In-vehicle Living Body Detection Method, Detection Device and Electronic Device

Abstract

The present invention provides a method for in-vehicle living body detection, a detection device and an electronic device. The method for in-vehicle living body detection includes: obtaining the force exerted by a target object on a seat; generating a target curve based on the force, where the target curve is used to characterize the correlation relationship among the input acceleration of the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmission ratio of the seat; and performing living body detection based on the target curve. The method for in-vehicle living body detection according to the present invention generates a target curve based on the force exerted by the target object on the seat and performs living body detection based on the target curve, which not only avoids the problem that the non-contact vital sign detection technology is easily affected by external vibrations and results in low accuracy of the detection results, but also avoids the problem that the non-contact vital sign monitoring technology has high requirements for the process, thereby achieving efficient, accurate and low-power consumption living body detection.

Description

Technical Field

[0001] The present invention relates to the technical field of in-vehicle living body detection, and particularly to an in-vehicle living body detection method, a detection device, and an electronic device. Background Art

[0002] Vehicles are used more and more frequently in people's daily lives. Therefore, detecting the vital signs in the vehicle has become an important measure to ensure people's lives and property safety. The existing vital sign detection technologies are greatly affected by external factors, resulting in inaccurate detection results and certain limitations in detection. Summary of the Invention

[0003] The present invention provides an in-vehicle living body detection method, a detection device, and an electronic device to solve the defect of inaccurate detection results in the prior art and achieve efficient and accurate living body detection.

[0004] The present invention provides an in-vehicle living body detection method, including:

[0005] Obtaining the force exerted by a target object on a seat;

[0006] Generating a target curve based on the force, where the target curve is used to characterize the correlation between the input acceleration on the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmissibility of the seat;

[0007] Performing living body detection based on the target curve.

[0008] According to the in-vehicle living body detection method provided by the present invention, the target curve includes at least one of a vibration transfer curve and a coherence curve, and the performing living body detection based on the target curve includes:

[0009] Determining that the force is a vertical excitation, and determining that the target object is a living body when the vibration frequency of the target object is a first target value and the secondary peak value of the vibration transfer curve reaches a second target value;

[0010] Or,

[0011] Determining that the force is a lateral excitation, and determining that the target object is a living body when the vibration transfer curve has a second peak value within a first target frequency range;

[0012] Or,

[0013] Determining that the force is a lateral excitation, and determining that the target object is a living body when the coherence curve drops within a second target frequency range.

[0014] A method for in-vehicle living body detection provided by the present invention, generating a target curve based on the acting force, includes:

[0015] Determine the target curve based on at least one of the input acceleration, the output acceleration, and the main frequency, where the target curve includes at least one of a vibration transfer curve and a coherence curve.

[0016] A method for in-vehicle living body detection provided by the present invention, determining the target curve based on at least one of the input acceleration, the output acceleration, and the main frequency, includes:

[0017] Based on the input acceleration, the output acceleration, and the main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, and the auto-power spectrum of the input acceleration;

[0018] Based on the cross-power spectrum of the input acceleration and the output acceleration and the auto-power spectrum of the input acceleration, determine the vibration transfer curve.

[0019] A method for in-vehicle living body detection provided by the present invention, determining the target curve based on at least one of the input acceleration, the output acceleration, and the main frequency, includes:

[0020] Based on the input acceleration, the output acceleration, and the main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration;

[0021] Based on the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration, determine the coherence curve.

[0022] A method for in-vehicle living body detection provided by the present invention, after performing living body detection based on the target curve, the method further includes:

[0023] When determining that the target object is a living body, output an alarm message based on the status information of the target object.

[0024] The present invention also provides an in-vehicle living body detection device, including:

[0025] A first acquisition module, configured to acquire the acting force of a target object on a seat;

[0026] A first generation module, configured to generate a target curve based on the acting force, where the target curve is used to characterize the correlation relationship among the input acceleration on the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmission rate of the seat;

[0027] The first determination module is configured to perform in-vehicle living body detection based on the target curve.

[0028] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the steps of the in-vehicle living body detection method as described in any one of the above are implemented.

[0029] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the in-vehicle living body detection method as described in any one of the above are implemented.

