Biometric detection device and biometric detection method

Abstract

The present invention provides a biometric detection device that acquires biometric information of an occupant of a moving body and includes a control unit (11) that acquires biometric information using a radio wave sensor. The control unit acquires, from the radio wave sensor or another on-vehicle sensor, evaluation data, which is data for evaluating the reliability of the biometric information. The control unit is configured to evaluate the reliability of the biometric information on the basis of the evaluation data and to output a measurement result of the biometric information corresponding to the reliability to a biometric information use unit that uses the biometric information.

Description

Living body detection device and living body detection method CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application is based on Patent Application No. 2024-114194 filed in Japan on July 17, 2024, the contents of which are incorporated by reference in their entirety.

[0002] The disclosure in this specification relates to a technique for detecting biometric information.

[0003] Patent document 1 discloses a biometric detection device that has a radio wave sensor that measures the distance to a person by sending and receiving radio waves, and accurately acquires biometric information by appropriately adjusting the output value of the radio wave sensor according to the distance.

[0004] Japanese Patent Application Laid-Open No. 2022-116583

[0005] Although Patent Document 1 adjusts the output, it does not evaluate the reliability of the biometric information acquired using the radio wave sensor. For example, in situations where the subject of measurement is moving a lot, the biometric information acquired using the radio wave sensor may be inaccurate. In other words, depending on the situation in which the radio wave sensor is used, erroneous biometric information may be used as is in applications that provide warnings, health management, etc.

[0006] One object of the disclosure is to provide a technology that can reduce the risk of incorrect biometric information being used.

[0007] The biometric detection device disclosed herein is a biometric detection device that acquires biometric information of an occupant of a moving body, and is equipped with a control unit that acquires the biometric information using a radio wave sensor. The control unit is configured to acquire evaluation data, which is data for evaluating the reliability of the biometric information, from the radio wave sensor or other on-board sensors, evaluate the reliability of the biometric information based on the evaluation data, and output the measurement results of the biometric information according to the reliability to a biometric information usage unit that uses the biometric information.

[0008] According to the biometric detection method disclosed herein, the biometric detection method is executed by a processor to acquire biometric information of an occupant of a moving body, and includes: acquiring the biometric information using a radio wave sensor; acquiring evaluation data from the radio wave sensor or another on-board sensor, which is data for evaluating the reliability of the biometric information; evaluating the reliability of the biometric information based on the evaluation data; and outputting the measurement results of the biometric information according to the reliability to a biometric information using unit that uses the biometric information.

[0009] According to these techniques, measurement results of the biological information corresponding to the reliability of the biological information are output to the biological information use unit, thereby reducing the risk of incorrect biological information being used by the biological information use unit.

[0010] It is a diagram showing a living body detection system.It is a flowchart showing an example of processing by a control unit.It is a flowchart showing an example of processing by a control unit.

[0011] In the following description, components having the same function may be given the same reference numerals, and a detailed description thereof may be omitted. Also, components having the same function may be given the same or similar names, and a detailed description thereof may be omitted. When only a portion of the configuration is mentioned, the description given elsewhere may apply to the other portions.

[0012] First Embodiment Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. Fig. 1 is a diagram showing an example of a schematic configuration of a living body detection system 100 including a living body detection device 1.

[0013] The living body detection device 1 is mounted on a moving body for use. In this embodiment, the moving body is a vehicle. The moving body may be a ship, construction machinery, agricultural machinery, or the like other than a vehicle. The living body detection device 1 is a device that acquires biological information of a vehicle occupant. In other words, the living body detection device 1 is a device that measures biological information of a vehicle occupant. Hereinafter, the occupant to be measured will also be referred to as a target occupant. In this disclosure, the seat in which the target occupant is seated will also be referred to as a target seat. Note that the living body to be measured is not limited to a human being, and may also be an animal (pet) such as a dog or cat. In the following description, the term "target occupant" may be replaced with "target body" or "measurement target."

[0014] In this embodiment, the biological information acquired by the biological detection device 1 is the respiratory rate. The biological detection device 1 may acquire biological information other than the respiratory rate. The biological detection device 1 may be configured to measure the heart rate instead of the respiratory rate, or may be configured to measure both the respiratory rate and the heart rate. The respiratory rate here refers to the number of breaths taken per certain period of time, and may be rephrased as the respiratory cycle or the respiratory rate. The heart rate also refers to the number of heartbeats per certain period of time, and may be rephrased as the pulse cycle or the pulse rate. The biological detection device 1 may acquire pulse rate or the like as biological information.

[0015] The living body detection device 1 is used to detect a decrease in the driver's level of alertness (i.e., the degree of drowsiness) or an abnormal physical condition (a so-called dead man). The living body detection device 1 may also be used to detect whether a child has been left behind. The living body detection device 1 may also be used for health management, such as recording changes in the physical condition of a passenger and notifying the passenger of such changes.

[0016] 1, a living body detection device 1 is used by being connected to a radio wave sensor 2, a camera 3, an ADASECU 4, and a plurality of vehicle-mounted sensors. Each of these will be described in turn below.

[0017] <Radio Wave Sensor> The radio wave sensor 2 is a sensor that generates and outputs data related to the biometric information of a target occupant by transmitting and receiving radio waves in a predetermined frequency band. The radio wave sensor 2 is disposed in a position where it can detect the biometric information of all occupants in the vehicle cabin. The radio wave sensor 2 is disposed on the ceiling of the vehicle interior, for example. Here, as an example, the radio wave sensor 2 is attached to the rearview mirror. The radio wave sensor 2 may also be disposed in any other position, such as near the overhead console. The radio wave sensor 2 may be disposed on the ceiling along the center line of the vehicle body extending in the fore-and-aft direction of the vehicle, or may be disposed in a position offset to the left or right. The radio wave sensor 2 may be attached to any position on the ceiling. Furthermore, the radio wave sensor 2 is not limited to being disposed on the ceiling, and may also be disposed on the instrument panel, pillar, etc.

