Thermal sensation estimation device

Abstract

To provide a thermal sensation estimation device that can more accurately estimate the thermal sensation of living organisms. [Solution] A biological information acquisition unit acquires biological information of living organisms within the observation range from signals obtained by a transmitting / receiving unit that transmits and receives radar waves. A temperature sensor measures the temperature within the observation range. An environmental sensor measures at least one environmental indicator within the observation range, including humidity, atmospheric pressure, illuminance, carbon dioxide concentration, oxygen concentration, noise level, wind speed, wind direction, and PM2.5 concentration. Based on the biological information acquired by the biological information acquisition unit, the temperature measurement values ​​acquired by the temperature sensor, and the environmental indicators measured by the environmental sensor, a thermal sensation estimation unit estimates the thermal sensation of living organisms within the observation range.

Description

Technical Field

[0001] The present invention relates to a warm and cold feeling estimation device.

Background Art

[0002] Devices for estimating the warm and cold feeling of a subject based on the temperature in a room and the biological information of the subject are known (Patent Document 1). A millimeter-wave radar device is used to acquire the biological information of the subject. The biological information includes information related to periodic changes such as heartbeat, respiration, body sway, etc., and information indicating non-periodic body movements. The operating state of the air conditioning system is controlled based on the estimated warm and cold feeling.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In order to control the operating state of the air conditioning system so that the subject, who is a living body, feels comfortable, it is desirable to more appropriately estimate the warm and cold feeling of the living body. An object of the present invention is to provide a warm and cold feeling estimation device capable of more appropriately estimating the warm and cold feeling of a living body.

Means for Solving the Problems

[0005] According to one aspect of the present invention, a biological information acquisition unit that acquires biological information of a living body within an observation range from a signal obtained by a transmission and reception unit that transmits and receives radar waves, a temperature sensor that measures the temperature within the observation range, an environmental sensor that measures at least one environmental index of humidity, atmospheric pressure, illuminance, carbon dioxide concentration, oxygen concentration, noise level, wind speed, wind direction, and PM2.5 concentration within the observation range, A thermal sensation estimation unit estimates the thermal sensation of living organisms within the observation range based on the biological information acquired by the biological information acquisition unit, the temperature measurement value acquired by the temperature sensor, and the environmental index measured by the environmental sensor. A thermal sensation estimation device equipped with [a specific feature] is provided. [Effects of the Invention]

[0006] By using environmental indicators in addition to ambient temperature when estimating the body's thermal sensation, it is possible to estimate the body's thermal sensation more accurately. [Brief explanation of the drawing]

[0007] [Figure 1] Figure 1 is a block diagram of a thermal sensation estimation device according to one embodiment. [Figure 2] Figure 2 is a flowchart showing the processing procedure for estimating thermal sensation, which is performed by the transmitting / receiving unit 20, the biological information acquisition unit 30, and the thermal sensation estimation unit 35. [Figure 3] Figure 3 is a schematic diagram showing the arrangement of various pieces of information (data) required in the process of detecting an object. [Figure 4] Figure 4A is a schematic plan view showing the arrangement of objects within the observation range 50, Figure 4B is a diagram showing the distribution of power obtained from the square of the absolute value of the complex signal P (Figure 3) obtained in step S2 (Figure 2) using shades of gray, and Figure 4C is a diagram showing the distribution of the biological determination index I obtained in step S3 (Figure 2) using shades of gray. [Figure 5] Figure 5A is a graph showing an example of a body surface displacement signal waveform, Figure 5B is a graph showing an example of a respiratory waveform, which is the low-frequency component of the body surface displacement signal, and Figure 5C is a graph showing an example of a heart rate waveform, which is the high-frequency component of the body surface displacement signal. [Figure 6] Figure 6 is a graph showing the respiratory waveform for one cycle. [Figure 7] Figure 7A is a graph showing an example of a heart rate waveform, Figure 7B is a graph showing the time variation of the heart rate interval, and Figure 7C is a graph showing the frequency analysis results of the time variation of the heart rate interval shown in Figure 7B. [Modes for carrying out the invention]

[0008] A thermal sensation estimation device according to one embodiment will be described with reference to Figures 1 to 7C. Figure 1 is a block diagram of a thermal sensation estimation device according to one embodiment. The thermal sensation estimation device according to the embodiment includes a transmitting / receiving unit 20, a biological information acquisition unit 30, and a thermal sensation estimation unit 35.