[0030] The present invention also provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the in-vehicle living body detection method as described in any one of the above are implemented.

[0031] The in-vehicle living body detection method, detection device, and electronic device provided by the present invention generate a target curve based on the force exerted by a target object on a seat, and perform living body detection based on the target curve, which not only avoids the problem that the non-contact vital sign detection technology is easily affected by external vibrations and results in low accuracy of detection results, but also avoids the problem that the non-contact vital sign detection technology has high requirements for technology, thereby realizing efficient, accurate, and low-power consumption living body detection. Description of the Drawings

[0032] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 is a flowchart of the in-vehicle living body detection method provided by the present invention;

[0034] Figure 2 is a structural diagram of the in-vehicle living body detection device provided by the present invention;

[0035] Figure 3 is a structural diagram of the electronic device provided by the present invention. Detailed Embodiments

[0036] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts belong to the scope of protection of the present invention.

[0037] The following will describe Figure 1 the in-vehicle living body detection method of the present invention in conjunction with

[0038] The execution subject of this in-vehicle living body detection method can be an in-vehicle living body detection device provided on the vehicle, or a server communicatively connected to the vehicle, or can also be a user's terminal communicatively connected to the vehicle, such as a mobile phone, a tablet computer, a computer, a watch, and an in-vehicle terminal, etc.

[0039] As Figure 1 shown, this in-vehicle living body detection method includes: step 110, step 120, and step 130.

[0040] Step 110: Obtain the force exerted by the target object on the seat;

[0041] In this step, the object is any object or living body other than vehicle components inside the vehicle, including but not limited to: people, animals, and sundries such as clothing or suitcases.

[0042] The target object is the object for which living body judgment is required.

[0043] It can be understood that the seat in the vehicle is the component that is in direct contact with the target object and has the longest contact time. When there is a target object in the vehicle, the target object will exert a force on the vehicle's seat.

[0044] In the actual execution process, sensors can be set on the vehicle's seat to collect the force exerted by the target object on the seat.

[0045] Among them, each seat corresponds to at least one sensor.

[0046] It should be noted that the force exerted by the target object on the seat includes a vertical force and a lateral force. Among them, the lateral force is the force in the front-rear direction, and the vertical force is the force perpendicular to the ground direction.

[0047] Taking the front of the vehicle as the front as an example, the lateral direction can be set as the x direction, the left-right direction can be set as the y direction, and the vertical direction can be set as the z direction.

[0048] In some embodiments, the road spectrum information of the road surface can also be obtained and used as an auxiliary confirmation in the subsequent judgment process.

[0049] Among them, the road spectrum information is a power spectral density curve used to characterize the road surface unevenness.

[0050] It can be understood that the vibration characteristics of a vehicle may be different on different road surfaces, and this vibration characteristic will in turn affect the analysis of the force exerted by the target object on the seat.

[0051] By using the road spectrum information as an auxiliary confirmation in the subsequent analysis process, calculation errors caused by road surface differences can be avoided, which helps to improve the accuracy of the final detection result.

[0052] Step 120: Generate a target curve based on the force, where the target curve is used to characterize the correlation relationship between the input acceleration on the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmissibility of the seat.

[0053] In this step, the target curve is used to characterize the correlation relationship between the input acceleration on the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmissibility of the seat.

[0054] Among them, the input acceleration includes lateral input acceleration and vertical input acceleration; the output acceleration includes lateral output acceleration and vertical output acceleration.

[0055] The input acceleration is the acceleration on the seat surface, and the output acceleration is the acceleration during vehicle driving.

[0056] The input acceleration can be calculated based on the force, the output acceleration can be obtained based on sensors, or it can also be directly retrieved from the vehicle's server.

[0057] In subsequent embodiments, lateral excitation will be used to refer to lateral input acceleration and lateral output acceleration; vertical excitation will be used to refer to vertical input acceleration and vertical output acceleration.

[0058] The vibration transmissibility of the seat depends on the force exerted by the target object on the seat and the dynamic response of the seat. Among them, the vibration transmissibility of the seat exhibits non-linear characteristics.

[0059] It should be noted that the dynamic response of a seated human body is different from that of a rigid body of the same weight.

[0060] In addition, the vibration characteristics exhibited by the target object under vertical excitation and lateral excitation are also different.