[0018] The radio wave sensor 2 is a millimeter-wave radar. As an example, the radio wave sensor 2 is a millimeter-wave radar using the FMCW (Frequency Modulated Continuous Wave) method. In other embodiments, the radio wave sensor 2 may be a Doppler millimeter-wave radar. The radio wave sensor 2 may be a pulse-type radar. For example, the radio wave sensor 2 may be a UWB (Ultra Wide Band) radar that uses impulse waves used in UWB communication. The frequency of the transmission wave of the radio wave sensor 2 is selected appropriately depending on the usage situation. The frequency of the transmission wave of the radio wave sensor 2 is referred to as the operating frequency below. As an example, the operating frequency is approximately 24 GHz. The frequency band of the transmission wave of the radio wave sensor 2 is referred to as the operating frequency band below.

[0019] The radio wave sensor 2 transmits radio waves (transmission waves) at an operating frequency toward the occupant. More preferably, the radio wave sensor 2 is mounted in an attitude and position that transmits radio waves toward a target region of the occupant. The target region is a body region used to acquire biometric information. In this embodiment, the target region is the chest. Additionally or alternatively, the target region may be the abdomen. The target region may be set arbitrarily depending on the type of biometric information acquired by the biometric detection device 1.

[0020] The radio wave sensor 2 receives reflected waves, which are radio waves reflected by the occupant. The radio wave sensor 2 transmits waveform data of the transmitted waves and waveform data of the reflected waves as observation data to the living body detection device 1. The living body detection device 1 acquires the distance between the radio wave sensor 2 and the occupant as a distance measurement value based on the observation data input from the radio wave sensor 2. When the radio wave sensor 2 acquires reflected waves from the occupant's chest, the living body detection device 1 can acquire the distance between the radio wave sensor 2 and the chest as a distance measurement value.

[0021] The position of the occupant's chest can fluctuate by several millimeters as the occupant breathes. The breathing cycle is approximately 4 seconds for adults and 0.8 seconds for infants. That is, the position of the chest can fluctuate in a cycle of several seconds. Therefore, the breathing rate can be estimated by observing the change in the measured distance over time. Furthermore, the position of the occupant's chest can fluctuate by several tens of micrometers as the occupant's heartbeats. Therefore, the heart rate can also be estimated by observing the change in the measured distance over time.

[0022] The radio wave sensor 2 has a signal processing circuit and an antenna (not shown). The antenna is an antenna for transmitting and receiving radio waves in the operating frequency band. The antenna is connected to the signal processing circuit. The antenna radiates a signal input from the signal processing circuit as a radio wave. The antenna inputs the received radio waves to the signal processing circuit.

[0023] The signal processing circuit performs appropriate signal processing on the transmitted and received signals, and transmits observation data, which is a processed digital signal, to a processor 11 (described later). The signal processing circuit may include a calculation unit that calculates biological information based on the transmitted and received radio waves. The signal processing circuit may transmit the calculated biological information to the processor 11.

[0024] <Camera> The camera 3 is a component that captures an image of the target occupant. The camera 3 is, for example, a visible light camera. The camera 3 may also be an infrared camera or a ToF (Time of Flight) camera. The camera 3 may also be included in other in-vehicle sensors described later. The camera 3 is disposed in a position that allows it to capture an image of all occupants in the vehicle cabin. The camera 3 is disposed near the radio wave sensor 2.

[0025] The camera 3 may be disposed at any position on the ceiling. Here, as an example, the camera 3 is attached to the rearview mirror. The camera 3 may also be disposed at any position, such as near the overhead console. The camera 3 does not have to be disposed near the radio wave sensor 2. The camera 3 may be disposed in a location where it is easy to capture an image of the target occupant.

[0026] The image of the target occupant captured by the camera 3 is hereinafter referred to as a captured image. The camera 3 transmits the captured image data to the living body detection device 1. Hereinafter, the captured image data may also be referred to as a captured image.

[0027] The camera 3 has a light receiving sensor 31. The light receiving sensor 31 is a sensor that detects the brightness in the shooting direction. The light receiving sensor 31 is used to set the exposure of the camera 3. The light receiving sensor 31 may be a photodiode, a phototransistor, or the like.

[0028] <Other In-Vehicle Sensors> A vehicle equipped with the living body detection device 1 has a plurality of in-vehicle sensors for detecting the running state of the vehicle, the environment around the vehicle, the state of the occupants, etc. Hereinafter, other in-vehicle sensors different from the radio wave sensor 2 will also be simply referred to as other in-vehicle sensors.

[0029] In this embodiment, the other on-board sensors include a vibration sensor 5, a steering angle sensor 6, an accelerator pedal sensor 7, a brake pedal sensor 8, and a vehicle speed sensor 9. Note that the living body detection system 100 does not need to include all of the above-mentioned on-board sensors.

[0030] The vibration sensor 5 is a sensor that detects the magnitude of vibration of the vehicle body. The steering angle sensor 6 is a sensor that detects the steering angle. The accelerator pedal sensor 7 is a sensor that detects the amount of depression of the accelerator pedal. The brake pedal sensor 8 is a sensor that detects the amount of depression of the brake pedal. The vehicle speed sensor 9 is a sensor that detects the traveling speed of the vehicle (so-called vehicle speed).

[0031] The other on-board sensors output data indicating the current values ​​of the physical state quantities to be detected (i.e., detection results) to a communication line of a local area network (LAN). The output data is acquired by the living body detection device 1 or the like via the communication line of the LAN.

[0032] Specifically, the vibration sensor 5 outputs data indicating the magnitude of vibrations inside the vehicle as vibration data to the living body detection device 1. The vibration sensor 5 may be a piezoelectric vibration sensor. The vibration sensor 5 may be an acceleration sensor. The steering angle sensor 6 outputs data indicating the steering angle as steering angle data to the living body detection device 1. The accelerator pedal sensor 7 outputs data indicating the amount of accelerator pedal depression as acceleration data to the living body detection device 1. The brake pedal sensor 8 outputs data indicating the amount of brake pedal depression as deceleration data to the living body detection device 1. The vehicle speed sensor 9 outputs data indicating the vehicle speed of the vehicle as vehicle speed data to the living body detection device 1.

