Intelligent steering wheel and hand physiological signal acquisition method thereof

Abstract

The embodiment of the invention provides an intelligent steering wheel and a hand physiological signal acquisition method thereof, and relates to the technical field of physiological signal monitoring. At least one guide groove is formed in the steering wheel body; the guide groove is used for accommodating a hand area when a driver holds the steering wheel body; the at least one measuring area is arranged in the guide groove; a photoelectric sensor and a pressure sensor are embedded in the measuring area; the controller is electrically connected with the photoelectric sensor and the pressure sensor; the controller is configured to generate a control instruction for controlling the photoelectric sensor according to a pressure value signal fed back by the pressure sensor; the control instruction is used for collecting physiological signals of the driver. According to the method, a driver does not need to additionally wear any equipment, the physiological data can be continuously and stably collected while privacy safety is ensured, implementation of personalized health services is supported, and the method has wide application prospects and important popularization value.

Description

Technical Field

[0001] The present application relates to the technical field of physiological signal monitoring, and in particular to an intelligent steering wheel and a method for collecting hand physiological signals thereof. Background Art

[0002] Physiological signals can reflect information about different states of the human body and are a major basis for clinical diagnosis. Physiological signals can help study the clinical physiological signs of various diseases. By monitoring changes in physiological parameters over a long period of time, key information that is difficult to obtain through short-term monitoring can be discovered, providing important data support for disease prevention and comprehensive evaluation.

[0003] Traditional electrocardiogram detection methods rely on direct contact between electrodes and the human body, which can achieve high-precision heart rate measurement and cardiac electrical activity analysis. Although its accuracy meets medical standards, it relies on complex measurement processes and special equipment, so its widespread application is limited to medical institutions, and data analysis requires the assistance of professional doctors.

[0004] As the demand for medical care continues to increase, long-term continuous monitoring of human physiological signals can provide important information for disease prevention and comprehensive and accurate medical evaluation. In recent years, the rapid development of integrated electronic technology has laid the foundation for the research of physiological signal acquisition systems with smaller size, lower power consumption, and long-term continuous detection, and various types of smart watches and bracelets have been derived from this. However, the accuracy of health measurements of bracelets and watches is heavily dependent on the user's wearing conditions. At the same time, long-term wearing of such devices may cause discomfort to users and affect their experience in daily life. Therefore, finding a more comfortable and imperceptible monitoring method has become the focus of research.

[0005] In the era of the Internet of Things, people's increasing demand for health and travel has made in-vehicle health monitoring and services the focus of the development of smart cockpit technology. With the growth of the economy and the improvement of living standards, the number of private cars has surged, which has promoted the development of in-vehicle health monitoring systems. At present, in-vehicle health services are still in their infancy, but the growth of market demand has brought it a broad space. Commonly used methods are based on vision to monitor driver health. However, this method has problems with privacy and accuracy, such as the camera may infringe on privacy and make the driver feel uncomfortable, and it mainly relies on external feature evaluation, which is difficult to accurately detect internal physiological changes. Environmental factors such as light and angle can also affect its accuracy. The camera system requires complex image processing technology, which increases cost and complexity. Summary of the invention

[0006] The embodiments of the present application provide an intelligent steering wheel and a method for collecting hand physiological signals thereof, so as to solve the problems of high monitoring cost and poor accuracy of existing devices and methods.

[0007] In a first aspect, the present application provides a smart steering wheel, comprising:

[0008] A steering wheel body; the steering wheel body is provided with at least one guide groove; the guide groove is used to accommodate the hand area of ​​the driver when holding the steering wheel body;

[0009] At least one measuring area is arranged in the guide groove; a photoelectric sensor and a pressure sensor are embedded in the measuring area;

[0010] A controller electrically connected to the photoelectric sensor and the pressure sensor; the controller is configured to: generate a control instruction for controlling the photoelectric sensor according to a pressure value signal fed back by the pressure sensor; the control instruction is used to collect physiological signals of the driver.

[0011] In some feasible embodiments, the measurement area includes a palm measurement area and / or at least one finger measurement area;

[0012] In some feasible embodiments, the guide groove is made of a flexible material.

[0013] In some feasible embodiments, the controller includes:

[0014] Intelligent control module; the intelligent control module is configured as:

[0015] Obtain the pressure value signal fed back by the pressure sensor in each measuring area;

[0016] If there is a pressure value corresponding to the pressure value signal that is within a preset interval, a control instruction is generated for controlling the photoelectric sensor in the same measurement area of ​​the pressure sensor to turn on, so as to obtain the physiological signal collected by the photoelectric sensor.

[0017] In some feasible embodiments, the controller further includes:

[0018] The data transmission module is configured to send the physiological signals collected by the photoelectric sensor to the car central control, cloud platform or mobile terminal, so that the user can obtain the analysis results corresponding to the physiological signals through the car central control, cloud platform or mobile terminal.