[0061] In this embodiment, the target curve can include a target curve corresponding to lateral excitation and a target curve corresponding to vertical excitation.

[0062] In the actual execution process, a target curve corresponding to the lateral excitation can be generated based on the lateral excitation; a target curve corresponding to the vertical excitation can be generated based on the vertical excitation.

[0063] The inventors found in the R & D process that in the related art, there are mainly the following several in-vivo detection methods: (1) The BCG (ballistocardiogram) monitoring method based on acceleration sensing. This method can monitor heart rate, heart rate variability, and respiratory rate, etc., but is greatly affected by external vibrations or movements, has high requirements for the monitoring environment, and the detection results are unstable; (2) The BCG monitoring method based on fiber optic sensing. This method has high requirements for processing technology and is relatively expensive; (3) The BCG monitoring method based on Doppler radar. This method requires the signal transmitter to be kept on for a long time and consumes a high amount of energy; (4) The non-contact capacitive electrocardiogram monitoring method. This method is easily interfered by heat sources, light sources, and connection methods, and the accuracy of the detection results is relatively low; (5) The magnetoimpedance monitoring method. This method monitors the cardiopulmonary tissue structure through the change of the magnetic field and is easily affected by the magnetic field environment and the movement state of the monitored object, and both the monitoring accuracy and precision are not high.

[0064] In the embodiment of the present invention, by using the force exerted by the target object on the seat and generating a target curve based on the force exerted by the target object on the seat as a parameter for subsequent in-vivo detection, a contact data acquisition method is adopted, avoiding the problem that the non-contact vital sign detection technology is easily affected by external factors and results in low accuracy of the detection results; in addition, the method of the present application only needs to collect data when needed, and the energy consumption is low.

[0065] In some embodiments, step 120 may include: determining a target curve based on at least one of the input acceleration, output acceleration, and main frequency, and the target curve includes at least one of a vibration transfer curve and a coherence curve.

[0066] In this embodiment, the input acceleration is the acceleration of the seat surface;

[0067] The output acceleration is the acceleration during vehicle driving.

[0068] The main frequency is the main frequency of the vibration transmission rate of the seat.

[0069] Among them, both the input acceleration and the main frequency can be generated based on the force.

[0070] In the actual execution process, based on the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, the auto-power spectrum of the output acceleration, and the cross-power spectrum of the input acceleration and the output acceleration can be generated.

[0071] Then, based on at least one of the auto-power spectrum of the input acceleration, the auto-power spectrum of the output acceleration, the cross-power spectrum of the input acceleration and the output acceleration, and the main frequency, a target curve is determined.

[0072] It can be understood that the auto-power spectrum of the input acceleration may include the auto-power spectrum of the input acceleration corresponding to the vertical excitation and the auto-power spectrum of the input acceleration corresponding to the lateral excitation.

[0073] Among them, the auto-power spectrum of the input acceleration corresponding to the vertical excitation is generated based on the vertical input acceleration, and the auto-power spectrum of the input acceleration corresponding to the lateral excitation is generated based on the lateral input acceleration.

[0074] The auto-power spectrum of the output acceleration may include the auto-power spectrum of the output acceleration corresponding to the vertical excitation and the auto-power spectrum of the output acceleration corresponding to the lateral excitation.

[0075] Among them, the auto-power spectrum of the output acceleration corresponding to the vertical excitation is generated based on the vertical output acceleration, and the auto-power spectrum of the output acceleration corresponding to the lateral excitation is generated based on the lateral output acceleration.

[0076] The cross-power spectrum of the input acceleration and the output acceleration may include the cross-power spectrum of the input acceleration and the output acceleration corresponding to the vertical excitation and the cross-power spectrum of the input acceleration and the output acceleration corresponding to the lateral excitation.

[0077] Among them, the cross-power spectrum of the input acceleration and the output acceleration corresponding to the vertical excitation is generated based on the vertical input acceleration and the vertical output acceleration, and the cross-power spectrum of the input acceleration and the output acceleration corresponding to the lateral excitation is generated based on the lateral input acceleration and the lateral output acceleration.