[0033] <ADASECU> The ADASECU 4 is an ECU that executes control to assist the driver in driving operations. ADAS is an abbreviation for Advanced Driving Assistant System. ECU is an abbreviation for Electronic Control Unit. The ADASECU 4 may notify or warn the driver based on the biometric information transmitted from the biometric detection device 1. The biometric detection device 1 is connected to the ADASECU 4, but the function may be built into the ADASECU 4. The ADASECU 4 corresponds to a biometric information usage unit that uses the biometric information.

[0034] The biometric information user unit may be any other ECU. For example, the biometric information user unit may be a cockpit ECU. The cockpit ECU is an ECU that controls a meter device, a navigation device, an air conditioning device, etc.

[0035] <Biodetection Device> The biodetection device 1 has a processor 11, RAM 12, storage 13, and I / O 14. The processor 11 corresponds to a control unit. The processor 11 is an arithmetic core that performs arithmetic processing based on data received from the radio wave sensor 2 or the camera 3. The processor 11 may be a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). RAM is an abbreviation for Random Access Memory.

[0036] The storage 13 is a rewritable non-volatile memory. The storage 13 may be realized by at least one type of non-transitory tangible storage medium, such as a semiconductor memory, a magnetic medium, or an optical medium. The storage 13 may include multiple types of storage media, such as a read-only memory (ROM) and a flash memory. The storage 13 stores a living body detection program to be executed by the processor 11. Execution of the living body detection program by the processor 11 corresponds to execution of a living body detection method.

[0037] The processor 11 performs a process to calculate biological information (breathing) based on the observation data. The biological information may be calculated based on changes in the distance measurement value over time due to the breathing of the occupant. The processor 11 may generate data (hereinafter referred to as distance FFT data) by performing an FFT on an IF (intermediate frequency) signal obtained by mixing a transmitted wave and a received wave, based on the observation data. The distance FFT data indicates the frequency spectrum of the IF signal and indirectly indicates the location of a reflecting object. The location of a reflecting object is, specifically, the distance to the reflecting object. Note that the signal processing circuit may generate the distance FFT data, and the processor 11 may receive the data as observation data. Additionally or alternatively, the processor 11 may be configured to measure the heart rate based on the observation data.

[0038] The processor 11 acquires evaluation data, which is data for evaluating the reliability of the biological information, from the radio wave sensor 2 or other on-board sensors. The processor 11 evaluates the reliability of the biological information based on the evaluation data. Specifically, the processor 11 determines whether or not a predetermined condition (hereinafter also referred to as a degradation condition) that may cause a decrease in reliability is satisfied based on the evaluation data. Note that the reliability of the biological information may be interpreted as the reliability of the measured biological information, in other words, the reliability of the measured value of the biological information.

[0039] In this embodiment, the processor 11 acquires evaluation data from other on-board sensors. The processor 11 acquires photographed image data, vibration data, steering angle data, acceleration data, deceleration data, and vehicle speed data as evaluation data. Note that the processor 11 is not limited to a configuration that acquires all of these types of data. The processor 11 may be configured to acquire at least one of photographed image data, vibration data, steering angle data, acceleration data, deceleration data, and vehicle speed data as evaluation data.

[0040] The processor 11 evaluates the magnitude Bm of the target occupant's body movement based on the evaluation data. If the magnitude Bm of the target occupant's body movement is greater than a predetermined body movement threshold Thb, the processor 11 evaluates that the reliability of the biometric information is low. The magnitude Bm of the target occupant's body movement represents the intensity of the target occupant's movement. The magnitude Bm of the target occupant's body movement will hereinafter be simply referred to as the magnitude Bm of body movement.

[0041] In this embodiment, the processor 11 evaluates the magnitude Bm of body movement based on the captured image. As a preparatory process for evaluating the magnitude Bm of body movement, the processor 11 identifies feature points of the target occupant by image recognition. Identifying feature points is a process of determining the positions of feature points that serve as references for calculating the magnitude Bm of body movement. In this embodiment, the feature points are both shoulders and the head. The feature points may be any part of the body. The feature points may be joint points such as shoulders, elbows, and knees. The feature points may be the chest or the eyes. The head may be the top of the head or the midpoint between the eyes.

[0042] The feature point to be identified may be only one location. The feature points to be identified and the number of feature points may be changed as appropriate depending on the position of the target seat. If the target seat is a rear seat, the feature point to be identified may be only one shoulder instead of both shoulders.

[0043] The processor 11 recognizes the shoulders and head of the target occupant through image recognition. The processor 11 calculates the positional change over time of the shoulders based on multiple captured images. The processor 11 similarly calculates the positional change over time of the head. The processor 11 calculates the sum of the positional change over time of the shoulders and the positional change over time of the head as the total body movement. The sum corresponds to the magnitude Bm of the occupant's body movement.

[0044] The processor 11 determines whether the total body movement amount is greater than the body movement threshold Thb. If the total body movement amount is greater than the body movement threshold Thb, the processor 11 determines that the reduction condition is met. The body movement threshold Thb may be set arbitrarily. The body movement threshold Thb may be changed as appropriate depending on the position of the target seat. The body movement threshold Thb for a rear seat target seat may be set greater than the body movement threshold Thb for a driver's seat.

[0045] When acquiring the respiratory rate based on the change over time in the distance measurement value (e.g., its periodicity) associated with the occupant's breathing, it is difficult to separate the occupant's body movement from the body surface displacement due to the occupant's breathing. In other words, the greater the occupant's body movement, the lower the reliability of the biometric information acquired by the radio wave sensor 2. Therefore, if the magnitude of the occupant's body movement is greater than the body movement threshold Thb, the reliability of the biometric information is determined to be low. In general, the error between the true value and the measured value of the biometric information, in other words, the reliability of the measurement result, is difficult to directly evaluate. With the above configuration, the reliability of the measurement result of the biometric information can be determined with validity (i.e., appropriately) from the perspective of the amount of body movement.

