42 calculates a correlation map DS2. The correlation map DS2 includes multiple pieces of correlation information between the signal change information of the selected cell CE1 and the signal change information of each of the multiple cells CE2. As shown in FIGS. 7 and 8, the correlation map DS2 includes a correlation map that indicates correlation information for each region in the detection range. For example, in the correlation map, correlation information values ​​with a correlation value of 0.4 or more are maintained, and correlation information values ​​with a correlation value of less than 0.4 are set to zero. Correlation information values ​​with a correlation value of less than 0.4 may be set to null. The information selection unit 43 updates the correlation map DS2 based on the correlation information calculated by the correlation information calculation unit 42.

[0073] The correlation information calculation unit 42 may form a correlation information image V2 including a plurality of pixels. The correlation map DS2 includes the correlation information image V2. The correlation information image V2 corresponds to the correlation map. In the correlation information image V2 shown in FIGS. 7 and 8, pixels with larger correlation information values ​​are displayed brighter. In the correlation information image V2, the vertical axis corresponds to the distance from the reference point, and the horizontal axis corresponds to the left-right orientation relative to the reference point.

[0074] The correlation information image V2 includes a plurality of pixels arranged two-dimensionally. The plurality of pixels of the correlation information image V2 correspond to different regions in real space. The plurality of pixels of the correlation information image V2 each indicate correlation information calculated for different second signal change information in the signal data set DS1. The correlation information indicated by each pixel corresponds to relative information between the signal change information corresponding to the pixel and the selected first signal change information. In other words, the plurality of pixels of the correlation information image V2 each indicate correlation information in different regions. For example, the plurality of pixels of the correlation information image V2 indicate correlation information between the cell CE2 and the cell CE1 corresponding to the pixel.

[0075] Each pixel in the correlation information image V2 corresponds to each piece of correlation information in the correlation map DS2. For example, multiple pixels included in the correlation information image V2 correspond to multiple pixels included in the signal information image V1. The position of each pixel in the correlation information image V2 corresponds to the position of a pixel in the signal information image V1 that was used to calculate the correlation information of that pixel. For example, when the signal information image V1 and the correlation information image V2 are superimposed, each pixel in the correlation information image V2 is arranged so as to overlap with the pixel in the signal information image V1 that corresponds to that pixel.

[0076] When multiple pieces of first signal change information are determined, the correlation information calculation unit 42 forms multiple correlation information images V2. Each correlation information image V2 includes multiple pieces of correlation information calculated for different pieces of first signal change information. In other words, the correlation information calculation unit 42 forms a correlation information image V2 for each piece of first signal change information.

[0077] The information selection unit 43 selects signal information to be used for detecting biological information based on the correlation information calculated in the correlation information calculation unit 42. For example, the information selection unit 43 selects cells CE1 and CE2 to be used for detecting biological information based on the correlation information calculated in the correlation information calculation unit 42 and the signal data set DS1. The information selection unit 43 selects cells CE1 and CE2 to be used for detecting biological information based on, for example, a correlation information image V2.

[0078] The information selection unit 43 updates the signal data set DS1 based on the correlation information calculated by the correlation information calculation unit 42, and selects cells CE1 and CE2 to be used for detecting biological information based on the updated signal data set DS1. For example, multiple pixels included in the signal information image V1 in the updated signal data set DS1 each indicate the above-mentioned curve lengths of the signal change information corresponding to different regions. The information selection unit 43 selects cells CE1 and CE2 to be used for detecting biological information based on the updated signal information image V1. For example, the information selection unit 43 selects cells CE1 and CE2 corresponding to the position of the detection target in real space.

[0079] The information selection unit 43 determines an area in real space where the detection target is not located, based on the correlation information calculated by the correlation information calculation unit 42. The information selection unit 43 determines whether the detection target is located in a selected area, based on the correlation information calculated by the correlation information calculation unit 42. For example, the information selection unit 43 determines an area where the detection target is not located from among the multiple selected areas, based on the correlation information calculated by the correlation information calculation unit 42. For example, the information selection unit 43 determines whether cell CE1 indicates signal change information of the detection target, based on the correlation information calculated by the correlation information calculation unit 42.

[0080] For example, the information selection unit 43 determines, based on a plurality of pieces of correlation information included in the correlation map DS2, whether or not the detection target is located in the first signal change information selected in the calculation of the correlation map DS2. When the correlation information calculation unit 42 calculates a plurality of correlation maps DS2 corresponding respectively to the plurality of pieces of first signal change information, the information selection unit 43 determines, based on the plurality of pieces of correlation information included in each correlation map DS2, whether or not the detection target is located in the first signal change information of each correlation map DS2.