[0019] In some feasible embodiments, the physiological signal sent by the data transmission module is a qualified signal; and the intelligent control module is further configured to:

[0020] In response to a control instruction for controlling the photoelectric sensor to turn on, acquiring a physiological signal collected by the photoelectric sensor;

[0021] Performing denoising processing on the physiological signal;

[0022] Detect whether there is pulse interference in the physiological signal after denoising;

[0023] If not, then detecting whether there is a missing segment in the physiological signal after the pulse interference detection;

[0024] If not, then the physiological signal after the missing segment detection is tested for motion artifacts;

[0025] If not, the physiological signal after motion artifact detection is marked as a qualified signal.

[0026] In some feasible embodiments, the intelligent control module is further configured to:

[0027] If there is pulse interference in the physiological signal after denoising, and / or there is a missing segment in the physiological signal after pulse interference detection, and / or there is a motion artifact in the physiological signal after missing segment detection;

[0028] Then, an unqualified label is added to the physiological signal, and the step of acquiring the physiological signal collected by the photoelectric sensor is continued.

[0029] In some feasible embodiments, the intelligent control module is further configured to:

[0030] The measurement area information of the photoelectric sensor corresponding to the physiological signal with the unqualified label is sent to the car central control, cloud platform or mobile terminal.

[0031] In a second aspect, the present application provides a method for collecting hand physiological signals, which is applied to the smart steering wheel described in the first aspect, and the method includes:

[0032] Acquire a pressure value signal fed back by a pressure sensor in at least one measuring area of ​​the smart steering wheel;

[0033] If the pressure value corresponding to the pressure value signal is within a preset interval, obtaining a physiological signal collected by a photoelectric sensor located in the same measuring area of ​​the pressure sensor;

[0034] The physiological signal is sent to the car central control, cloud platform or mobile terminal, so that the user can obtain the analysis result corresponding to the physiological signal through the car central control, cloud platform or mobile terminal.

[0035] In some feasible embodiments, the method further includes:

[0036] Acquire a collection mode of the smart steering wheel; the collection mode includes full-area collection and single-area collection;

[0037] If the acquisition mode is full-area acquisition, then if the pressure value corresponding to the pressure value signal is within a preset interval, the step of acquiring the physiological signal acquired by the photoelectric sensor located in the same measurement area of ​​the pressure sensor includes:

[0038] If the pressure values ​​corresponding to the pressure value signals fed back by the pressure sensors in all the measuring areas are within the preset interval, then the physiological sub-signals collected by all the photoelectric sensors are obtained, and all the physiological sub-signals are combined into a physiological signal, or the physiological sub-signals are used as the physiological signal;

[0039] If the acquisition mode is single-area acquisition, the method includes:

[0040] Obtain the pressure value signal fed back by the pressure sensor in any measurement area of ​​the smart steering wheel.

[0041] The present application provides an intelligent steering wheel and a method for collecting hand physiological signals thereof, which collects the driver's hand physiological signals in real time through a photoelectric sensor device embedded in the steering wheel. The collected data can be used for subsequent data processing and analysis to generate health indicators such as blood pressure, blood oxygen saturation, heart rate, etc., or to evaluate the driver's status, thereby providing accurate and reliable support for driving safety and health monitoring. This application does not require the driver to wear any additional equipment. While ensuring privacy and security, it can continuously and stably collect physiological data, support the implementation of personalized health services, and has broad application prospects and important promotion value. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments are briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0043] Figure 1 A schematic diagram of a partial structure of a smart steering wheel provided in an embodiment of the present application;

[0044] Figure 2 A schematic diagram of the structure of a smart steering wheel provided in an embodiment of the present application;

[0045] Figure 3 This is a schematic diagram of the driver holding the steering wheel;

[0046] Figure 4 Schematic diagram of the target position of the driver's hand measurement;

[0047] Figure 5 A software structure diagram of a smart steering wheel provided in an embodiment of the present application;

[0048] Figure 6Schematic diagram of the process of performing quality assessment for intelligent control modules;

[0049] Figure 7 A flow chart of collecting hand physiological signals by a smart steering wheel provided in an embodiment of the present application;

[0050] Figure 8 A flowchart of a hand physiological signal acquisition method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0051] The present application aims to solve the limitations and privacy protection issues of existing in-vehicle health monitoring technologies, while overcoming the inconvenience caused by the use of wearable devices. To this end, the present application embodiment proposes a smart steering wheel with a hand physiological signal collection function and a collection method thereof.

[0052] See also Figure 1 , is a schematic diagram of a partial structure of a smart steering wheel provided in an embodiment of the present application;

[0053] Depend on Figure 1 It can be seen that the present application provides a smart steering wheel, comprising:

[0054] A steering wheel body 100; the steering wheel body 100 is provided with at least one guide groove 101; the guide groove 101 is used to accommodate the hand area of ​​the driver when holding the steering wheel body 100;

[0055] It should be noted that the steering wheel body 100 in this embodiment is not limited to Figure 1 As shown in the figure, it is generally believed that the structure of the steering wheel body 100 can be divided into three parts: a steering wheel outer ring, a steering wheel spoke, and a steering wheel center cover. The steering wheel outer ring can be a complete closed ring of a circle, a nearly circle or other shape, or a non-closed ring structure; at the same time, the position of the guide groove 101 on the steering wheel body 100 should be set according to driving rules and the driving habits of the driver. For example, the guide groove 101 can be set on one side or both sides of the steering wheel outer ring, or on the steering wheel spokes, etc.