[0046] The processor 11 evaluates the vehicle vibration level Vi based on the evaluation data. If the vehicle vibration level Vi is greater than a predetermined vibration threshold Thv, the processor 11 determines that the reliability of the biological information is low. The vehicle vibration level Vi is the magnitude of the effect of vehicle vibration. Hereinafter, the vehicle vibration level Vi will be simply referred to as the vibration level Vi.

[0047] In this embodiment, the processor 11 evaluates the vibration level Vi based on the vibration data, steering angle data, acceleration data, deceleration data, and vehicle speed data. The processor 11 determines that the vibration level Vi is higher as the magnitude of vibration inside the vehicle indicated by the vibration data increases. The processor 11 determines that the vibration level Vi is higher as the steering angle indicated by the steering angle data increases. The processor 11 determines that the vibration level Vi is higher as the accelerator pedal depression amount indicated by the acceleration data increases. The processor 11 determines that the brake pedal depression amount indicated by the deceleration data increases. The processor 11 determines that the vibration level Vi is higher as the vehicle speed indicated by the vehicle speed data increases. Note that in other embodiments, the processor 11 may determine the vibration level Vi based on at least one of the vibration data, steering angle data, acceleration data, deceleration data, and vehicle speed data. The processor 11 may also determine the vibration level Vi from the displacement amount or control amount of the suspension.

[0048] The processor 11 determines whether the vibration level Vi is greater than the vibration threshold value Thv. If the vibration level Vi is greater than the vibration threshold value Thv, the processor 11 determines that the reduction condition is satisfied. The vibration threshold value Thv may be set arbitrarily. The vibration threshold value Thv may be changed appropriately depending on the position of the target seat. If the target seat is a rear seat, the vibration threshold value Thv may be set higher than that of the driver's seat.

[0049] When the radio wave sensor 2 acquires the respiratory rate based on the change in the distance measurement value over time associated with the occupant's breathing, it is difficult to separate the vehicle vibration from the surface displacement caused by the occupant's breathing. In other words, if the vehicle vibration level Vi is greater than a certain value, the reliability of the biometric information may be low. Therefore, as the vibration level Vi increases, the reliability of the biometric information acquired by the radio wave sensor 2 may be reduced. The vibration level Vi is also expected to increase when the vehicle accelerates, decelerates, curves, or travels at high speeds. In other words, the vibration level Vi is expected to increase when the amount of operation of the steering wheel, accelerator pedal, or brake pedal is greater than a certain value or when the vehicle speed is greater than a certain value. Therefore, when the vibration level Vi is greater than the vibration threshold value Thv, the reliability of the biometric information is determined to be low.

[0050] In this embodiment, the processor 11 evaluates the reliability of the biological information as high when the magnitude of body movement Bm is equal to or less than a predetermined body movement threshold Thb and the vibration level Vi is equal to or less than a predetermined vibration threshold Thv. Note that the reliability of the biological information may be evaluated using only either the magnitude of body movement Bm or the vibration level Vi. In this case, the processor 11 may determine that the reliability is not low or that the reliability is high when the magnitude of body movement Bm is equal to or less than the body movement threshold Thb. The processor 11 may determine that the reliability is not low or that the reliability is high when the vibration level Vi is equal to or less than the vibration threshold Thv.

[0051] The processor 11 is configured to output the measurement result of the biological information according to the reliability to the ADASECU 4 that uses the biological information. If the reliability is equal to or less than a predetermined reliability threshold Thr, the processor 11 outputs a specific value (e.g., Nan: Not a Number) indicating that the biological information is unmeasurable as the measurement result. If the reliability is greater than the predetermined reliability threshold Thr, the processor 11 outputs the biological information as is as the measurement result.

[0052] <Processing Flow> A flow illustrating an example of processing performed by the processor 11 will be described using FIG. 2 . The processing flow starts when the vehicle's power switch is turned ON. The processing flow may be repeated until the power switch is turned OFF. For example, while the power switch is ON, the processing shown in FIG. 2 may be executed every 10 seconds, every 30 seconds, or every minute. This enables periodic collection of biometric information even while the vehicle is traveling. Note that one measurement process may include a process of driving the radio wave sensor 2 multiple times at a predetermined sampling interval to obtain multiple distance measurements. For example, one measurement process may include obtaining 50 or 100 or more distance measurements. Furthermore, the measurement process shown in FIG. 2 may be executed in response to an event such as opening or closing a door or locking the vehicle. This makes it possible to detect, for example, a child being left behind in a vehicle.

[0053] In step 11, the processor 11 acquires biometric information using the radio wave sensor 2. As described above, step 11 may include a process of driving the radio wave sensor 2 multiple times at a predetermined sampling interval to acquire multiple distance measurements. This results in time-series data of the distance measurements. The driving interval of the radio wave sensor 2, in other words, the sampling interval, may be set to a value sufficiently small (e.g., 1 / 100 or less) relative to the period of breathing or heartbeat, such as 10 microseconds. The processor 11 may determine the respiratory rate by analyzing observation data including the time-series data of the distance measurements. For example, by analyzing the time-series data of the distance measurements, the periodicity of distance changes resulting from the occupant's breathing may be identified, and the respiratory rate may be determined.

[0054] Of course, the method for identifying biometric information based on observation data is not limited to this, and various other methods may be applied. Alternatively, for example, time series data of the distance from the radio wave sensor 2 to the target location may be calculated based on the distance FFT data, and the time series data of the distance may be further subjected to FFT to obtain a frequency spectrum. The respiratory rate and heart rate may be identified by analyzing the signal of a desired signal band component. The desired signal band component may be a frequency component corresponding to the respiratory cycle (0.2 Hz to 1 Hz) or a frequency component corresponding to the heartbeat cycle (1.0 to 2.5 Hz). Furthermore, the processor 11 may measure biometric information from multiple candidate target locations (e.g., the chest and abdomen), evaluate both, and select the biometric information that provides the better results.