[0009] The transmitting / receiving unit 20 includes a signal generating unit 22, a plurality of AD converters 23, a plurality of mixers 24, at least one transmitting antenna Tx, and a plurality of receiving antennas Rx.

[0010] The signal generator 22 periodically supplies a transmission signal called a chirp to the transmitting antenna Tx, which linearly increases in frequency over time. The transmitting antenna Tx transmits radio waves (radar waves) based on the transmission signal within the observation range 50. Each of the multiple receiving antennas Rx receives reflected waves from objects 51 within the observation range 50.

[0011] Mixers 24, each prepared for multiple receiving antennas Rx, mix the transmitted signal and the received signal to generate an intermediate frequency signal (IF signal). AD converters 23 perform AD conversion on each of the IF signals. The AD-converted IF signals are input to the biological information acquisition unit 30.

[0012] The temperature sensor 40 measures the temperature within the observation range 50, and the environmental sensor 41 measures environmental indicators other than temperature within the observation range 50. The environmental indicators include at least one of the following within the observation range 50: humidity, atmospheric pressure, illuminance, carbon dioxide concentration, oxygen concentration, noise level, wind speed, wind direction, and PM2.5 concentration.

[0013] The biological information acquisition unit 30 detects an object within the observation range 50 based on the IF signal input from the transmission / reception unit 20. Further, it determines whether the detected object is a living body and acquires biological information. The biological information includes a body surface displacement signal that changes over time according to the displacement of the body surface of the living body. The biological information acquisition unit 30 calculates a respiration feature amount derived from the respiration of the living body and a heartbeat feature amount derived from the heartbeat of the living body based on the body surface displacement signal. The body surface displacement signal, the respiration feature amount, and the heartbeat feature amount will be described in detail later with reference to FIGS. 5A, 5B, and 5C.

[0014] The warm / cold feeling estimation unit 35 estimates the warm / cold feeling of the living body within the observation range 50 based on the biological information (for example, the respiration feature amount and the heartbeat feature amount) acquired by the biological information acquisition unit 30, the temperature measurement value measured by the temperature sensor 40, and the environmental index measured by the environmental sensor 41.

[0015] Next, referring to FIG. 2, the procedure for estimating the warm / cold feeling by the warm / cold feeling estimation device according to the embodiment will be described. FIG. 2 is a flowchart showing the processing procedure for estimating the warm / cold feeling executed by the transmission / reception unit 20, the biological information acquisition unit 30, and the warm / cold feeling estimation unit 35. Note that, in order to estimate the warm / cold feeling of the living body, it is not necessary to execute all the steps shown in FIG. 2, and some steps can be omitted.

[0016] First, the transmission / reception unit 20 (FIG. 1) transmits and receives signals (step S1). The transmission signal is a frequency continuous modulation wave in which a plurality of chirps repeatedly appear. The mixer 24 and the AD converter 23 generate an IF signal for each channel constituted by each of a plurality of sets of the transmission antenna Tx and the reception antenna Rx.

[0017] Next, the biological information acquisition unit 30 detects an object 51 within the observation range 50 (step S2). Hereinafter, the procedure for detecting the object will be described.

[0018] The biometric information acquisition unit 30 performs distance FFT, velocity FFT, and angle estimation processing on the IF signal to calculate the distribution of complex signals within the observation range 50 and the power obtained by squaring the absolute value of these complex signals. This processing is the same as that of known FMCW radar systems. For example, a distance FFT is performed for each chirp, and a velocity FFT is performed on the results of the distance FFT processing for each chirp frame consisting of multiple chirps. Angle estimation processing is performed on the results of the velocity FFT processing for multiple channels. The calculated complex signals are represented by complex numbers that reflect the presence or absence of objects and the velocity of objects at each position within the observation range 50, and the power is represented by the square of the absolute value of the complex signal.

[0019] Next, the process of step S2 will be explained with reference to Figure 3. Figure 3 is a schematic diagram showing the arrangement of various information (data) obtained in the processing procedure of step S2. By performing distance FFT processing and velocity FFT processing, three-dimensional data X(r,d,n) defined in the three-dimensional space of distance r, velocity d, and channel n is calculated.