[0081] For example, the information selector 43 evaluates the states of the multiple pieces of correlation information in the correlation map DS2 and detects the position of the detection target based on the evaluation results of the multiple pieces of correlation information. For example, the information selector 43 evaluates the states of the multiple pieces of correlation information in each of the multiple correlation maps DS2 and detects the position of the detection target based on the evaluation results of the multiple pieces of correlation information in each of the multiple correlation maps DS2. For example, the information selector 43 determines, based on the evaluation results of the multiple pieces of correlation information, whether the detection target is located in a selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2. In other words, the information selector 43 evaluates the states of the multiple pieces of correlation information for multiple cells CE2 in the signal dataset DS1 and determines, based on the evaluation results of the multiple pieces of correlation information, whether the detection target is located in the selected cell CE1.

[0082] In the example shown in this embodiment, the information selector 43 extracts correlation information whose value is equal to or greater than a threshold from the multiple pieces of correlation information included in the correlation map DS2, and determines areas in real space where no detection target is located based on the extracted correlation information. For example, the information selector 43 sets signal change information corresponding to areas where it is determined that no detection target is located to zero or Null in the signal dataset DS1. For example, the information selector 43 sets the value of cell CE1 corresponding to areas where it is determined that no detection target is located to zero or Null in the signal dataset DS1. In other words, the information selector 43 updates the signal dataset DS1 based on the correlation information calculated by the correlation information calculator 42.

[0083] For example, the information selecting unit 43 determines an area where the detection target is not located based on the variation in the correlation information in the correlation map DS2, or the proportion of the extracted correlation information among the multiple pieces of correlation information included in the correlation map DS2, etc. The variation in the correlation information in the correlation map DS2 includes, for example, the variation in real space of the area corresponding to the extracted correlation information.

[0084] In the example shown in this embodiment, when the variation in correlation information in the correlation map DS2 is within a predetermined range, the information selection unit 43 determines that the detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2. In other words, when the variation in correlation information in the correlation map DS2 is within a predetermined range, the information selection unit 43 determines that the cell CE1 selected in the calculation of the correlation map DS2 indicates signal change information other than the detection target.

[0085] In the example shown in this embodiment, the information selection unit 43 forms a correlation map DS2 in which correlation information values ​​with a correlation value of 0.4 or greater are maintained and correlation information values ​​with a correlation value of less than 0.4 are set to zero. The information selection unit 43 calculates the standard deviation of the correlation values ​​for the correlation map. If the standard deviation does not satisfy a predetermined range, the information selection unit 43 determines that a detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2. For example, if the standard deviation is 0 or greater, the information selection unit 43 determines that a detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2. As a variation of this embodiment, if the standard deviation is within a range of 0.3 to 0.5, the information selection unit 43 may determine that a detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2. As another variation of this embodiment, the information selection unit 43 may determine that the detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2 when the standard deviation is outside the range of 0.02 to 0.09.

[0086] As a modified example of this embodiment, when the ratio of the extracted correlation information to the plurality of pieces of correlation information included in the correlation map DS2 is greater than a threshold, the information selection unit 43 may determine that the detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2. The ratio of the extracted correlation information to the plurality of pieces of correlation information included in the correlation map DS2 may be, for example, the ratio of the number of extracted correlation information to the number of relative information included in the correlation map DS2. The ratio of the extracted correlation information to the plurality of pieces of correlation information included in the correlation map DS2 may also be the ratio of the area of ​​pixels indicating the extracted correlation information to the area of ​​pixels indicating the correlation information in the correlation information image V2.

[0087] As yet another modification of this embodiment, the information selection unit 43 may calculate the variance of correlation information values ​​for a plurality of pieces of correlation information for a plurality of regions in the detection range RA, and detect the position of the detection target based on the calculated variance. In other words, the information selection unit 43 may calculate the variance of correlation information values ​​for a plurality of pieces of correlation information included in the correlation map DS2, and detect the position of the detection target based on the calculated variance. For example, if the calculated variance is greater than a threshold, the information selection unit 43 may determine that the detection target is not located in the selected region corresponding to the first signal change information selected in the calculation of the correlation map DS2.

[0088] The biometric information derivation unit 44 derives biometric information using information on the reflected wave R selected by the information selection unit 43. The biometric information derivation unit 44 acquires, for example, the information on the reflected wave R selected by the information selection unit 43 from the information acquisition unit 41. In other words, the biometric information derivation unit 44 derives biometric information using information on the cell selected by the information selection unit 43. The biometric information derivation unit 44 includes a filter unit 61, a signal decomposition unit 62, a reconstruction signal generation unit 63, an evaluation unit 64, a signal selection unit 65, a biometric information estimation unit 66, a biometric information selection unit 67, a biometric information acquisition unit 68, and a storage unit 69.

[0089] The filter unit 61 acquires information about the reflected wave R selected by the information selector 43 from the information acquirer 41 and performs a filtering process. The filter unit 61 performs a filtering process on the information output from the information selector 43. The filter unit 61 performs a filtering process on the signal information selected by the information selector 43. For example, the filter unit 61 includes a band-pass filter that removes noise components from the information output from the information selector 43. The cutoff frequency of this band-pass filter is determined depending on the biological information to be detected. A normal human heartbeat is, for example, approximately 40 bpm (beats per minute) to 120 bpm. In this case, the frequency of a human heartbeat is approximately 0.8 to 2.0 Hz. Therefore, for example, when the biological information detection system 1 detects a heartbeat, the pass band of the band-pass filter is set to 0.8 Hz or more and 2.0 Hz or less.