[0055] In step 12, the processor 11 acquires evaluation data, which is data for evaluating the reliability of the biometric information, from other on-board sensors. For example, the processor 11 acquires at least one of captured image data, vibration data, steering angle data, acceleration data, deceleration data, and vehicle speed data as the evaluation data.

[0056] In step S13, the processor 11 evaluates the reliability of the biological information based on the evaluation data acquired in step S12. Specifically, the processor 11 determines whether a predetermined condition (i.e., a reduction condition) that may cause a decrease in reliability is met based on the evaluation data. The processor 11 determines whether the magnitude of body movement Bm is greater than a predetermined body movement threshold Thb or whether the vibration level Vi is greater than a vibration threshold Thv. A case in which the magnitude of body movement Bm is greater than a predetermined body movement threshold Thb or a case in which the vibration level Vi is greater than a vibration threshold Thv corresponds to a case in which the reduction condition is met. Determining whether the reduction condition is met corresponds to evaluating the reliability of the biological information. If the reduction condition is met, the processor 11 determines that the reliability of the biological information has decreased. Conversely, if the reduction condition is not met, the processor 11 may determine that the reliability of the biological information is not low or is high.

[0057] If the answer is Yes in step 13, the processor 11 outputs a specific value (e.g., a Nan value) indicating that the biological information is not measurable as the measurement result to the ADASECU 4 (step 14). If the answer is No in step 13, the processor 11 outputs the biological information as is as the measurement result to the ADASECU 4 (step 15). Note that the specific value may be replaced with a specific code or the like.

[0058] The above configuration corresponds to a configuration in which biometric information acquired in a situation where the reliability of the biometric information may be low is handled separately from biometric information acquired in a situation where the reliability of the biometric information is guaranteed, thereby reducing the risk of providing unreliable biometric information to a biometric information user unit such as the ADASECU 4.

[0059] Summary of First Embodiment The processor 11 evaluates the reliability of the biological information acquired using the radio wave sensor 2, and outputs the measurement result of the biological information (respiratory rate) according to the reliability to the ADASECU 4. This allows the ADASECU 4 to appropriately use the acquired measurement result.

[0060] Furthermore, if the reliability is lower than the reliability threshold Thr, the processor 11 outputs information indicating that the biological information is unmeasurable as a measurement result. For example, even if the driver's respiratory rate indicates an abnormal value while driving, if the processor 11 determines that the reliability of the biological information is low, it outputs a measurement unmeasurable message to the ADASECU 4. This prevents the ADASECU 4 from erroneously issuing an emergency stop or warning. In other words, it prevents the ADASECU 4 from performing control using inaccurate biological information. In this way, this configuration reduces the risk of incorrect biological information measurement results being used by the biological information user (such as another application).

[0061] In the previous embodiment, the processor 11 evaluated the magnitude Bm of the body movement based on the camera image. In another embodiment, the processor 11 may obtain the magnitude Bm of the body movement based on the vibration data, the steering angle data, the acceleration data, the deceleration data, and the vehicle speed data. For example, the processor 11 may determine that the magnitude Bm of the body movement is greater as the magnitude of the vibration inside the vehicle included in the vibration data is greater.

[0062] The processor 11 may use, as evaluation data, the observation data input from the radio wave sensor 2. That is, the magnitude Bm of body movement or the vibration level Vi may be acquired based on the observation data input from the radio wave sensor 2. Specifically, if the change over time in the distance measurement value is much larger than the value due to respiration or heartbeat, it may be determined that the magnitude Bm of body movement is large or the vibration level Vi is high.

[0063] The processor 11 may be configured to calculate reliability as a score based on at least one type of evaluation data, and determine that reliability is low when the score is equal to or less than a predetermined reliability threshold Thr. The score indicating the reliability of the biometric information will hereinafter also be referred to as reliability S. When the processor 11 evaluates that the reliability S is equal to or less than the predetermined reliability threshold Thr, the processor 11 may output the biometric information together with information indicating low reliability as the measurement result. When the processor 11 evaluates that the reliability S is greater than the reliability threshold Thr, the processor 11 may output the biometric information together with information indicating high reliability as the measurement result.

[0064] For example, the processor 11 may evaluate the reliability S by combining parameters of the review type, such as the magnitude of vibration, the steering angle value, the operation amount of the accelerator pedal, the operation amount of the brake pedal, and the vehicle speed. For example, the processor 11 may calculate the reliability S using Equation 1.

[0065] [Equation 1] S = A1 x X1 + A2 x X2 + A3 x X3 + A4 x X4 + A5 x X5 + A6 x X6 In equation (1), "X1" indicates the magnitude of vibration inside the vehicle. "X2" indicates the amount of steering angle operation. "X3" indicates the amount of accelerator pedal depression. "X4" indicates the amount of brake pedal depression. "X5" indicates vehicle speed. "X6" indicates the magnitude Bm of occupant body movement. "A1" to "A6" indicate coefficients. The values ​​of coefficients A1 to A6 can be set to appropriate values ​​by performing actual vehicle evaluation. The processor 11 may determine that the reliability of the biological information is low when the reliability S is greater than a predetermined total threshold Ths.

[0066] The coefficient A6 by which the magnitude Bm of the body movement is multiplied may be a different value depending on the distance from the radio wave sensor 2. For example, the value of the coefficient A6 may be increased as the distance from the radio wave sensor 2 decreases.

[0067] Body movements of a target occupant close to the radio wave sensor 2 have a significant adverse effect on the measurement of biological information. Therefore, the reliability of the biological information can be determined more accurately by increasing the value of coefficient A6 as the distance from the radio wave sensor 2 decreases.

[0068] The value of coefficient A6 may be changed depending on the target seat. The storage 13 may store a coefficient A6 for each target seat. The processor 11 may be configured to read and use the value of coefficient A6 corresponding to the target seat. In addition to coefficient A6, the processor 11 may change the values ​​of coefficients A1 to A6 depending on the target seat. For example, if the target seat is the driver's seat, the values ​​of coefficients A1, A2, and A6 may be set to values ​​larger than coefficients A3, A4, A5, etc. In this case, coefficient A2 may be a value larger than 0.