[0078] In the actual execution process, a target curve may be generated based on the auto-power spectrum of the input acceleration, the cross-power spectrum of the input acceleration and the output acceleration, and the main frequency; or, a target curve may also be generated based on the auto-power spectrum of the input acceleration, the auto-power spectrum of the output acceleration, the cross-power spectrum of the input acceleration and the output acceleration, and the main frequency.

[0079] According to the in-vehicle living body detection method provided by the embodiments of the present invention, based on at least one of the input acceleration, the output acceleration, and the main frequency, a vibration transfer curve and a coherence curve can be generated, which have high accuracy and precision; by selecting at least one of the curves for subsequent living body detection, it has high flexibility and universality.

[0080] Next, step 120 will be described from two different implementation perspectives respectively.

[0081] First, in some embodiments, determining a target curve based on at least one of an input acceleration, an output acceleration, and a main frequency includes:

[0082] Determining a cross-power spectrum of the input acceleration and the output acceleration, and an auto-power spectrum of the input acceleration based on the input acceleration, the output acceleration, and the main frequency;

[0083] Determining a vibration transfer curve based on the cross-power spectrum of the input acceleration and the output acceleration and the auto-power spectrum of the input acceleration.

[0084] In this embodiment, the vibration transfer curve is a manifestation of the target curve.

[0085] The vibration transfer curve is used to characterize the ride vibration characteristics of the target object, that is, the vibration characteristics of the seat.

[0086] It should be noted that the vibration characteristics of the seat exhibit non-linear characteristics, and the dynamic response of a seated human body is different from that of a rigid body of the same weight. Among them, the vibration transmissibility in the vertical and longitudinal directions has the greatest impact on human ride comfort and is the most direct reflection.

[0087] In the actual execution process, the formula:

[0088]

[0089] can be used to determine the target curve;

[0090] where H(f) is the vibration transfer curve, f is the main frequency, S xy (f) is the cross-power spectrum of the input acceleration and the output acceleration, and S xx (f) is the auto-power spectrum of the input acceleration.

[0091] It should be noted that the vibration transfer curve includes: a vibration transfer curve corresponding to a vertical excitation and a vibration transfer curve corresponding to a lateral excitation.

[0092] Based on the auto-power spectrum of the input acceleration corresponding to the vertical excitation, the cross-power spectrum of the input acceleration and the output acceleration corresponding to the vertical excitation, and the main frequency, the vibration transfer curve corresponding to the vertical excitation can be generated through the above formula.

[0093] Based on the auto-power spectrum of the input acceleration corresponding to the lateral excitation, the cross-power spectrum of the input acceleration and the output acceleration corresponding to the lateral excitation, and the main frequency, the vibration transfer curve corresponding to the lateral excitation can be generated through the above formula.

[0094] In this embodiment, based on the input acceleration, output acceleration, and main frequency, the vibration transfer curve corresponding to the vertical excitation and the vibration transfer curve corresponding to the lateral excitation can be obtained respectively. During actual use, the best vibration transfer curve can be selected based on actual needs for subsequent in-vivo detection, which has high flexibility and is applicable to various situations.

[0095] Second, in some embodiments, determining a target curve based on at least one of the input acceleration, output acceleration, and main frequency includes:

[0096] Based on the input acceleration, output acceleration, and main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration;

[0097] Based on the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration, determine the coherence curve.

[0098] In this embodiment, the coherence curve is another form of manifestation of the target curve.

[0099] The coherence curve is used to characterize the coherence relationship between the input acceleration and the output acceleration.

[0100] During actual execution, the formula:

[0101]

[0102] can be used to determine the target curve;

[0103] where is the coherence curve, f is the main frequency, S xy (f) is the cross-power spectrum of the input acceleration and the output acceleration, S xx (f) is the auto-power spectrum of the input acceleration, s yy (y) is the auto-power spectrum of the output acceleration, and y is the output acceleration.

[0104] It should be noted that the coherence curve includes: the coherence curve corresponding to the vertical excitation and the coherence curve corresponding to the lateral excitation.

[0105] Based on the auto-power spectrum of the input acceleration corresponding to the vertical excitation, the auto-power spectrum of the output acceleration corresponding to the vertical excitation, and the cross-power spectrum of the input acceleration and the output acceleration corresponding to the vertical excitation, the coherence curve corresponding to the vertical excitation can be generated through the above formula.