[0090] For example, the filter unit 61 outputs the information that has been subjected to the filtering process as signal information to the signal decomposition unit 62. The filter unit 61 outputs a plurality of pieces of signal information that have been subjected to the filtering process on the information of the reflected wave R selected by the information selection unit 43 to the signal decomposition unit 62.

[0091] As a modification of this embodiment, the biometric information derivation unit 44 may not include the filter unit 61. In this case, for example, signal information selected by the information selection unit 43 is output as signal information to the signal decomposition unit 62. In other words, for example, the information selection unit 43 outputs information on the reflected wave R selected by the information selection unit 43 to the signal decomposition unit 62. Hereinafter, as an example, a description will be given assuming that the biometric information derivation unit 44 includes the filter unit 61. The "signal information selected by the information selection unit 43" includes information that has been filtered by the filter unit 61 and information that has not been filtered by the filter unit 61.

[0092] The signal decomposition unit 62 decomposes the information of the reflected wave R selected by the information selection unit 43 into a plurality of signals. For example, the signal decomposition unit 62 performs mode decomposition on the information of the reflected wave R selected by the information selection unit 43 based on VMD (Variational Mode Decomposition). For example, the signal decomposition unit 62 decomposes the information of the reflected wave R selected by the information selection unit 43 into IMF (Intrinsic Mode Function) signals. The signal decomposition unit 62 decomposes the information of a signal corresponding to each pixel p into a plurality of IMF signals. For example, the signal decomposition unit 62 decomposes an I / Q signal into a plurality of IMF signals. For example, the signal decomposition unit 62 decomposes the information of each of the plurality of signals output from the filter unit 61 into 10 IMF signals.

[0093] The reconstructed signal generating unit 63 reconstructs the information of the signal decomposed by the signal decomposing unit 62, and generates a reconstructed signal. For example, the reconstructed signal generating unit 63 generates a reconstructed signal from the multiple IMF signals decomposed by the signal decomposing unit 62 by weighting based on the energy of each IMF signal. In other words, each of the multiple signals is a reconstructed signal obtained by decomposing each of multiple input signals representing multiple reflected waves R into multiple decomposed signals, and reconstructing the multiple decomposed signals based on the energy of each decomposed signal. For example, if the multiple IMF signals output from the signal decomposing unit 62 are S1(t), S2(t), ..., S L (t), the reconstructed signal W(t) is constructed as shown in equation (12).

number

[0094] In this case, “e” is the energy of the IMF signal, which is the sum of the squares of the amplitudes of the IMF signals. L The energies of (t) are respectively “e1, e2,…, e L "

[0095] The evaluation unit 64 evaluates the periodicity of each of the plurality of signals based on waveform information of each of the plurality of signals. For example, the evaluation unit 64 acquires an autocorrelation function of each of the plurality of signals based on the waveform information of each of the plurality of signals, and evaluates the periodicity of each of the plurality of signals based on the autocorrelation function. For example, the evaluation unit 64 calculates the autocorrelation function of the reconstructed signal generated by the reconstructed signal generation unit 63. As a modification of this embodiment, the evaluation unit 64 may calculate the autocorrelation function of the signal filtered by the filter unit 61 or the signal output from the information selection unit 43.

[0096] The evaluation unit 64 includes a peak detection unit 70. The peak detection unit 70 detects peaks of the signals. The evaluation unit 64 evaluates the periodicity of each of the multiple signals from the detection results of the peak detection unit 70. For example, the peak detection unit 70 detects peaks in an autocorrelation function. For example, the peak detection unit 70 detects multiple peaks p1, p2, ..., p in the autocorrelation function in order of the shortest lag. M For example, the peak detection unit 70 detects peaks within a predetermined time range for each of the multiple signals. After starting measurement, the peak detection unit 70 sets time windows at predetermined intervals and detects peaks in each time window.

[0097] The signal selection unit 65 selects, from among the multiple signals, a signal that is determined to have reliability indicative of biological information, based on the evaluation result by the evaluation unit 64. For example, when only one peak is detected within a predetermined time range, the signal selection unit 65 selects this signal in which only one peak is detected as a signal that is determined to have reliability indicative of biological information.

[0098] For example, when multiple peaks are detected within a predetermined time range, the signal selection unit 65 compares the first peak p1 with the second peak p2. If the comparison results in the second peak p2 being smaller than the first peak p1 and the value obtained by dividing the second peak p2 by the first peak p1 being smaller than a predetermined value, the signal selection unit 65 selects the signal in which multiple peaks are detected as a signal determined to have reliable biological information. In other words, if p2 / p1≦TH, the signal selection unit 65 selects the signal as a signal determined to have reliable biological information. If no peaks are detected within the predetermined time range or if p2 / p1>TH, the signal selection unit 65 does not select the signal as a signal determined to have reliable biological information. The predetermined threshold TH is, for example, 0.6. In FIG. 9, the predetermined time range is set between time TH1 and time TH2 from the start of measurement. Time TH2 is greater than time TH2. The predetermined time range is, for example, a time interval corresponding to the heartbeat interval, for example, 0.5 to 1.25 seconds.