[0069] If the target seat is other than the driver's seat, the values ​​of coefficients A1 and A6 may be set to values ​​larger than coefficients A2, A3, A4, A5, etc. If the target seat is other than the driver's seat, the value of coefficient A2 may be set to 0. Furthermore, coefficients A1 and A6 when the target seat is other than the driver's seat may be set to values ​​smaller than coefficients A1 and A6 when the target seat is the driver's seat. For example, if the target seat is other than the driver's seat, the value of the steering angle operation amount may not be used in evaluating reliability.

[0070] <Second Embodiment> In the first embodiment, biometric information was acquired only from the radio wave sensor 2, but the same type of biometric information may be acquired using another sensor. In this embodiment, the biometric information in the first embodiment, i.e., the biometric information acquired using the radio wave sensor 2, is referred to as first biometric information. In this embodiment, second biometric information, which is the same type of biometric information as the first biometric information, is acquired using the camera 3. The first biometric information can be referred to as radio wave sensor-based biometric information, and the second biometric information can be referred to as camera-based biometric information. An example of the biometric information acquired by the biometric detection device 1 of this embodiment (i.e., the first and second biometric information) is heart rate. The evaluation data in the first embodiment is referred to as first evaluation data. The confidence threshold Thr in the first embodiment is referred to as first confidence threshold Thr1. In this embodiment, the degradation condition in the first embodiment is referred to as first degradation condition.

[0071] In this embodiment, the vehicle equipped with the living body detection device 1 may further include an illuminance sensor (not shown) as another on-board sensor. The illuminance sensor detects the brightness inside the vehicle. Specifically, the illuminance sensor detects the illuminance inside the vehicle. The illuminance sensor outputs data indicating the illuminance inside the vehicle to the living body detection device 1 as illuminance data.

[0072] The processor 11 performs a process of calculating the heart rate based on changes in color or brightness of the captured image over time. Specifically, the processor 11 detects the facial area of ​​the target occupant in the captured image by image recognition. The processor 11 calculates the heart rate (actually, the pulse rate) based on changes in color or brightness of the facial area over time. Various methods, such as remote photoplethysmography (rPPG), may be applied as a method for estimating the heart rate (pulse rate) through image analysis.

[0073] The processor 11 acquires second evaluation data, which is data for evaluating the reliability of the second biometric information, from another on-board sensor. The processor 11 acquires captured image data and illuminance data as evaluation data. The processor 11 evaluates the reliability of the second biometric information based on the second evaluation data. Specifically, the processor 11 determines, based on the second evaluation data, whether a predetermined condition (hereinafter also referred to as a second degradation condition) that may cause a degradation of the reliability of the second biometric information is satisfied. The second degradation condition corresponds to the second predetermined condition.

[0074] The processor 11 acquires the brightness Lu of the interior of the vehicle based on the second evaluation data. The brightness Lu of the interior of the vehicle will be simply referred to as brightness Lu hereinafter. The brightness Lu may be illuminance or luminance. In this embodiment, the processor 11 determines the illuminance included in the illuminance data as the brightness Lu. Alternatively, the processor 11 may determine the brightness Lu as the value of the luminance of the entire captured image.

[0075] The processor 11 acquires a change amount Luc in the brightness Lu based on the second evaluation data. Hereinafter, the change amount Luc in the brightness Lu will be simply referred to as the change amount Luc. In this embodiment, the processor 11 acquires the change amount Luc based on the captured image included in the captured image data. The processor 11 calculates the change amount Luc as the amount of change over time in the brightness of the face area of ​​the target occupant in the captured image. Specifically, the processor 11 calculates the difference between the maximum and minimum brightness values ​​of the face area of ​​the target occupant in the captured image within a predetermined time period.

[0076] The processor 11 determines that the second deterioration condition is met if the brightness Lu is less than a predetermined brightness threshold ThL or the change Luc is greater than a predetermined brightness change threshold ThLc. When the vehicle interior is dark, such as at night, it is difficult to acquire biometric information based on color changes in the captured image. Therefore, in this case, the reliability of the second biometric information may be low. Furthermore, if the change Luc is greater than a certain value, it is possible that the brightness of the interior has suddenly changed due to ambient light. In this case, it is difficult to distinguish whether the color change is due to the occupant's biological activity or to ambient light. In other words, if the brightness Lu is less than a certain value or the change Luc is greater than a certain value, the reliability of the second biometric information may be low.

[0077] Therefore, the processor 11 determines that the reliability of the second biological information is low when the brightness Lu is smaller than a predetermined brightness threshold ThL or the change amount Luc is larger than a predetermined brightness change threshold ThLc.

[0078] Based on the evaluation results of the reliability of the first biological information and the evaluation results of the reliability of the second biological information, the processor 11 selects, from the first biological information and the second biological information, the biological information to be output as a measurement result to the ADASECU 4. The processor 11 selects the biological information that is not determined to be low in reliability and outputs it to the ADASECU 4.

[0079] Specifically, when the processor 11 determines that the first degradation condition is satisfied but the second degradation condition is not satisfied, the processor 11 selects the second biological information as the measurement result and outputs it to the ADASECU 4. When the processor 11 determines that the first degradation condition is not satisfied but the second degradation condition is satisfied, the processor 11 selects the first biological information as the measurement result and outputs it to the ADASECU 4. As a result, the biological information that is not determined to have low reliability is output to the ADASECU 4.

[0080] In this embodiment, when the processor 11 determines that the reliability of both the first biological information and the second biological information is not low, it selects the first biological information as the measurement result and outputs it to the ADASECU 4. Specifically, when the processor 11 determines that the first degradation condition and the second degradation condition are not satisfied, it selects the first biological information as the measurement result and outputs it to the ADASECU 4. This is because obtaining biological information using the radio wave sensor 2 generally tends to have higher resolution and more accurate biological information than obtaining biological information using the camera 3.