[0106] Based on the auto-power spectrum of the input acceleration corresponding to the lateral excitation, the auto-power spectrum of the output acceleration corresponding to the lateral excitation, and the cross-power spectrum of the input acceleration and the output acceleration corresponding to the lateral excitation, the coherence curve corresponding to the lateral excitation can be generated through the above formula.

[0107] In this embodiment, based on the input acceleration, the output acceleration, and the main frequency, the coherence curve corresponding to the vertical excitation and the coherence curve corresponding to the lateral excitation can be obtained respectively. During actual use, the best coherence curve can be selected based on actual needs for subsequent in-vivo detection, with high flexibility and applicability to various situations.

[0108] Step 130: Perform in-vivo detection based on the target curve.

[0109] In this step, by comparing the target curve generated in step 120 with the target value, it can be determined whether the target object is a living body.

[0110] It should be noted that for target curves with different manifestations, their corresponding target values are different. For target curves corresponding to excitations in different directions, their corresponding target values are also different.

[0111] Among them, the target value can be user-defined.

[0112] The inventor found through experiments that under vertical excitation (z-direction), the transmissibility from the z-direction of the vehicle floor to the z-direction of the seat cushion of the seat generates a large peak near 5 Hz under excitations of different vibration magnitudes. At this time, the seat vibration transmissibility is close to the excitation frequency, resulting in resonance.

[0113] The vibration transmitted from the vehicle floor to the target object is amplified. At the same time, as the vibration magnitude increases, both the main frequency of the transmissibility and the magnitude of the vibration frequency will decrease.

[0114] Under lateral excitation (x-direction), the transmissibility from the x-direction of the vehicle floor to the x-direction of the seat cushion of the seat generates a trough near 4 Hz under excitations of different vibration magnitudes. As the vibration magnitude increases, both the frequency of this peak and the magnitude of the vibration transmissibility will increase.

[0115] During actual execution, by comparing the interval values of the lateral excitation and / or the vertical excitation, it can be determined whether there is a living body in the vehicle. Among them, the interval value is the vibration magnitude.

[0116] The inventor also found through multiple experiments that when the target object is a living body, the movement of the target object will generate interval values. Even for a sleeping baby, it is very difficult to remain completely still, so interval values will also be generated. However, when the target object is other stationary objects, interval values cannot be generated.

[0117] In this embodiment, by using the target curve for living body detection, it can be free from the interference of external factors, and the detection result has high precision and accuracy.

[0118] Next, the implementation manner of step 130 will be specifically described from two implementation perspectives respectively.

[0119] I. Vertical excitation

[0120] In some embodiments, the target curve includes at least one of a vibration transfer curve and a coherence curve. Step 130 may include:

[0121] Determine that the acting force is vertical excitation. When the vibration frequency is the first target value and the secondary peak value of the vibration transfer curve reaches the second target value, determine that the target object is a living body.

[0122] In this embodiment, the vertical excitation is the z-direction excitation.

[0123] The target curve under vertical excitation may include the vibration transfer curve corresponding to the vertical excitation.

[0124] Among them, the vibration transfer curve corresponding to the vertical excitation is used to characterize the transfer rate from the z-direction of the vehicle floor to the z-direction of the seat cushion.

[0125] The vibration frequency is the vibration frequency of the target object.

[0126] The first target value and the second target value can be user-defined. For example, the first target value is set to 5.5 Hz and the second target value is set to 12.5 Hz.

[0127] Under vertical excitation, when the target object and the seat show different vibration characteristics, at different vibration levels, the peak value at the main peak of the vibration transfer rate curve from the z-direction of the vehicle floor to the z-direction of the seat cushion is 12 Hz, and the secondary peak value is 22 Hz.

[0128] When the vibration frequency of the driver is 5.5 Hz and the secondary peak value of the vibration transfer curve is 12.5 Hz, it can be determined that there are vital signs in the vehicle currently.

[0129] II. Lateral excitation

[0130] In some embodiments, the target curve includes at least one of a vibration transfer curve and a coherence curve. Step 130 may include:

[0131] Determine that the acting force is a lateral excitation. When a second peak appears in the vibration transfer curve within the first target frequency range, determine that the target object is a living body.