[0099] The biological information estimation unit 66 estimates biological information using the signal selected by the signal selection unit 65. The biological information estimation unit 66 estimates biological information based on peak detection of the reconstructed signal selected by the signal selection unit 65. If no peak is detected within a predetermined time range in all the reconstructed signals, the biological information estimation unit 66 estimates that no biological information exists. The biological information estimation unit 66 estimates, for example, the heart rate as the biological information. For example, if no peak is detected within a predetermined time range in all the reconstructed signals, the biological information estimation unit 66 estimates that the heart rate is 0.

[0100] When a plurality of signals are selected by the signal selection unit 65, the biometric information selection unit 67 selects biometric information from the biometric information estimated by the biometric information estimation unit 66 using each of the plurality of signals. For example, when a plurality of signals are selected by the signal selection unit 65, the biometric information selection unit 67 selects biometric information estimated by the biometric information estimation unit 66 using each of the plurality of signals in accordance with the energy of the signals from the biometric information estimated by the biometric information estimation unit 66 using each of the plurality of signals. For example, when a plurality of signals are selected by the signal selection unit 65, the biometric information selection unit 67 selects biometric information estimated by the biometric information estimation unit 66 using the signal with the maximum energy from the biometric information estimated by the biometric information estimation unit 66 using each of the plurality of signals.

[0101] As a modification of this embodiment, when a plurality of signals are selected by the signal selection unit 65, the biometric information selection unit 67 may select biometric information estimated by the biometric information estimation unit 66 from the biometric information estimated by the biometric information estimation unit 66 using each of the plurality of signals in accordance with the periodicity of the signal. For example, the biometric information selection unit 67 may make the selection using the number of peaks and the peak ratio of the autocorrelation function detected by the peak detection unit 70. For example, the biometric information selection unit 67 may select biometric information estimated by the biometric information estimation unit 66 using a signal with the smallest variation in the signal peaks.

[0102] As a further modification of this embodiment, when multiple signals are selected by the signal selection unit 65, the biometric information selection unit 67 may select biometric information estimated by the biometric information estimation unit 66 from the biometric information estimated by the biometric information estimation unit 66 using each of the multiple signals, based on both the energy and periodicity of the signal.

[0103] Furthermore, for example, when the signal selection unit 65 selects multiple signals and a peak is detected in an Nth or shorter time window from the start of measurement, the biological information selection unit 67 selects the biological information estimated by the biological information estimation unit 66 using the signal with the maximum energy from the biological information estimated by the biological information estimation unit 66 using each of the multiple signals. When the signal selection unit 65 selects multiple signals and a peak is detected in a time window after the Nth time window from the start of measurement, the biological information selection unit 67 selects the biological information closest to the average value of the most recent N pieces of biological information from the biological information estimated by the biological information estimation unit 66 using each of the multiple signals. "N" is, for example, 4.

[0104] The biological information acquiring unit 68 acquires the biological information selected by the biological information selecting unit 67. The biological information acquiring unit 68 stores the acquired biological information in the storage unit 69, for example. For example, when the biological information estimated by the biological information estimating unit 66 is a heart rate, the biological information acquiring unit 68 may calculate and acquire heartbeat time-series data based on the heart rate selected by the biological information selecting unit 67. The biological information acquiring unit 68 acquires, for example, information indicating at least one of a heart rate and a heartbeat interval, or at least one of a respiratory rate and a respiratory interval, as the biological information.

[0105] The storage unit 69 stores information used by each functional unit in advance. The storage unit 69 stores outputs from each functional unit. The storage unit 69 stores, for example, information acquired by the information acquisition unit 41. The storage unit 69 stores, for example, calculation results from the correlation information calculation unit 42 and the information selection unit 43. Furthermore, the storage unit 69 stores calculation results from the filter unit 61, the signal decomposition unit 62, the reconstruction signal generation unit 63, the evaluation unit 64, the signal selection unit 65, the biometric information selection unit 67, and the biometric information acquisition unit 68. The storage unit 69 stores biometric information acquired by the biometric information acquisition unit 68.

[0106] Next, a hardware configuration of the signal processing unit 3 of the biological information detection system 1 will be described with reference to Fig. 10. Fig. 10 is a diagram showing an example of the hardware configuration of the signal processing unit 3 of the biological information detection system 1.

[0107] The signal processing unit 3 includes a processor 101, a main memory device 102, an auxiliary memory device 103, a communication device 104, an input device 105, and an output device 106. The signal processing unit 3 includes one or more computers configured with these hardware devices and software such as programs. Each of the information acquisition unit 41, the information selection unit 43, and the biometric information derivation unit 44 may be configured with one computer or multiple computers. The biometric information detection system 1 is realized in cooperation with hardware.