[0020] Next, the biometric information acquisition unit 30 averages the three-dimensional data X in the velocity direction. This yields two-dimensional data X'(r,n) defined in a two-dimensional space of distance r and channel n. By performing angle estimation processing based on the two-dimensional data X'(r,n), a complex signal P(r,θ) defined in a two-dimensional space where the position can be represented by distance r and angle θ is calculated. The complex signal P is a complex number defined for each position and includes an amplitude component m and a phase component p. The complex signal P reflects the presence or absence of an object and the velocity of the object. The position of an object can be detected from the complex signal P or the power distribution. The complex signal P(r,θ) can be considered as a signal that reflects the amplitude and phase of the reflected wave from position (r,θ).

[0021] The biological information acquisition unit 30 calculates the amplitude component m(r,θ) and phase component p(r,θ) of the complex signal P(r,θ) from the complex signal P(r,θ). By calculating the amplitude component m(r,θ) and phase component p(r,θ) for each of the multiple chirp frames and saving the calculation results, the amplitude component m(r,θ,t) and phase component p(r,θ,t) of the complex signal P can be obtained for each distance r, angle θ, and discretized time t.

[0022] Next, the biological information acquisition unit 30 detects a living organism within the observation range 50, as shown in Figure 2 (step S3). The procedure for detecting a living organism will be described below.

[0023] In step S2 (Figure 2), once the distribution of the complex signal P, for example, the amplitude component m(r,θ,t) and phase component p(r,θ,t) shown in Figure 3, is determined, the biological information acquisition unit 30 (Figure 1) calculates a biological determination index I(r,θ) for each position (r,θ).

[0024] Next, the biological identification index I(r,θ) will be explained. The surface of a living organism is periodically displaced by respiration, heartbeat, etc. When a living organism is present at a specific location (r,θ), the amplitude component m(r,θ,t) and phase component p(r,θ,t) at that location will show a strong characteristic attributable to the periodic displacement of the body surface. For example, the time evolution of the amplitude component m(r,θ,t) and the time evolution of the phase component p(r,θ,t) will show the same trend, and the correlation between the two will become stronger. The biological identification index I(r,θ) is defined such that when the characteristics attributable to the periodic displacement of the body surface are strongly expressed in the amplitude component m(r,θ,t) and phase component p(r,θ,t), the biological identification index I(r,θ) becomes large.

[0025] When a stationary object other than a living organism is present at a specific position (r,θ), the time evolution of the amplitude component m(r,θ,t) and the phase component p(r,θ,t) does not show features caused by the periodic displacement of the body surface. Instead, random noise components are superimposed, weakening the correlation between the two.

[0026] Furthermore, the amplitude of the time variation of the amplitude component m caused by displacement of the body surface is greater than the amplitude of the time variation of the noise component. For this reason, the variance of the amplitude component m(r,θ,t) when a living organism is present at a specific position (r,θ) is greater than the variance of the amplitude component m(r,θ,t) when a stationary object is present.

[0027] By using the correlation between the time evolution of the amplitude component m(r,θ,t) and the time evolution of the phase component p(r,θ,t), and the aforementioned properties of the variance of the amplitude component m(r,θ,t), it is possible to determine whether the detected object is a living organism or not.

[0028] The strength of the correlation C between the time evolution of the amplitude component m(r,θ,t) and the phase component p(r,θ,t). mp This is defined by the following formula.

number

[0029] Variance σ of the amplitude component m(r,θ,t) m 2 This can be calculated, for example, using the following formula.

number

[0030] The judgment index I(r,θ,t) is defined, for example, by the following formula.

number

[0031] Once the biological identification index I(r,θ,t) is calculated, the biological information acquisition unit 30 identifies the location of the living organism based on the spatial distribution of the biological identification index I(r,θ,t) in step S3 of Figure 2.

[0032] Next, with reference to Figures 4A, 4B, and 4C, the results of an evaluation experiment to detect living organisms within the observation range 50 will be described. Figure 4A is a schematic plan view showing the arrangement of objects within the observation range 50. A thermal sensation estimation device 55 is positioned approximately in the center of one of the shorter sides of the rectangular observation range 50. Two people 53 are located in close proximity in front of the thermal sensation estimation device 55, and a stationary object 52 is located at approximately the same distance as the people 53. A wall 54 is located further away from the people 53 and the stationary object 52.