[0056] In this embodiment, the guide groove 101 can be set to a groove structure recessed in the steering wheel body 100. The shape of the guide groove 101 should correspond to the shape of the driver's hand (or the average value calculated based on the body shape characteristics of most people). The guide groove 101 is used to guide the driver's hand to be correctly placed in the area where the physiological signal can be measured, ensuring that the driver's hand fits tightly with the measurement area. When the driver's hand is located in the guide groove 101 and tightly grasps the steering wheel body 100, the side wall of the guide groove 101 can prevent the driver's hand from moving toward other parts of the steering wheel body 100, thereby reducing the signal error of the subsequent physiological signal detection caused by the hand movement and improving the detection accuracy.

[0057] Depend on Figure 1 and Figure 2 As shown, the smart steering wheel further includes at least one measuring area 102 disposed in the guide groove 101; a sensor module 103 is embedded in the measuring area 102, and the sensor module 103 may include a photoelectric sensor and a pressure sensor;

[0058] In this embodiment, the working principle of the pressure sensor (Pressure Transduce, PT) is to detect the pressure applied to the sensor based on the change of resistance. When pressure is applied, the resistance of the sensor changes: the greater the pressure, the more conductive paths, and the lower the resistance of the sensor. By measuring the change in this resistance, the sensor can determine the magnitude of the applied pressure. A pressure sensor is used on the steering wheel to sense the state of the driver's hand on the steering wheel. It can be judged whether the signal measured by the current photoelectric sensor is accurate and reliable based on the driver's hand grip state.

[0059] In this embodiment, the photoelectric sensor measures physiological signals based on photoplethysmography (PPG), wherein PPG technology is a non-invasive technology for obtaining physiological signals by detecting changes in blood volume, and monitors changes in blood volume in living tissues by photoelectric means, thereby capturing specific physiological signals. The PPG method uses a light beam of a specific wavelength to illuminate the surface of the skin. With each heartbeat, the contraction and expansion of blood vessels will affect the transmission or reflection of light. When the light beam passes through the skin tissue and is reflected to the photoelectric sensor, the pulsation in the blood will cause periodic changes in light absorption due to the relatively constant light absorption characteristics of tissues such as muscles and bones. By converting these changing light signals into electrical signals and further analyzing the blood flow pattern, the user's physiological signals, such as heart rate, blood oxygen saturation, etc., can be obtained. This technology ensures high-precision capture of physiological signals and provides a reliable basis for health monitoring.

[0060] Further, in the embodiment of the present application, since the position where the driver's hand contacts the steering wheel body 100 includes the palm and multiple fingers, the measurement area can be subdivided into multiple sub-measurement areas corresponding to different hand areas, for example, the measurement area is divided into a palm measurement area and / or a finger measurement area, corresponding to different hand positions. It should be noted that the palm measurement area and the finger measurement area can be set separately or simultaneously.

[0061] See also Figure 3 As shown, when the driver holds the steering wheel body 100, the palm and fingers are in close contact with the steering wheel body 100 from different directions and positions, thereby determining the driver's hand measurement target position ( Figure 4 The shaded part), such as Figure 4 As shown, the shape and size of the guide groove 101 can be set accordingly for different hand measurement target positions to ensure the comfort of the driver when holding the steering wheel and to ensure that the pressure value information and the light signal can be measured.

[0062] Therefore, see Figure 2 As shown, in some embodiments, the measurement area may include a palm measurement area, or four finger measurement areas, or include the above five sub-measurement areas at the same time; wherein the four finger measurement areas correspond to the driver's index finger, middle finger, ring finger and little finger respectively.

[0063] At this time, the guide groove 101 can be further divided into a palm groove for accommodating the driver's hand when holding the steering wheel body 100, and four finger grooves for accommodating the driver's hand when holding the steering wheel body 100; wherein, the palm groove is located on the outer circumference of the steering wheel body 100, and the palm measurement area is located in the palm groove; the finger groove is located on the inner circumference of the steering wheel body, and the four finger grooves are arranged adjacent to each other according to the state when the hand grasps the steering wheel body 100, and the finger measurement area is located in the finger groove. At this time, the sensor module located in the palm measurement area is dedicated to measuring the physiological signal of the palm position, and the sensor module in each finger measurement area is dedicated to measuring the physiological signal corresponding to a single finger position. The embodiment of the present application uses the physiological signal obtained by multi-point measurement, which can be more accurate than the physiological signal obtained by single-point measurement.