[0108] When the signal processing unit 3 is configured by multiple computers, these computers may be connected locally or via a communication network such as the Internet or an intranet. This connection logically constructs one biological information detection system 1.

[0109] The processor 101 executes an operating system, application programs, etc. The main memory device 102 is composed of a read-only memory (ROM) and a random-access memory (RAM). For example, at least some of the various functional units of the signal processing unit 3 can be realized by the processor 101 and the main memory device 102.

[0110] The auxiliary storage device 103 is a storage medium configured with a hard disk, a flash memory, etc. The auxiliary storage device 103 generally stores a larger amount of data than the main storage device 102. For example, at least a part of the storage unit 69 can be realized by the auxiliary storage device 103.

[0111] The communication device 104 is configured with a network card or a wireless communication module. For example, at least a part of the information acquisition unit 41 can be realized by the communication device 104. The input device 105 is configured with a keyboard, a mouse, a touch panel, etc. For example, at least a part of the information acquisition unit 41 can be realized by the input device 105. The output device 106 is configured with a printer, a display, etc. For example, at least a part of the information selection unit 43 and the biometric information derivation unit 44 can be realized by the output device 106.

[0112] The auxiliary storage device 103 stores in advance a program and data necessary for processing. This program causes a computer to execute each functional element of the biometric information detection system 1. This program causes, for example, each process in a biometric information detection method described below to be executed on the computer. This program may be provided in a state recorded on a tangible recording medium such as a CD-ROM, a DVD-ROM, or a semiconductor memory. This program may also be provided as a data signal via a communication network.

[0113] Next, an example of a method for detecting biological information will be described with reference to Fig. 11 to Fig. 13. Fig. 11 is a flowchart showing an example of a method for detecting biological information.

[0114] First, beamforming is performed (process S11). For example, in process S11, the signal transmitter 11 transmits a transmission wave T toward the detection range RA, and the signal receiver 12 receives a reflected wave R. For example, the change information calculator 47 performs a fast Fourier transform on the acquired signal information for each receiving antenna 31. This allows the distance from the reference point to the reflection position of the reflected wave R to be calculated. The change information calculator 47 calculates signal information in each direction relative to the reference point by beamforming, based on the information of multiple signals acquired by the multiple receiving antennas 31. The information acquirer 41 acquires information on I / Q signals in the detection range.

[0115] Next, the curve length of the trajectory of the I / Q signal is calculated (process S12). For example, the information acquisition unit 41 calculates the curve length of the trajectory of the I / Q signal as signal change information. The information acquisition unit 41 acquires a plurality of pieces of signal change information corresponding to a plurality of different regions in the real space S.

[0116] Next, a plurality of pieces of first signal change information are determined (process S13). For example, the correlation information calculation unit 42 determines a plurality of pieces of first signal change information from a plurality of pieces of signal change information in the signal data set DS1. The plurality of pieces of first signal change information indicate, for example, values ​​that are greater than values ​​indicated by signal change information other than the plurality of first signal change information among the plurality of pieces of signal change information. In process S13, the "value" is, for example, a power value or a curve length value.

[0117] Next, correlation information is calculated (process S14). For example, the correlation information calculation unit 42 calculates correlation information for each of the plurality of first signal change information. The correlation information calculation unit 42 calculates correlation information between the first signal change information selected from the plurality of signal change information and each of the plurality of second signal change information.

[0118] Next, the information selection unit 43 selects signal information to be used for detecting the biological information (process S15). For example, the information selection unit 43 selects signal information of the reflected wave R corresponding to the cell to be used for detecting the biological information. For example, in process S16, only the position of the cell to be used for detecting the biological information may be identified.

[0119] For example, the information selection unit 43 evaluates the states of multiple pieces of correlation information in the correlation map DS2. Based on the evaluation results of the multiple pieces of correlation information, the information selection unit 43 determines whether a detection target is located in a selected region used in the calculation of the correlation map DS2. If the information selection unit 43 determines that a detection target is not located in a selected region used in the calculation of the correlation map DS2, it removes signal change information corresponding to the selected region from the signal dataset DS1 as unnecessary data. For example, the information selection unit 43 sets signal change information corresponding to a selected region in the signal dataset DS1 where it is determined that a detection target is not located to zero or Null. In other words, the information selection unit 43 updates the signal dataset DS1 based on the correlation information in the correlation map DS2.

[0120] Next, the biometric information derivation unit 44 executes a biometric information derivation process (process S16). In process S16, the biometric information derivation unit 44 derives biometric information using information on the reflected wave R. In other words, the biometric information derivation unit 44 derives biometric information using signal information on the reflected wave R corresponding to the cell selected in process S15.

[0121] Next, the biometric information derivation process will be described with reference to Fig. 12. Fig. 12 is a flowchart showing an example of the biometric information derivation process.

[0122] Next, the filter unit 61 performs a filtering process on the information of the reflected wave R selected by the information selection unit 43 (process S21). When the biological information detection system 1 detects a heartbeat, the filtering process in process S21 extracts a frequency band of 0.8 Hz or more and 2.0 Hz or less from the signal information of the cell selected by the information selection unit 43. In process S21, filtering is performed on the signal information of the reflected wave R corresponding to the selected cell. When process S21 is completed, process S22 is executed.