[0132] In this embodiment, the lateral excitation is the x-direction excitation.

[0133] The target curve under lateral excitation may include the vibration transfer curve corresponding to the lateral excitation.

[0134] Among them, the vibration transfer curve corresponding to the lateral excitation is used to characterize the transfer rate from the x-direction of the vehicle floor to the x-direction of the seat cushion, or to characterize the transfer rate from the x-direction of the seat to the x-direction of the seat backrest.

[0135] The first target frequency range can be user-defined. For example, it can be set to 20Hz - 30Hz, or 18Hz - 35Hz, etc.

[0136] When the acting force is a lateral excitation, for the transfer rate curve from the x-direction of the vehicle floor to the x-direction of the seat cushion, when the target object is a living body, as the vibration level increases, the frequency of the peak of the vibration transfer curve corresponding to this lateral excitation and the magnitude of the vibration transfer rate will both decrease. At the same time, a second peak will appear near 20Hz - 30Hz in the transfer rate curve from the x-direction of the vehicle floor to the x-direction of the seat.

[0137] Then, by judging whether a second peak appears in the vibration transfer curve corresponding to the lateral excitation within the first target frequency range, it can be determined whether the target object is a living body.

[0138] When a second peak appears in the vibration transfer curve corresponding to the lateral excitation within the first target frequency range, it can be approximately considered that the target object is a living body; otherwise, it is considered that the target object is not a living body.

[0139] It should be noted that a similar conclusion can also be obtained for the vibration transfer curve from the x-direction of the vehicle floor to the x-direction of the seat backrest. The judgment method is the same as above and will not be elaborated here.

[0140] In some embodiments, the target curve includes at least one of the vibration transfer curve and the coherence curve. Step 130 may further include:

[0141] Determine that the acting force is a lateral excitation. When the coherence curve drops within the second target frequency range, determine that the target object is a living body.

[0142] In this embodiment, the target curve under lateral excitation may include the coherence curve corresponding to the lateral excitation.

[0143] Among them, the coherence curve corresponding to the lateral excitation is used to characterize the coherence relationship from the x-direction of the vehicle floor to the x-direction of the seat backrest.

[0144] The second target frequency range can be user-defined. For example, it can be set to 30 Hz - 40 Hz.

[0145] In the case where the acting force is a lateral excitation, for the coherence curve from the x-direction of the vehicle floor to the x-direction of the seat backrest, when the coherence curve drops within the second target frequency range, it can be approximately considered that there is a vital sign in the vehicle, and the target object is determined to be a living body.

[0146] According to the in-vehicle living body detection method provided by the embodiments of the present invention, a target curve is generated based on the acting force of the target object on the seat, and living body detection is performed based on the target curve, which not only avoids the problem that the non-contact vital sign detection technology is easily affected by external vibrations and results in low accuracy of the detection result, but also avoids the problem that the non-contact vital sign monitoring technology has high requirements for the process, thus achieving efficient, accurate and low-energy consumption living body detection.

[0147] In some embodiments, after step 130, the method may further include:

[0148] When it is determined that the target object is a living body, an alarm message is output based on the status information of the target object.

[0149] In this embodiment, the status information of the target object is used to characterize the current behavior or action and other information of the target object.

[0150] Based on the status information of the target object, it can be determined whether the target object has taken self-rescue measures currently.

[0151] When it is determined that the target object has not taken self-rescue currently, an alarm message is generated and output.

[0152] Among them, the alarm message is used to assist the system or the user in performing active and passive rescue on the target object in the vehicle.

[0153] The alarm message may include: rescue reminder, location of the vehicle, number of living bodies in the vehicle, and current status information of the target object, etc.

[0154] The alarm message can be output through at least one of the following ways:

[0155] First, the output can be in the form of text output.

[0156] In this embodiment, the alarm message can be displayed on the user's terminal in text form.

[0157] Second, the output can be in the form of voice output.

[0158] In this embodiment, the terminal of the user communicatively connected to the vehicle can warn the user by voice that there is a living body in the current vehicle and rescue is required.

[0159] Thirdly, the output can be in the form of an image output.

[0160] In this embodiment, while outputting an alarm prompt, the image of the interior of the vehicle will also be displayed.