[0033] Figure 4B shows the power distribution obtained from the square of the absolute value of the complex signal P (Figure 3) obtained in step S2 (Figure 2), using shades of gray. Regions with relatively high power are shown in darker shades. In regions 53A, 52A, and 54A, which correspond to the person 53, the stationary object 52, and the wall 54, the power is relatively high. At this stage, since it has not been determined whether the objects are living organisms or not, the person 53, the stationary object 52, and the wall 54 are detected.

[0034] Figure 4C shows the distribution of the biological detection index I obtained in step S3 (Figure 2) using shades of gray. The biological detection index I is smaller in the regions 52A and 54A (Figure 4B) corresponding to the stationary object 52 and the wall 54, while the biological detection index I is relatively larger in the region 53A corresponding to the person 53. This suppresses the complex signal P (Figure 3) and its power originating from the stationary object 52, etc., making it possible to detect a living organism.

[0035] After step S3 (Figure 2), the biological information acquisition unit 30 acquires a body surface displacement signal (step S4). As the body surface displacement signal, for example, the phase component p(r,θ,t) of a complex signal P can be used. The time change of the phase component p(r,θ,t) reflects the time change of the body surface displacement.

[0036] Next, the biological information acquisition unit 30 calculates respiratory features from the low-frequency components of the body surface displacement signal and heart rate features from the high-frequency components (step S5).

[0037] Next, with reference to Figures 5A, 5B, and 5C, the body surface displacement signal, its low-frequency component, and its high-frequency component will be explained. Figure 5A is a graph showing an example of the waveform of the body surface displacement signal, Figure 5B is a graph showing an example of the respiratory waveform, which is the low-frequency component of the body surface displacement signal, and Figure 5C is a graph showing an example of the heartbeat waveform, which is the high-frequency component of the body surface displacement signal. The horizontal axis in Figures 5A, 5B, and 5C represents time. The vertical axis in Figure 5A represents a physical quantity corresponding to the displacement of the body surface, the vertical axis in Figure 5B represents a physical quantity corresponding to the displacement of the body surface due to respiration, and the vertical axis in Figure 5C represents a physical quantity corresponding to the displacement of the body surface due to heartbeat. The physical quantity corresponding to the displacement of the body surface is, for example, the magnitude of the phase component p of the complex signal P.

[0038] The waveform of the body surface displacement signal (Figure 5A) superimposes the time changes in body surface displacement caused by respiration and the time changes in body surface displacement caused by heartbeat. When a low-pass filter is applied to the body surface displacement signal to extract the low-frequency components, the respiration waveform (Figure 5B) is obtained. When a high-pass filter is applied to the body surface displacement signal to extract the high-frequency components, the heartbeat waveform (Figure 5C) is obtained. Once the body surface displacement signal is acquired, in step S5 (Figure 2), the biological information acquisition unit 30 (Figure 1) calculates respiration features from the respiration waveform (Figure 5B) and heartbeat features from the heartbeat waveform (Figure 5C).

[0039] Next, we will explain the respiratory features calculated from the respiratory waveform, referring to Figure 6. Figure 6 is a graph showing the respiratory waveform for one cycle. The respiratory waveform gradually increases during the period when the body inhales (inspiratory time Ti) and gradually decreases during the period when it exhales (expiratory time Te). The respiratory features include at least one of the following, determined from the respiratory waveform: amplitude A, inspiratory time Ti, expiratory time Te, amplitude / inspiratory time (A / Ti), inspiratory time / respiratory time (Ti / Tr), and pause time (Tp).

[0040] Amplitude A is defined as the difference between the lowest and highest values ​​of the respiratory waveform in one cycle. Respiratory time Tr is the sum of inspiratory time Ti and expiratory time Te. Next, pause time Tp is explained. Of the lines connecting point P1, which corresponds to the peak value of the respiratory waveform, and any point on the curve corresponding to the expiratory time Te, the line with the greatest negative slope is denoted as L1. The line segment with the lowest values ​​of the respiratory waveform in one cycle as its endpoints is denoted as L2. The intersection point of line L1 and line segment L2 is denoted as P2. The point corresponding to the lowest value of the respiratory waveform after the intersection point P2 is denoted as P3. The elapsed time from intersection point P2 to point P3 is defined as pause time Tp. Pause time Tp occupies a portion of the latter half of the expiratory time Te and can be considered as a time when neither inhalation nor exhalation is occurring significantly.