[0123] Next, the signal decomposition unit 62 decomposes the information of the reflected wave R selected by the information selection unit 43 into a plurality of signals (process S22). Based on the VMD, the signal decomposition unit 62 decomposes each of the plurality of signals that have been subjected to the filtering process in process S22 into a plurality of IMF signals.

[0124] Next, the reconstructed signal generator 63 reconstructs the information of the signal decomposed in step S22 to generate a reconstructed signal (step S23). For example, the reconstructed signal is generated from the multiple IMF signals decomposed by the signal decomposition unit 62 by weighting based on the energy of each IMF signal.

[0125] Next, the evaluation unit 64 performs an evaluation process for the reconstructed signal generated in step S23 (step S24).

[0126] Next, the signal selection unit 65 selects, from among the multiple signals, a signal that is determined to have sufficient reliability to represent biological information, based on the evaluation result in step S24 (step S25).

[0127] Next, the biological information estimation unit 66 estimates biological information using the signal selected in process S25 (process S26). The biological information estimation unit 66 estimates biological information using the signal selected in process S25.

[0128] Next, when a plurality of signals are selected in process S25, the biological information selection unit 67 selects biological information from the biological information estimated in process S26 using each of the plurality of signals. First, the biological information selection unit 67 determines whether the biological information estimated in process S26 is biological information based on a peak detected in a time window that is N or less from the start of measurement (process S27). If the time window is N or less from the start of measurement (YES in process S27), a first biological information selection process is executed (process S28). If the time window is N or less from the start of measurement (NO in process S27), a second biological information selection process is executed (process S29).

[0129] In process S28, the biometric information selection unit 67 selects biometric information estimated by the biometric information estimation unit 66 using the signal with the maximum energy from the biometric information estimated by the biometric information estimation unit 66 using each of the multiple signals. In process S29, the biometric information selection unit 67 selects biometric information closest to the average value of the most recent N pieces of biometric information from the biometric information estimated by the biometric information estimation unit 66 using each of the multiple signals.

[0130] Next, the biological information acquisition unit 68 acquires the biological information selected in step S28 or step S29 (step S30). For example, information indicating at least one of the heart rate and the heartbeat interval, or at least one of the respiratory rate and the respiratory interval is acquired as the biological information. For example, heartbeat time-series data is calculated and acquired based on the heart rate selected in step S26.

[0131] Next, the biological information derivation process will be described with reference to Fig. 13. Fig. 13 is a flowchart showing an example of the signal evaluation process.

[0132] First, the evaluation unit 64 calculates an autocorrelation function (step S41). Next, the peak detection unit 70 detects peaks within a time window (step S42). The time window is a predetermined time range.

[0133] Next, the evaluation unit 64 determines whether a peak is detected within the time window (step S43). If a peak is detected within the time window (YES in step S43), the process proceeds to step S45. If a peak is not detected within the time window (NO in step S43), the process proceeds to step S48.

[0134] In step S45, the evaluation unit 64 determines whether only one peak is detected within the time window (step S45). If only one peak is detected within the time window (YES in step S45), the process proceeds to step S46. If multiple peaks are detected within the time window (NO in step S45), the process proceeds to step S47.

[0135] In step S46, the evaluation unit 64 determines that the signal evaluation is good. In this case, for example, the evaluation unit 64 sets a flag indicating that the signal has periodicity, i.e., that the reliability of the signal indicating biological information is ensured.

[0136] In process S47, the evaluation unit 64 determines whether the peak ratio is lower than the threshold value (process S47). If it is determined that the peak ratio is lower than the threshold value (YES in process S47), the process proceeds to process S46. If it is not determined that the peak ratio is lower than the threshold value (NO in process S47), the process proceeds to process S48. For example, the evaluation unit 64 determines whether the second peak p2 is smaller than the first peak p1 in a predetermined time window, and the value obtained by dividing the second peak p2 by the first peak p1 is smaller than a predetermined threshold value TH. In other words, it is determined whether p2 / p1≦TH is satisfied.

[0137] In step S48, the evaluation unit 64 determines that the signal evaluation is poor. In this case, for example, the evaluation unit 64 sets a flag indicating that the signal does not have periodicity, i.e., that the reliability of the signal as biological information is not ensured.

[0138] Next, the effects of the biological information detecting system 1 and the biological information detecting method in the above-described embodiment will be described.

[0139] In the biological information detection system 1, the periodicity of each of the multiple signals is evaluated based on the waveform information of each of the multiple signals, and a signal is selected from the multiple signals based on the evaluation result. The selected signal is a signal that is determined to have sufficient reliability to indicate biological information. The biological information estimation unit 66 estimates the biological information using the selected signal. In this case, the accuracy of selecting a reliable signal can be improved. As a result, the accuracy of detecting biological information can be improved while detecting biological information contactlessly.