[0064] In some embodiments, the guide groove 101 may be made of a flexible and / or stretchable material with good elasticity and cushioning properties. The flexible material can not only improve the comfort of the driver when holding the steering wheel, but also adapt to the hand shape and finger size of different users to ensure continuous and stable contact between the fingers and the sensor. The precision of the design of the guide groove 101 can effectively reduce the impact of hand movement on signal acquisition and avoid signal loss or misalignment due to posture deviation or looseness. The material of the guide groove 101 can be rubber, silicon, soft plastic, cloth or any combination thereof.

[0065] It should be noted that in the embodiments of the present application, the guide groove refers to a design structure that has the function of guiding the hand or finger to be correctly placed in the specified position. It is not limited to any specific shape, size or layout, and its role is to guide the physiological contact position of the user's hand, finger or other part through physical form or surface features to ensure the correct posture or position of the hand during use. Specifically, the guide groove can achieve the purpose of correct hand placement through different design methods, such as depression, groove, protrusion, edge or any other form. Its function is mainly to provide a stable physical contact area and guide the user's hand to maintain a specific posture and position during operation, thereby optimizing the use effect of the device and improving the user experience.

[0066] In addition, the finger-fitting design of the guide groove 101 helps to shield stray light in the external environment and prevent external light from entering the measurement area of ​​at least one sensor module. The wrapping and fit of the flexible material can effectively seal the contact area between the sensor and the finger, reduce the interference of ambient light, and thus improve the measurement accuracy of the photoelectric sensor. This structural design enables the photoelectric sensor to obtain high-quality physiological signals more accurately and stably during driving, providing more reliable support for health monitoring and driving safety assessment.

[0067] It should be noted that in the embodiment of the present application, it is not limited to the case where only one set of sensor modules is set in each measurement area. According to actual needs, more than one set of sensor modules can also be set in one measurement area.

[0068] In addition, for the position of the sensor module in the measurement area, the position can be adjusted or the sensor module can be added according to the identity of the driver. For example, there may be a certain difference in the finger length between male drivers and female drivers, resulting in different distances between the finger position and the palm position when male drivers and female drivers hold the same steering wheel. In order to make the steering wheel suitable for different drivers at the same time, the number of sensor modules can be increased, and the shape of the guide groove 101 can be designed accordingly to solve the above problem, which is not limited here.

[0069] The smart steering wheel also includes a controller electrically connected to the photoelectric sensor and the pressure sensor; in this embodiment, the controller can be a separately arranged control unit integrated inside the smart steering wheel (such as hardware such as a CPU or a single-chip microcomputer), or it can be a functional module integrated in the vehicle's electronic control system (such as a control module dedicated to controlling photoelectric sensors and pressure sensors).

[0070] In order to realize the control of the photoelectric sensor and the pressure sensor, and thus achieve stable detection of the driver's physiological signals, the controller can be configured to: generate a control instruction for controlling the photoelectric sensor according to the pressure value signal fed back by the pressure sensor; the control instruction is used to collect the driver's physiological signals.

[0071] It can be seen from the above technical solution that the workflow of the smart steering wheel provided in the embodiment of the present application for collecting hand physiological signals is as follows:

[0072] When the vehicle system is started (or after the user sends a start command on the vehicle terminal or mobile terminal APP), the pressure sensor in the sensor module monitors the driver's hand pressure in real time and transmits the pressure value information to the controller to determine whether the driver places his hand in the designated measurement area of ​​the steering wheel. When it is detected that the driver's hand is in contact with the designated measurement area and the applied pressure value is within the predetermined pressure range, the controller will control the photoelectric sensor in the sensor module to start. The photoelectric sensor emits a light beam of a specific wavelength to illuminate the target position of the driver's hand and receives the reflected light from the driver's hand, thereby realizing the continuous collection of hand physiological signals.

[0073] For further information, see Figure 5 , the controller may include:

[0074] Intelligent control module 11; the intelligent control module 11 is configured as follows:

[0075] Obtain the pressure value signal fed back by the pressure sensor in each measuring area;

[0076] If there is a pressure value corresponding to the pressure value signal that is within a preset interval, a control instruction is generated for controlling the photoelectric sensor in the same measurement area of ​​the pressure sensor to turn on, so as to obtain the physiological signal collected by the photoelectric sensor.

[0077] In this embodiment, the pressure sensor can be configured to monitor the pressure value signal of the hand contacting the steering wheel in real time, and according to the pressure value corresponding to the pressure value signal, ensure that the acquisition operation of the photoelectric sensor is started only when a certain pressure condition (i.e., within a preset interval) is met, so as to ensure the stability and reliability of the data. Specifically, to determine whether to generate an instruction for instructing the photoelectric sensor to turn on, a preset interval can be pre-set, and the preset interval can be determined by experience or obtained by experiment; the minimum value of the preset interval can be set to a smaller pressure value, considering that the driver does not always need to hold the steering wheel to perform a turning operation. When driving the vehicle in a straight line, the pressure of the hand on the steering wheel can only be the pressure value on the steering wheel. Setting a smaller pressure value can ensure that the vehicle can also achieve the acquisition operation of the physiological signal when driving in a straight line; the maximum value of the preset interval can be set to a pressure value slightly larger than the pressure applied to the steering wheel by the driver when steering the vehicle;

[0078] In some other embodiments, the pressure sensor can be replaced by a touch sensor, that is, the acquisition operation of the photoelectric sensor can be started without pressure conditions. At this time, the intelligent control module 11 only needs to determine whether the corresponding touch sensor feedback signal is obtained.