[0041] When a living organism feels hot, the tidal volume (tidal ventilation) and the tidal volume per minute (minute ventilation) increase. Tidal volume corresponds to the area of ​​the respiratory waveform for one cycle, as shown in Figure 6. Minute ventilation corresponds to the area of ​​the total respiratory waveform for one minute. It is generally known that when tidal volume and minute ventilation increase, the respiratory rate increases, the amplitude A increases, the inspiratory time Ti, expiratory time Te, and respiratory time Tr increase, and the amplitude / inspiratory time (A / Ti) and inspiratory time / respiratory time (Ti / Tr) increase. When a living organism feels cold, ventilation decreases. It is generally known that when ventilation decreases, the pause time Tp increases. These values ​​can be used as respiratory features.

[0042] Next, we will explain the heart rate features calculated from the heart rate waveform, referring to Figures 7A, 7B, and 7C. Figure 7A is a graph showing an example of a heart rate waveform. The heart rate interval is denoted as Ih. The heart rate interval (R-R interval) is calculated, for example, by measuring the time interval of the R wave in the heart rate waveform.

[0043] Figure 7B is a graph showing the time evolution of heart rate intervals. The heart rate interval changes gradually over time. Figure 7C is a graph showing the frequency analysis results of the time evolution of heart rate intervals shown in Figure 7B. The horizontal axis represents frequency in units of [Hz], and the vertical axis represents the amplitude of the frequency components.

[0044] The frequency components of heart rate intervals can be mainly classified into emotional fluctuation components (sometimes called VLF components) with a frequency of less than 0.04 Hz, low-frequency components (LF components, sometimes called blood pressure fluctuation components) with a frequency of 0.04 Hz or more but less than 0.15 Hz, and high-frequency components (HF components, sometimes called respiratory fluctuation components) with a frequency of 0.15 Hz or more but less than 0.4 Hz.

[0045] It is known that inhaling increases heart rate (decreases heart rate interval), and exhaling decreases heart rate (increases heart rate interval). This effect manifests as changes in heart rate interval, coefficient of heart rate variability (CVRR), respiratory variability component (HF component), and the ratio of blood pressure variability component to respiratory variability component (LF component / HF component).

[0046] It is also known that blood pressure rises when the body senses cold and decreases when it senses heat. This effect manifests as changes in heart rate interval, heart rate variability coefficient, blood pressure variability component (LF component), and the ratio of blood pressure variability component to respiratory variability component (LF component / HF component). For example, when feeling cold, it generally manifests as an increase in heart rate, a shortening of heart rate interval, a change in heart rate variability coefficient, a slight increase in the HF component, an increase in the LF component, and an increase in the LF component / HF component ratio. These values ​​can be used as heart rate features.

[0047] Therefore, based on indicators related to ventilation (respiratory features) and indicators representing heart rate variability caused by blood pressure (heart rate features), it is possible to estimate whether the organism feels hot, cold, or just right, i.e., its thermal sensation.

[0048] After step S5 (Figure 2), the thermal sensation estimation unit 35 acquires temperature measurements from the temperature sensor 40 and environmental indicators from the environmental sensor 41 (step S6). Subsequently, the thermal sensation estimation unit 35 estimates the thermal sensation of the living organism based on respiratory characteristics, heart rate characteristics, temperature measurements, and environmental indicators (step S7).

[0049] The thermal sensation estimation unit 35 outputs the thermal sensation estimation result to a device that utilizes thermal sensation. The thermal sensation estimation result may be expressed in three stages, for example, "hot," "just right," and "cold," or it may be expressed in four or more stages. The device that receives the thermal sensation estimation result changes the environment based on the thermal sensation estimation result so that the living body feels "just right." For example, it changes the temperature, humidity, etc.

[0050] Next, we will describe the excellent effects demonstrated by the examples. Respiratory and heart rate features are affected not only by ambient temperature but also by other environmental indicators. In the example, the thermal sensation of living organisms within the observation range 50 is estimated not only based on biological information and temperature measurements but also on environmental indicators measured by the environmental sensor 41 (Figure 1), thereby reducing estimation errors caused by environmental indicators other than temperature.

[0051] The degree to which environmental indicators influence thermal comfort should be determined by conducting evaluation experiments under various environmental conditions.