[0161] Of course, in other embodiments, the output can also be in other forms, which can be determined according to actual needs, and the embodiments of the present invention do not limit this.

[0162] According to the in-vehicle living body detection method provided by the embodiments of the present invention, by outputting an alarm message based on the state information of the living body when it is determined that there is a living body in the vehicle, the user can be timely reminded to rescue the target object in the vehicle, preventing safety accidents caused by the target object being locked in the vehicle, thereby effectively protecting people's lives and property safety.

[0163] Next, the in-vehicle living body detection device provided by the present invention will be described. The in-vehicle living body detection device described below can be mutually referred to the in-vehicle living body detection method described above.

[0164] As Figure 2 shown, the in-vehicle living body detection device includes: a first acquisition module 210, a first generation module 220, and a first determination module 230.

[0165] The first acquisition module 210 is configured to acquire the force exerted by the target object on the seat;

[0166] The first generation module 220 is configured to generate a target curve based on the force, where the target curve is used to characterize the correlation between the input acceleration on the seat surface, the output acceleration of the vehicle, and the main frequency of the seat vibration transmissibility;

[0167] The first determination module 230 is configured to perform living body detection based on the target curve.

[0168] According to the in-vehicle living body detection device provided by the embodiments of the present invention, a target curve is generated based on the force exerted by the target object on the seat, and living body detection is performed based on the target curve, which not only avoids the problem that the non-contact vital sign detection technology is easily affected by external vibrations and results in low accuracy of detection results, but also avoids the problem that the non-contact vital sign monitoring technology has high requirements for technology, thereby achieving efficient, accurate, and low-power consumption living body detection.

[0169] In some embodiments, the target curve includes at least one of a vibration transfer curve and a coherence curve. The first determination module 230 can also be used for:

[0170] Determine that the acting force is a vertical excitation. When the vibration frequency of the target object is the first target value and the secondary peak value of the vibration transfer curve reaches the second target value, determine that the target object is a living body.

[0171] In some embodiments, the target curve includes at least one of a vibration transfer curve and a coherence curve. The first determination module 230 can also be used to:

[0172] Determine that the acting force is a lateral excitation. When the vibration transfer curve has a second peak within the first target frequency range, determine that the target object is a living body.

[0173] In some embodiments, the target curve includes at least one of a vibration transfer curve and a coherence curve. The first determination module 230 can also be used to:

[0174] Determine that the acting force is a lateral excitation. When the coherence curve drops within the second target frequency range, determine that the target object is a living body.

[0175] In some embodiments, the first generation module 220 can also be used to: determine the target curve based on at least one of the input acceleration, output acceleration, and main frequency. The target curve includes at least one of a vibration transfer curve and a coherence curve.

[0176] In some embodiments, the first generation module 220 can also be used to:

[0177] Based on the input acceleration, output acceleration, and main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, and the auto-power spectrum of the input acceleration;

[0178] Based on the cross-power spectrum of the input acceleration and the output acceleration and the auto-power spectrum of the input acceleration, determine the vibration transfer curve.

[0179] In some embodiments, the first generation module 220 can also be used to:

[0180] Based on the input acceleration, output acceleration, and main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration;

[0181] Based on the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration, determine the coherence curve.

[0182] In some embodiments, after step 130, the device can further include:

[0183] A first output module, configured to output an alarm message based on the status information of the target object when it is determined that the target object is a living body.

[0184] According to the in-vehicle living body detection device provided by an embodiment of the present invention, by outputting an alarm message based on the status information of the living body when it is determined that there is a living body in the vehicle, it can timely remind the user to rescue the target object in the vehicle, prevent safety accidents caused by the target object being locked in the vehicle, and thus effectively protect people's lives and property safety.

[0185] Figure 3 An example of a physical structure diagram of an electronic device is shown as Figure 3 shown. The electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340. Among them, the processor 310, the communication interface 320, and the memory 330 complete mutual communication through the communication bus 340. The processor 310 can call the logical instructions in the memory 330 to execute the in-vehicle living body detection method, and the method includes: obtaining the acting force of the target object on the seat; generating a target curve based on the acting force, where the target curve is used to characterize the correlation relationship between the input acceleration of the seat surface, the output acceleration of the vehicle, and the main frequency of the seat vibration transmissibility; performing living body detection based on the target curve.