[0079] Furthermore, in the solution of the embodiment of the present application, the pressure value signal acquisition and the physiological signal acquisition operation can be realized at multiple positions of the driver's hand at the same time. When it is necessary to judge multiple pressure values ​​and preset intervals, the intelligent control module 11 can adopt two different working modes:

[0080] Mode 1: Full area acquisition mode;

[0081] In the full-area acquisition mode, the intelligent control module 11 can first obtain the pressure value signals monitored by the pressure sensors in all measurement areas, and judge whether all the pressure value signals are within the preset range. Only when all the pressure value signals are within the preset range, a start control instruction is generated for all the photoelectric sensors to control all the photoelectric sensors to collect physiological signals.

[0082] Mode 2: Single area / specified area acquisition mode;

[0083] In the single area / specified area acquisition mode, the intelligent control module 11 can obtain the pressure value signal monitored by the pressure sensor in one or several predetermined measurement areas. When a pressure value signal is within the preset interval, a control instruction is immediately generated to start the photoelectric sensor in the measurement area. For the measurement area corresponding to the pressure value not within the preset interval, a standby mode is adopted for processing.

[0084] For the switching of the above working modes, the user can switch the mode and set the designated area by interacting with the device connected to the controller (such as the car central control, mobile terminal, etc.), and the application does not limit this. The user can set the working mode according to actual needs. For example, if the full area collection mode is selected, the comprehensiveness and accuracy of the collected data can be guaranteed. If the single area / designated area collection mode is selected, the information collection can be more flexible and the constraints on the driver can be reduced.

[0085] It should be noted that, in the present application, the setting of the working mode is not limited to the above two modes. For example, according to the different positions and numbers of the steering wheels where the measurement areas are located, a single-handed collection mode for collecting physiological signals of the driver's left and right hands, a double-handed collection mode for collecting physiological signals of both hands, etc. can be set accordingly. Accordingly, when setting the number and positions of the guide grooves 101, the measurement area of ​​a left-hand steering vehicle can be set in the left half of the steering wheel to collect the physiological signals of the user's left hand, and the measurement area of ​​a right-hand steering vehicle can be set in the right half of the steering wheel to collect the physiological signals of the user's right hand. At the same time, the measurement areas can also be set in the left half and right half of the steering wheel to collect the physiological signals of the user's hands, etc.

[0086] Furthermore, in some feasible embodiments, the controller further includes:

[0087] The data transmission module 13 is configured to send the physiological signal collected by the photoelectric sensor to the car central control, cloud platform or mobile terminal, so that the user can obtain the analysis result corresponding to the physiological signal through the car central control, cloud platform or mobile terminal. The analysis result can be used to evaluate the driver's health status or driving behavior to support functions such as safe driving and health monitoring.

[0088] In this embodiment, the data transmission module 13 can upload the information obtained by the intelligent control module 11 to the car central control 14 in real time, and display it on the car central control screen, and further realize the real-time transmission of data to the cloud platform 15 through the integrated wireless communication module. At the same time, the data transmission module 13 can also support pairing with mobile terminals 16 such as smart phones and tablet computers, so that users can view the driver's physiological data in real time through the application configured on the mobile terminal. The user here can be not only the driver himself, but also other passengers or other people who are not in the car.

[0089] Furthermore, in some feasible embodiments, the controller may further include:

[0090] The power module 12 can be designed to be connected to the internal battery system of the car, thereby providing power support for the components (sensors, controllers, etc.) in the smart steering wheel; the power module 12 can also be designed with a low power mode and a sleep function, which automatically reduces power consumption when not in operation, thereby extending the battery life of the system.

[0091] Furthermore, when the automobile central control, cloud platform or mobile terminal obtains an analysis result based on the physiological signal analysis sent by the data transmission module 13, in order to ensure the accuracy and high quality of the analysis result, the signal quality of the physiological signal can be evaluated before the data transmission module 13 sends the physiological signal, and the physiological signal whose signal quality meets the preset standard is defined as a qualified signal, and only the qualified signal is sent to the automobile central control, cloud platform or mobile terminal for analysis, and the remaining physiological signals that do not meet the requirements are eliminated; the factors used to evaluate the quality of the physiological signal may include: 1. Whether there is pulse interference; 2. Whether there is a lost segment; 3. Whether there is a motion artifact.