[0140] The evaluation unit 64 may include a peak detection unit 70 that detects peaks in the signals. The evaluation unit 64 may evaluate the periodicity of each of the multiple signals from the detection results of the peak detection unit 70. In this case, the detection accuracy of the biological information can be further improved.

[0141] The evaluation unit 64 may acquire an autocorrelation function of each of the plurality of signals based on waveform information of each of the plurality of signals. The evaluation unit 64 may evaluate the periodicity of each of the plurality of signals based on the autocorrelation function. In this case, the detection accuracy of the biological information may be further improved.

[0142] The evaluation unit 64 may include a peak detection unit 70 that detects peaks in the autocorrelation function. The evaluation unit 64 may evaluate the periodicity of each of the multiple signals from the detection results of the peak detection unit 70. In this case, the detection accuracy of the biological information may be further improved.

[0143] The peak detection unit 70 may detect peaks within a predetermined time range for each of the multiple signals. If only one peak is detected within the predetermined time range, the signal selection unit 65 may select the signal from which only one peak is detected as a signal determined to have sufficient reliability to represent biological information. In this case, the detection accuracy of biological information may be further improved.

[0144] The peak detection unit 70 may detect peaks within a predetermined time range for each of the multiple signals. When multiple peaks are detected within the predetermined time range, the signal selection unit may compare a second peak with a first peak within the predetermined time range. When the comparison results in the second peak being smaller than the first peak and the value obtained by dividing the second peak by the first peak being smaller than a predetermined value, the signal selection unit may select the signal in which the multiple peaks are detected as a signal determined to have sufficient reliability to represent biological information. In this case, the detection accuracy of biological information may be further improved.

[0145] Each of the plurality of signals may be a reconstructed signal obtained by decomposing each of a plurality of input signals, each representing a plurality of reflected waves, into a plurality of decomposed signals and reconstructing the decomposed signals based on the energy of each decomposed signal. In this case, the detection accuracy of the biological information can be further improved.

[0146] The input signal may be an I / Q signal, and the decomposed signal may be an IMF signal. In this case, the detection accuracy of the biological information can be further improved.

[0147] When a plurality of signals are selected by the signal selection unit 65, the biometric information selection unit 67 may select the biometric information estimated by the biometric information estimation unit 66. The biometric information acquisition unit 68 may acquire the biometric information selected by the biometric information selection unit 67. In this case, the detection accuracy of the biometric information may be further improved.

[0148] The biometric information selection unit 67 may select the biometric information estimated by the biometric information estimation unit 66 using the signal with the maximum energy from among the biometric information estimated by the biometric information estimation unit 66 using each of the multiple signals. In this case, the detection accuracy of the biometric information can be further improved.

[0149] When the estimation of biometric information by the biometric information estimation unit 66 is performed a predetermined number of times or more for signals at different times, the biometric information selection unit 67 may select an average value of the biometric information most recently estimated by the biometric information estimation unit 66. In this case, the detection accuracy of the biometric information can be further improved.

[0150] 14 to 16, an example of verification of the above-described biological information detection system 1 and the biological information detection method using steps S11 to S48 will be described. Hereinafter, the biological information detection method using the above-described biological information detection system 1 and the biological information detection method using steps S11 to S48 will be referred to as the "proposed method."

[0151] The conditions for this verification are as follows. In this verification, the heart rates of four subjects in a natural, seated, and stationary position were detected as biometric information. The subjects were humans. A MIMO FMCW radar with a bandwidth of 3.43 GHz was used as the signal control unit 2. The transmission bandwidth was 77.06 GHz. The number of samples per chirp was 240. The signal transmission unit 11 included three transmission antennas 23, and the signal reception unit 12 included four reception antennas 31.

[0152] In this test, beamforming was performed in the azimuth range of -40° to 40°. The beamforming interval was 3°. There were two distance patterns from the MIMO FMCW radar to the subject: 1.0 m and 2.0 m. The observation time was 2 minutes. The upper limit of the number of selected cells CE1 was 10.

[0153] Figure 14 shows the results of comparing the proposed method with other methods. Figure 14 shows the MAE between the estimated heart rate and the true heart rate for each method. The true heart rate was taken as the heart rate measured by an electrocardiogram. The MAE is given by Equation (13).

number

[0154] "N" is the number of observed heartbeats. BPM est (n) is the nth estimated heart rate, BPM ref (n) is the true heart rate measured at the nth time.

[0155] In the spectrogram-based method shown in Figure 14, a spectrogram was calculated and peaks due to heartbeats were detected from the spectral integrals. In the Mitabi algorithm-based method shown in Figure 14, the average of multiple peaks in the spectral integrals was considered as a single peak candidate, and the most likely peak set was selected based on the Viterbi algorithm. In the VMD-based method shown in Figure 14, a reconstructed signal was generated using IMF signals acquired by VMD whose center frequencies were within the frequency range of the heartbeat, and peaks were detected from the reconstructed signal. In these three methods, the average of heart rates estimated in multiple cells was calculated as the estimated heart rate.