[0052] Next, we will describe a thermal sensation estimation device according to another embodiment. The above embodiment shows an example of detecting a living organism using an FMCW radar, but other types of radar may be used. For example, Doppler radar, pulse radar, OFDM (Orthogonal Frequency Division Multiplexing) radar, etc. may be used. In this case, among the various information obtained from the received signal, an index that reflects the periodic displacement of the body surface caused by the living organism's respiration and heartbeat may be used as the biological identification index.

[0053] The embodiments described above are illustrative, and it goes without saying that partial substitution or combination of the configurations shown in different embodiments is possible. Similar effects and benefits from similar configurations in multiple embodiments will not be mentioned sequentially for each embodiment. Furthermore, the present invention is not limited to the embodiments described above. For example, it will be obvious to those skilled in the art that various modifications, improvements, and combinations are possible. [Explanation of symbols]

[0054] 20 Transmitter / Receiver Unit 22 Signal generation unit 23 AD converters 24 Mixer 30. Biological Information Acquisition Unit 35 Thermal sensation estimation unit 40 Temperature Sensors 41 Environmental Sensors 50 Observation range 51 Object 52 Stationary objects 52A Region corresponding to stationary objects 53 People 53A Area corresponding to a person 54 Wall 54A Area corresponding to the wall 55 Thermal sensation estimation device A. Amplitude of the respiratory waveform Rx receiving antenna Tx Transmitter Antenna Ti Intake Time Te exhalation time Tr breathing time Tp Pause time

Claims

1. A biological information acquisition unit acquires biological information of living organisms within the observation range from signals obtained by a transmitting / receiving unit that transmits and receives radar waves, A temperature sensor that measures the temperature within the aforementioned observation range, An environmental sensor that measures at least one environmental indicator within the observation range, including humidity, atmospheric pressure, illuminance, carbon dioxide concentration, oxygen concentration, noise level, wind speed, wind direction, and PM2.5 concentration. A thermal sensation estimation unit estimates the thermal sensation of living organisms within the observation range based on the biological information acquired by the biological information acquisition unit, the temperature measurement value acquired by the temperature sensor, and the environmental index measured by the environmental sensor. A thermal sensation estimation device equipped with the following features.

2. The transmitting and receiving unit receives reflected waves of radio waves transmitted from at least one transmitting antenna to the observation range using multiple receiving antennas, and generates an intermediate frequency signal based on the transmitted signal and the received signal. The aforementioned biological information includes respiratory features that characterize the respiratory waveform resulting from displacement of the body surface due to respiration, and heart rate features that characterize the heart rate waveform resulting from displacement of the body surface due to heartbeat. The aforementioned biological information acquisition unit is Based on the aforementioned intermediate frequency signal, a living organism within the observation range is detected. Based on the aforementioned intermediate frequency signal, a time-varying body surface displacement signal is obtained in accordance with the detected displacement of the body surface of the living organism. The thermal sensation estimation device according to claim 1, wherein the respiratory feature is calculated based on the relatively low-frequency component of the frequency component of the body surface displacement signal, and the heart rate feature is calculated based on the relatively high-frequency component.

3. The thermal sensation estimation device according to claim 2, wherein the respiratory feature includes at least one of the respiratory rate, amplitude, inspiratory time, expiratory time, respiratory time, amplitude / inspiratory time, inspiratory time / respiratory time, and pause time, which are determined from the respiratory waveform.

4. The thermal sensation estimation device according to claim 2 or 3, wherein the heart rate feature comprises at least one of the following: heart rate, heart rate interval, heart rate variability coefficient, respiratory variability component, blood pressure variability component, and the ratio of the blood pressure variability component to the respiratory variability component, determined from the heart rate waveform.

5. The aforementioned transmitting and receiving unit is As the transmission signal, a chirp whose frequency changes linearly over time is transmitted periodically. The transmission signal and the reception signal are mixed to generate the intermediate frequency signal. The biological information acquisition unit performs distance FFT processing on the intermediate frequency signal for each chirp, performs velocity FFT processing on the result of the distance FFT processing for each chirp frame consisting of multiple chirps, and performs angle estimation processing on the result of the velocity FFT processing, thereby detecting a living organism based on the complex signal obtained for each position within the observation range. The thermal sensation estimation device according to any one of claims 2 to 4, which acquires the body surface displacement signal based on the time change of the phase component of the complex signal for each position within the observation range.

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