[0092] Therefore, in some feasible embodiments, see Figure 6 , the intelligent control module is also configured to perform the following method:

[0093] In response to the control instruction for controlling the photoelectric sensor to turn on, the physiological signal collected by the photoelectric sensor (the original signal, essentially a pulse signal) is obtained; at this time, based on the PPG signal interference detection algorithm, the quality of the PPG signal can be evaluated by using a cascaded layer-by-layer discrimination method, and then the original signal is finally divided into "usable signal (qualified signal)" and "unusable signal (unqualified signal)". The signal evaluation process can be divided into four key stages as follows:

[0094] In the signal preprocessing stage, the physiological signal is subjected to denoising; specifically, the collected physiological signal can be filtered to remove baseline drift, power frequency interference and other common noise sources. Different types of noise can be effectively filtered out through high-pass, low-pass or band-pass filters to ensure the basic quality of the signal and lay a good foundation for subsequent processing steps.

[0095] Among them, when executing the signal preprocessing stage, the pulse signal can be preprocessed by using an integer coefficient notch filter and a low-pass filter. The notch filter can filter out power frequency interference of integer multiples of 0Hz and 50Hz and baseline drift below 0.5Hz. The cutoff frequency of the low-pass filter is 66Hz, which can effectively filter out electromyographic interference.

[0096] In the pulse interference detection stage, it is detected whether the physiological signal after denoising has pulse interference; specifically, a pulse interference detection algorithm can be applied to the filtered physiological signal to identify and propose the pulse noise that may exist in the physiological signal.

[0097] Among them, in order to accurately detect high pulse and low pulse signals, the corresponding amplitude threshold and time threshold can be set to perform interference detection on the pulse signal through the following steps:

[0098] High pulse interference detection.

[0099] 1. Amplitude detection:

[0100] Set a new pulse signal sampling point as PPG(i), and assume that the previous pulse signal peak is H i-1 .

[0101] Determine whether the amplitude value of PPG(i) is greater than 1.2×H i-1 If the condition is met, proceed to the next step; if not, return to step 1 and continue to detect the next pulse signal.

[0102] Duration calculation:

[0103] Taking PPG(i) as the starting point, the calculated amplitude value is continuously greater than 1.2×H i-1 The cumulative time C t .

[0104] If C t >0.2×T (where T is the sampling period), it is determined to be a high pulse interference signal. t If the value is smaller than the threshold, the signal is considered to be a motion artifact.

[0105] Low pulse interference detection:

[0106] The detection process of low pulse interference is similar to that of high pulse interference, but when setting the amplitude threshold, the valley value of the signal is used instead of the peak value for judgment. Through similar steps, first check whether the amplitude of the low pulse signal is lower than the set threshold, and judge whether it is low pulse interference based on the signal duration.

[0107] Sensor slip compensation:

[0108] When the starting point of high pulse (or low pulse) interference is detected, it usually means that the sensor may have slipped. Therefore, when counting the pulse interference segment, additional sampling points of 0.1 cycles forward will be counted to estimate the starting point of the sensor slipping and ensure the accuracy of the interference segment statistics.

[0109] Threshold setting:

[0110] All amplitude and time thresholds are empirical values ​​obtained through statistical analysis of a large amount of data with pulse interference signals. The setting of these thresholds ensures accurate detection of pulse interference signals and can effectively distinguish high-pulse, low-pulse interference and other motion artifacts.

[0111] At this time, if pulse interference is detected, the signal segment can be marked as "unavailable", that is, an unqualified label is added to the physiological signal, and further processing of the physiological signal is terminated. If no pulse interference is detected, the next stage is entered.

[0112] In the lost segment detection phase, it is detected whether there is a lost segment in the physiological signal after the pulse interference detection; specifically, the lost segment analysis is performed on the physiological signal after the pulse interference detection. The lost segment usually manifests as a temporary loss or mutation of the signal, which may be caused by poor contact of the device or interruption of signal transmission.

[0113] Sensor dropout usually causes a noise signal, which is characterized by a constant amplitude with very small fluctuations. In contrast, the amplitude fluctuation of a normal PPG signal is significantly larger than the fluctuation of the noise signal caused by sensor dropout. However, the amplitude mean of the normal PPG signal and the mean of the noise signal caused by sensor dropout may be very close, which brings challenges to detection.

[0114] Missing segment detection based on dynamic coefficient of variation:

[0115] In statistics, the mean can effectively reflect the central tendency of a section of data, while the variance can characterize the fluctuation range of the data. In order to accurately detect the signal loss section caused by sensor shedding, the dynamic coefficient of variation can be used, which combines the characteristics of the mean and variance and can effectively distinguish normal signals from noise signals caused by sensor shedding.

[0116] Definition of dynamic coefficient of variation:

[0117] The dynamic coefficient of variation CV(t) is defined at a certain time t as the ratio of the standard deviation to the mean of the signal in a certain time window before and after that time:

[0118]

[0119] in

[0120] σ(t) is the standard deviation of the signal in the time window.

[0121] μ(t) is the mean value of the signal in the time window.