[0186] In addition, when the logical instructions in the above-mentioned memory 330 are implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disc that can store program codes.

[0187] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the in-vehicle living body detection method provided by each of the above methods. The method includes: obtaining the force exerted by a target object on the seat; generating a target curve based on the force, where the target curve is used to characterize the correlation relationship between the input acceleration of the seat surface, the output acceleration of the vehicle, and the main frequency of the seat vibration transmissibility; and performing living body detection based on the target curve.

[0188] In yet another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the in-vehicle living body detection method provided by each of the above. The method includes: obtaining the force exerted by a target object on the seat; generating a target curve based on the force, where the target curve is used to characterize the correlation relationship between the input acceleration of the seat surface, the output acceleration of the vehicle, and the main frequency of the seat vibration transmissibility; and performing living body detection based on the target curve.

[0189] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0190] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, also by hardware. Based on such an understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disc, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0191] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. An in-vehicle living body detection method, characterized in that, it includes: Obtain the force exerted by the target object on the seat; Based on the force, generate a target curve, where the target curve is used to characterize the correlation between the input acceleration on the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmission ratio of the seat; Perform living body detection based on the target curve; The target curve includes a vibration transfer curve; The performing living body detection based on the target curve includes: Determine that the force is a vertical excitation. When the vibration frequency of the target object is the first target value and the secondary peak value of the vibration transfer curve reaches the second target value, determine that the target object is a living body.

2. The in-vehicle living body detection method according to claim 1, characterized in that, The target curve further includes a coherence curve. The performing living body detection based on the target curve includes: Determine that the force is a lateral excitation. When the vibration transfer curve has a second peak value within the first target frequency range, determine that the target object is a living body; Or, Determine that the force is a lateral excitation. When the coherence curve drops within the second target frequency range, determine that the target object is a living body.

3. The in-vehicle living body detection method according to claim 1, characterized in that, The generating a target curve based on the force includes: Based on at least one of the input acceleration, the output acceleration, and the main frequency, determine the target curve, and the target curve includes at least one of a vibration transfer curve and a coherence curve.

4. The in-vehicle living body detection method according to claim 3, characterized in that, The determining the target curve based on at least one of the input acceleration, the output acceleration, and the main frequency includes: Based on the input acceleration, the output acceleration, and the main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, and the auto-power spectrum of the input acceleration; Based on the cross-power spectrum of the input acceleration and the output acceleration and the auto-power spectrum of the input acceleration, determine the vibration transfer curve.

5. The in-vehicle living body detection method according to claim 3, characterized in that, The determining the target curve based on at least one of the input acceleration, the output acceleration, and the main frequency includes: Based on the input acceleration, the output acceleration, and the main frequency, determine the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration; Based on the cross-power spectrum of the input acceleration and the output acceleration, the auto-power spectrum of the input acceleration, and the auto-power spectrum of the output acceleration, determine the coherence curve.

6. The in-vehicle living body detection method according to any one of claims 1-5, characterized in that, After the performing living body detection based on the target curve, the method further includes: When it is determined that the target object is a living body, based on the status information of the target object, output an alarm message.

7. An in-vehicle living body detection device, characterized in that, it includes: A first acquisition module, configured to acquire the force exerted by a target object on the seat; A first generation module, configured to generate a target curve based on the force, wherein the target curve is used to characterize the correlation between the input acceleration of the seat surface, the output acceleration of the vehicle, and the main frequency of the vibration transmission rate of the seat; A first determination module, configured to perform living body detection based on the target curve; The target curve includes a vibration transfer curve; The first determination module is configured to: Determine that the force is a vertical excitation, and when the vibration frequency of the target object is a first target value and the secondary peak value of the vibration transfer curve reaches a second target value, determine that the target object is a living body.

8. An electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, when the processor executes the computer program, it implements the steps of the in-vehicle living body detection method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, it implements the steps of the in-vehicle living body detection method according to any one of claims 1 to 6.

10. A computer program product, including a computer program, characterized in that, when the computer program is executed by a processor, it implements the steps of the in-vehicle living body detection method according to any one of claims 1 to 6.

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