[0081] When the processor 11 determines that the reliability of both the first biological information and the second biological information is low, the processor 11 outputs a signal indicating that the biological information is unmeasurable to the ADASECU 4. Specifically, when the processor 11 determines that the first degradation condition and the second degradation condition are satisfied, the processor 11 outputs a signal indicating that the biological information is unmeasurable (e.g., Nan value) to the ADASECU 4.

[0082] When it is determined that the second deterioration condition is satisfied, the processor 11 may output information indicating that the second biological information is not measurable as the measurement result.

[0083] <Processing Flow> A flow showing an example of processing performed by the processor 11 will be described with reference to Fig. 3. The start and end timings of the processing flow are the same as those in the first embodiment.

[0084] Step 21 is a step of acquiring first biometric information and second biometric information. In step 21, the processor 11 acquires observation data from the radio wave sensor 2 and calculates the first biometric information (heart rate) based on the observation data. Also in step 21, the processor 11 performs processing to calculate the second biometric information (heart rate) based on changes over time in color and brightness of the captured image received from the camera 3. In step 22, the processor 11 acquires first evaluation data and second evaluation data from other on-board sensors.

[0085] In step 23, the processor 11 evaluates the reliability of the second biometric information. Specifically, the processor 11 determines whether a second degradation condition is met based on the second evaluation data. The processor 11 determines whether the brightness Lu is smaller than the brightness threshold ThL or whether the change amount Luc is greater than the brightness change threshold ThLc. If the second degradation condition is met, the processor 11 determines that the reliability of the second biometric information is low. If the second degradation condition is not met, the processor 11 determines that the reliability of the second biometric information is not low. If the answer is Yes in step 23, proceed to step 24.

[0086] In step 24, the processor 11 evaluates the reliability of the first biological information. Specifically, the processor 11 determines whether the first deterioration condition is satisfied based on the first evaluation data. The processor 11 determines whether the magnitude of body movement Bm is greater than a predetermined body movement threshold Thb or whether the vibration level Vi is greater than a vibration threshold Thv. If the answer is Yes in step 24, the processor 11 outputs a value indicating that the biological information is unmeasurable to the ADASECU 4 as the measurement result (step 25). If the answer is No in step 24, the processor 11 outputs the first biological information to the ADASECU 4 as the measurement result (step 27).

[0087] If the answer is No in step 23, the process proceeds to step 26. In step 26, the processor 11 evaluates the reliability of the first biological information. As in step 24, the processor 11 determines whether the first deterioration condition is met based on the first evaluation data. The processor 11 determines whether the magnitude of body movement Bm is greater than a predetermined body movement threshold Thb, or whether the vibration level Vi is greater than a vibration threshold Thv. If the answer is Yes in step 26, the processor 11 outputs the second biological information as the measurement result to the ADASECU 4 (step 28). If the answer is No in step 26, the processor 11 outputs the first biological information as the measurement result to the ADASECU 4 (step 27).

[0088] Summary of Second Embodiment According to this embodiment, based on the evaluation results of the reliability of the first biological information and the evaluation results of the reliability of the second biological information, one of the first biological information and the second biological information is selected to be output to the ADASECU 4 as a measurement result. The selected biological information is output to the ADASECU 4. This allows the ADASECU 4 to acquire the more appropriate biological information from the first biological information and the second biological information. Therefore, it is expected that the ADASECU 4 will use highly reliable biological information.

[0089] <Modification> The camera 3 may include a calculation unit that calculates biometric information based on a captured image. The camera 3 may transmit the calculated biometric information to the processor 11.

[0090] The light receiving sensor 31 may transmit a signal according to the illuminance to the living body detection device 1. The processor 11 may calculate the illuminance based on the signal from the light receiving sensor 31 and set it as the brightness Lu.

[0091] When the biological information acquired by the biological detection device 1 is a respiratory rate, the processor 11 may perform a process of calculating the respiratory rate based on the body movement of the occupant accompanying breathing, based on the captured image data. Specifically, the processor 11 recognizes the chest or abdomen of the target occupant in the captured images by image recognition. The processor 11 calculates changes in the chest or abdomen over time based on multiple captured images, and calculates the respiratory rate.

[0092] As another example, there may be cases where it is assumed that acquiring biometric information using the camera 3 is more accurate than acquiring biometric information using the radio wave sensor 2. In such a case, if the processor 11 determines that the reliability of both the first biometric information and the second biometric information is not low, it may select the second biometric information as the measurement result and output it to the ADASECU 4.

[0093] The processor 11 may determine which of the biological information is more reliable based on the first evaluation data and the second evaluation data, and may be configured to output the biological information with the higher reliability.

[0094] The biometric information using unit may be a device, such as the ADASECU 4, that is provided separately from the biometric detection device 1 and is connected to the biometric detection device 1 via a wired or wireless connection. The external device serving as the biometric information using unit may be a server. In other embodiments, the biometric information using unit may be a hardware / software module provided inside the biometric detection device 1. The biometric information using unit may be various applications, such as emergency control for poor health / falling asleep, a notification of child abandonment, or an application for health management. The term "application" may be replaced with "device," "subsystem," or the like.

[0095] (Disclosure of Technical Ideas) This specification discloses multiple technical ideas described in the following multiple clauses. Some clauses may be described in a multiple dependent form, with the subsequent clause alternatively referring to the preceding clause. Furthermore, some clauses may be described in a multiple dependent form, with the subsequent clause referring to another multiple dependent clause. These multiple dependent clauses define multiple technical ideas.

[0096] (Technical Idea 1) A biometric detection device for acquiring biometric information of an occupant of a moving body, comprising a control unit (11) for acquiring the biometric information using a radio wave sensor, wherein the control unit is configured to acquire evaluation data from the radio wave sensor or other on-board sensors, which is data for evaluating the reliability of the biometric information, evaluate the reliability of the biometric information based on the evaluation data, and output measurement results of the biometric information according to the reliability to a biometric information usage unit that uses the biometric information.