[0122] In practical applications, the dynamic coefficient of variation can be dynamically adjusted as the signal acquisition changes in real time, thereby better adapting to the volatility of the signal.

[0123] Determination of lost segments:

[0124] Sensor dropout noise: When the dynamic coefficient of variation of the signal is less than a set threshold, it indicates that the signal fluctuation is very small, which is consistent with the noise characteristics caused by sensor dropout. At this time, the system determines it as a signal loss segment.

[0125] Normal signal: When the dynamic coefficient of variation of the signal exceeds the set threshold, it means that the signal fluctuates greatly, which meets the characteristics of a normal PPG signal. Therefore, this segment of the signal is considered to be a valid signal.

[0126] By using the dynamic coefficient of variation, noise signals caused by sensor shedding can be efficiently identified and eliminated, ensuring that only valid signals with higher quality are retained for subsequent processing and analysis.

[0127] By detecting the missing segment and comparing it with the continuity of the surrounding signals, if a missing segment is found, the signal segment can be marked as "unavailable", that is, an unqualified label is added to the physiological signal, and further processing of the physiological signal is terminated. If there is no missing segment, it enters the next stage.

[0128] In the motion artifact detection stage, it is detected whether there are motion artifacts in the physiological signal after the loss segment detection; specifically, the artifacts caused by body movement or external interference are identified. Motion artifacts usually manifest as drastic changes in the amplitude of the physiological signal or abnormal fluctuations in the frequency.

[0129] Motion artifacts are PPG signals that cause feature points to be lost when the sensor slides on the human body surface due to hand movement or other reasons during driving. When disturbed by external factors (such as human movement), the PPG signal usually appears chaotic and loses its normal regularity and quasi-periodic characteristics. In contrast, the waveform of a normal PPG signal is usually more regular and exhibits quasi-periodic characteristics. By detecting the autocorrelation function, it is possible to effectively distinguish normal PPG signals from motion artifacts, eliminate motion artifact interference, and ensure the accuracy and reliability of subsequent signal processing.

[0130] Autocorrelation function definition:

[0131] For a discrete-time signal x(n), the autocorrelation function R(k) is defined as:

[0132]

[0133] Where k is the number of delay points of the signal, and N is the total length of the signal. By calculating the autocorrelation function, the similarity of the signal at different delay points can be determined.

[0134] Periodic characteristics of the autocorrelation function:

[0135] Normal pulse signal: A normal pulse signal has a clear periodicity, which makes its autocorrelation function show a large periodic peak, especially at k=0,T,2T,3T,… (where T is the period of the signal), the autocorrelation function will reach a maximum value, reflecting the quasi-periodicity of the signal.

[0136] Motion artifact signal: When the signal is disturbed by motion artifacts, the periodicity of its autocorrelation function will be significantly weakened. The fluctuation of the autocorrelation value becomes irregular, and the autocorrelation value is usually less than 0.5, showing a small peak or no obvious periodicity.

[0137] Motion Artifact Detection Methods:

[0138] By analyzing the autocorrelation function, motion artifacts can be detected based on the following criteria:

[0139] (1) Calculate the autocorrelation function: For the time-discrete PPG signal x(n), calculate its autocorrelation function R(k) and observe its change with the delay point number k.

[0140] (2) Evaluate the autocorrelation value:

[0141] For a normal pulse signal, the autocorrelation function has a large peak at the period position k=0, T, 2T, 3T, ..., and the autocorrelation value is close to 1.

[0142] For motion artifact signals, the autocorrelation value is usually small, especially at periodic positions, and the overall autocorrelation value is usually less than 0.5.

[0143] (3) Determine motion artifacts:

[0144] When the autocorrelation function of the signal shows an obvious loss of periodicity and the autocorrelation value is less than 0.5, it can be determined that the PPG signal is a motion artifact.

[0145] Through comprehensive analysis of the signal spectrum and time domain characteristics, if motion artifacts are detected, the signal segment can be marked as "unusable", that is, an unqualified label is added to the physiological signal, and further processing of the physiological signal is terminated. Only when the physiological signal passes the detection of the above stages can it be finally determined as a qualified signal (usable signal) and continue to enter the next stage of processing.

[0146] After the above-mentioned stages of detection, available or unavailable labels can be generated for the detection results of each stage based on the evaluation results. The entire signal quality evaluation process can not only accurately identify and propose low-quality signal segments, but also ensure the effective retention of high-quality signals, providing reliable signal data support for subsequent signal processing and analysis.

[0147] In addition to the above-mentioned detection of the quality of the physiological signal, before the data transmission module 13 sends the qualified signal, a step of detecting the signal duration can also be performed: the duration of the physiological signal collection is judged, and when the collection time exceeds a predetermined threshold (for example, more than 30s), the physiological signal is identified as a qualified signal and sent for subsequent data processing and analysis. Combined with the above-mentioned pressure value determination process and signal quality evaluation process, the process of collecting hand physiological signals by the smart steering wheel provided in the embodiment of the present application is as follows: Figure 7 shown.