[0156] In the verification results shown in FIG. 14, the proposed method is a biological information detection method using the biological information detection system 1 and processes S11 to S48. In this proposed method, a reconstructed signal is generated, and the reconstructed signal to be used for heart rate estimation is selected by evaluating the signal based on an autocorrelation function. From the biological information estimated by the biological information estimation unit 66 using each of the multiple signals, the biological information closest to the average value of the most recent four pieces of biological information was selected. As shown in FIG. 14, it was confirmed that the MAE of the proposed method was the smallest.

[0157] Fig. 15 shows the verification results comparing the proposed method when signal evaluation by the evaluation unit 64 is used and when it is not used. Fig. 16 shows the verification results comparing the proposed method when time transitions are taken into account in peak detection by the biological information selection unit 67 and when they are not taken into account. These results confirm that MAE is improved by selecting a reconstructed signal through signal evaluation. It was confirmed that taking time transitions into account stabilizes the estimated heart rate and improves MAE.

[0158] The above describes embodiments and modifications of the present invention, but the present invention is not necessarily limited to the above-described embodiments and modifications, and various modifications are possible without departing from the spirit of the present invention.

[0159] For example, the biological information detection system 1 is not limited to a MIMO FMCW radar, and may be a radar such as a SIMO or MISO radar. The biological information detection system 1 may include a plurality of different types of radars. [Explanation of symbols]

[0160] 1...biometric information detection system, 41...information acquisition unit, 64...evaluation unit, 65...signal selection unit, 66...biometric information estimation unit, 67...biometric information selection unit, 68...biometric information acquisition unit, 70...peak detection unit, p1, p2...peak, R...reflected wave

Claims

1. an information acquisition unit that acquires information on a plurality of signals that respectively indicate a plurality of reflected waves reflected at a plurality of different positions; an evaluation unit that evaluates the periodicity of each of the plurality of signals based on waveform information of each of the plurality of signals; a signal selection unit that selects, from the plurality of signals, a signal that is determined to have reliability indicative of biological information based on an evaluation result by the evaluation unit; and an estimation unit that estimates the biological information using the signal selected by the signal selection unit.

2. The biological information detection system according to claim 1 , wherein the evaluation unit includes a peak detection unit that detects peaks of the signals, and evaluates the periodicity of each of the plurality of signals from the detection results of the peak detection unit.

3. the peak detection unit detects peaks within a predetermined time range for each of the plurality of signals; 3. The biological information detection system according to claim 2, wherein, when only one peak is detected within the predetermined time range, the signal selection unit selects the signal in which the only peak is detected as a signal whose reliability in indicating the biological information is determined to be ensured.

4. the peak detection unit detects peaks within a predetermined time range for each of the plurality of signals; 3. The biological information detection system of claim 2, wherein when multiple peaks are detected within the predetermined time range, the signal selection unit compares a second peak with a first peak within the predetermined time range, and when the comparison results in the second peak being smaller than the first peak and the value obtained by dividing the second peak by the first peak being smaller than a predetermined value, selects the signal in which the multiple peaks are detected as a signal whose reliability in representing the biological information is determined to be ensured.

5. 2. The biological information detection system according to claim 1, wherein the evaluation unit acquires an autocorrelation function for each of the plurality of signals based on waveform information of each of the plurality of signals, and evaluates the periodicity of each of the plurality of signals based on the autocorrelation function.

6. The biological information detection system according to claim 5 , wherein the evaluation unit includes a peak detection unit that detects peaks in the autocorrelation function, and evaluates the periodicity of each of the plurality of signals from a detection result of the peak detection unit.

7. 2. The biological information detection system of claim 1, wherein each of the plurality of signals is a reconstructed signal obtained by decomposing each of a plurality of input signals, each representing a plurality of reflected waves, into a plurality of decomposed signals and reconstructing the plurality of decomposed signals based on the energy of each of the decomposed signals.

8. the input signal is an I / Q signal, The biological information detection system according to claim 7 , wherein the decomposed signal is an IMF signal.

9. a biometric information selection unit that selects the biometric information estimated by the estimation unit when a plurality of signals are selected by the signal selection unit; The biological information detection system according to claim 1 , further comprising: a biological information acquisition unit that acquires the biological information selected by the biological information selection unit.

10. 10. The biological information detection system according to claim 9, wherein the biological information selection unit selects the biological information estimated by the estimation unit using a signal having a maximum energy from among the biological information estimated by the estimation unit using each of the plurality of signals.

11. The biometric information detection system according to claim 9, wherein the biometric information selection unit selects an average value of a plurality of biometric information most recently estimated by the estimation unit when the estimation unit has performed estimation of the biometric information a predetermined number of times or more for signals at different times.

12. acquiring information on a plurality of signals respectively indicating a plurality of reflected waves reflected at a plurality of positions different from each other; evaluating the periodicity of each of the plurality of signals based on waveform information of each of the plurality of signals; selecting, from the plurality of signals, a signal that is determined to have sufficient reliability to represent biological information based on an evaluation result regarding the periodicity of each of the plurality of signals; and estimating the biometric information using the selected signal.

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