[0097] (Technical Idea 2) A biological detection device described in Technical Idea 1, which determines whether or not a predetermined condition that may reduce the reliability is met based on the evaluation data, and if it determines that the predetermined condition is met, outputs information indicating that the biological information cannot be measured as the measurement result.

[0098] (Technical Idea 3) The biometric information is respiratory rate or heart rate, and the control unit acquires the biometric information based on changes in distance measurements over time associated with the occupant's breathing or heart rate observed using the radio wave sensor, acquires the magnitude of the occupant's body movement based on the evaluation data, and determines that the specified condition is met when the magnitude of the occupant's body movement is greater than a specified value, in the biometric detection device described in Technical Idea 2.

[0099] (Technical Idea 4) The biometric information is respiratory rate or heart rate, and the control unit acquires the biometric information based on changes in distance measurements over time associated with the occupant's breathing or heart rate observed using the radio wave sensor, acquires the vibration level of the moving body based on the evaluation data, and determines that the specified condition is met when the vibration level of the moving body is greater than a specified value, in the biometric detection device described in Technical Idea 2 or 3.

[0100] (Technical Idea 5) A biometric detection device described in any one of Technical Ideas 2 to 4, wherein the biometric information acquired using the radio wave sensor is defined as first biometric information, the evaluation data is defined as first evaluation data, the other vehicle-mounted sensor includes a camera, and the control unit: acquires second biometric information, which is the same type of biometric information as the first biometric information, using the camera; acquires second evaluation data, which is data for evaluating the reliability of the second biometric information, from the other vehicle-mounted sensor; evaluates the reliability of the second biometric information based on the second evaluation data; and selects the biometric information to output to the biometric information usage unit as the measurement result from the first biometric information and the second biometric information based on the evaluation result of the reliability of the first biometric information and the evaluation result of the reliability of the second biometric information.

[0101] (Technical Idea 6) A biological detection device as described in Technical Idea 5, wherein the specified condition is a first specified condition, and the control unit determines whether a second specified condition that may reduce the reliability of the second biological information is met based on the second evaluation data, and if it determines that the second specified condition is met, outputs information indicating that the second biological information cannot be measured as the measurement result.

[0102] (Technical Idea 7) The control unit of the biological detection device described in Technical Idea 6 acquires the second biological information based on color changes in the image captured by the camera, acquires the brightness of the interior of the moving body based on the second evaluation data, and determines that the second specified condition is met when the brightness is less than a specified value or the amount of change in brightness is greater than a specified value.

[0103] (Technical Idea 8) A biometric detection method executed by a processor for acquiring biometric information of an occupant of a moving body, comprising: acquiring the biometric information using a radio wave sensor; acquiring evaluation data from the radio wave sensor or another on-board sensor, the evaluation data being data for evaluating the reliability of the biometric information; evaluating the reliability of the biometric information based on the evaluation data; and outputting measurement results of the biometric information according to the reliability to a biometric information usage unit that uses the biometric information.

Claims

1. A biometric detection device for acquiring biometric information of an occupant of a moving body, comprising a control unit (11) for acquiring the biometric information using a radio wave sensor, wherein the control unit is configured to acquire evaluation data from the radio wave sensor or other on-board sensors, which is data for evaluating the reliability of the biometric information, evaluate the reliability of the biometric information based on the evaluation data, and output the measurement results of the biometric information according to the reliability to a biometric information usage unit that uses the biometric information.

2. A biological detection device as described in claim 1, which determines whether or not a predetermined condition that may reduce the reliability is met based on the evaluation data, and if it determines that the predetermined condition is met, outputs information indicating that the biological information cannot be measured as the measurement result.

3. The biological information is respiratory rate or heart rate, and the control unit acquires the biological information based on changes in distance measurements over time associated with the occupant's breathing or heart rate observed using the radio wave sensor, acquires the magnitude of the occupant's body movement based on the evaluation data, and determines that the specified condition is met if the magnitude of the occupant's body movement is greater than a specified value.

4. The biological information is respiratory rate or heart rate, and the control unit acquires the biological information based on changes in distance measurements over time associated with the occupant's breathing or heart rate observed using the radio wave sensor, acquires the vibration level of the moving body based on the evaluation data, and determines that the specified condition is met when the vibration level of the moving body is greater than a specified value.

5. The biometric detection device of claim 2, wherein the biometric information acquired using the radio wave sensor is defined as first biometric information, the evaluation data is defined as first evaluation data, the other vehicle-mounted sensor includes a camera, and the control unit: acquires second biometric information, which is the same type of biometric information as the first biometric information, using the camera; acquires second evaluation data, which is data for evaluating the reliability of the second biometric information, from the other vehicle-mounted sensor; evaluates the reliability of the second biometric information based on the second evaluation data; and selects the biometric information to output to the biometric information usage unit as the measurement result from the first biometric information and the second biometric information based on the evaluation result of the reliability of the first biometric information and the evaluation result of the reliability of the second biometric information.

6. A biological detection device as described in claim 5, wherein the specified condition is a first specified condition, and the control unit determines whether a second specified condition that may reduce the reliability of the second biological information is met based on the second evaluation data, and if it determines that the second specified condition is met, outputs information indicating that the second biological information is unmeasurable as the measurement result.

7. The control unit of the biological detection device described in claim 6 acquires the second biological information based on color changes in the image captured by the camera, acquires the brightness of the interior of the moving body based on the second evaluation data, and determines that the second specified condition is met when the brightness is less than a specified value or the amount of change in brightness is greater than a specified value.

8. A biometric detection method executed by a processor for acquiring biometric information of an occupant of a moving body, comprising: acquiring the biometric information using a radio wave sensor; acquiring evaluation data from the radio wave sensor or another on-board sensor, the evaluation data being data for evaluating the reliability of the biometric information; evaluating the reliability of the biometric information based on the evaluation data; and outputting measurement results of the biometric information according to the reliability to a biometric information usage unit that uses the biometric information.

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