[0148] Furthermore, when there is an unavailable signal in any of the above-mentioned detection processes, the unqualified signal and abnormal information can be recorded, and a prompt signal can be generated. Accordingly, the intelligent control module can also be configured as follows:

[0149] The measurement area information of the photoelectric sensor corresponding to the physiological signal with the unqualified label is sent to the car's central control, cloud platform or mobile terminal, and the user is prompted to troubleshoot or repair or replace the photoelectric sensor in the area.

[0150] It can be seen from the above technical solutions that the smart steering wheel provided by the present application has significant advantages over other parts (such as wrists, etc.) through the collection of physiological signals from the hands. First, the blood vessels in the hand area are densely distributed, and the quality of the collected physiological signals is also superior. Due to the high transparency of the skin on the hands, it is less affected by skin color than the wrist area, which further improves the accuracy of data collection. Secondly, the natural contact between the palm and the steering wheel can ensure stable pressure conditions, avoid the interference of changes in tightness on the measurement results when the device is worn on the wrist, and improve the stability of signal acquisition. In addition, the palm collection method does not require the device to be worn for a long time, which significantly improves the user's comfort and avoids skin discomfort caused by long-term wearing. It is particularly suitable for in-vehicle health monitoring scenarios, and realizes non-invasive and continuous physiological signal collection and health monitoring.

[0151] The smart steering wheel of this application can significantly improve the accuracy and reliability of physiological signal acquisition through the precise layout of the palm and finger measurement areas, combined with the coordinated work of photoelectric sensors and pressure sensors, and the optimized design of the guide grooves. This precise layout and design ensures stable contact between the sensor and the hand skin, and effectively reduces the impact of hand movement and external interference on signal quality, laying a solid technical foundation for subsequent health monitoring, driving safety assessment and data analysis, ensuring the accuracy and credibility of the data.

[0152] This application proposes a new physiological signal collection method, which collects the driver's hand physiological signals in real time through a photoelectric sensor device embedded in the steering wheel. The collected data can be used for subsequent data processing and analysis to generate health indicators such as blood pressure, blood oxygen saturation, heart rate, etc., or to evaluate the driver's status, thereby providing accurate and reliable support for driving safety and health monitoring. This application does not require the driver to wear any additional equipment. While ensuring privacy and security, it can continuously and stably collect physiological data and support the implementation of personalized health services. It has broad application prospects and important promotion value.

[0153] The present application also provides a hand physiological signal collection method, which is applied to the smart steering wheel described in any of the above embodiments, and the method includes:

[0154] Acquire a pressure value signal fed back by a pressure sensor in at least one measuring area of ​​the smart steering wheel;

[0155] If the pressure value corresponding to the pressure value signal is within a preset interval, obtaining a physiological signal collected by a photoelectric sensor located in the same measuring area of ​​the pressure sensor;

[0156] The physiological signal is sent to the car central control, cloud platform or mobile terminal, so that the user can obtain the analysis result corresponding to the physiological signal through the car central control, cloud platform or mobile terminal.

[0157] Further, such as Figure 8 As shown, the method also includes:

[0158] Acquire a collection mode of the smart steering wheel; the collection mode includes full-area collection and single-area collection;

[0159] If the acquisition mode is full-area acquisition, then if the pressure value corresponding to the pressure value signal is within a preset interval, the step of acquiring the physiological signal acquired by the photoelectric sensor located in the same measurement area of ​​the pressure sensor includes:

[0160] If the pressure values ​​corresponding to the pressure value signals fed back by the pressure sensors in all measuring areas are within the preset interval, the physiological sub-signals collected by all photoelectric sensors are obtained, and all the physiological sub-signals are merged into a physiological signal, or the physiological sub-signals are used as the physiological signal, that is, the physiological signal can be subsequently processed after the physiological sub-signals are merged, or each physiological sub-signal can be processed separately.

[0161] If the acquisition mode is single-area acquisition, the method includes:

[0162] Obtain the pressure value signal fed back by the pressure sensor in any measurement area of ​​the smart steering wheel.

[0163] The technical effects produced by the hand physiological signal collection method described in the above embodiment during the application process can be found in the description of the above device embodiment, which will not be repeated here.

[0164] The above specific implementation methods further illustrate the purpose, technical solutions and beneficial effects of the present application in detail. It should be understood that the above are only specific implementation methods of the present application and are not used to limit the protection scope of the present application. Any modifications, equivalent substitutions, improvements, etc. made on the basis of the technical solutions of the present application should be included in the protection scope of the present application.

Claims

1. A smart steering wheel, characterized in that: include: Steering wheel body; At least one guide groove is provided on the steering wheel body; the guide groove is used to accommodate the hand area of ​​the driver when holding the steering wheel body; At least one measuring area is arranged in the guide groove; a photoelectric sensor and a pressure sensor are embedded in the measuring area; A controller electrically connected to the photoelectric sensor and the pressure sensor; the controller is configured to: generate a control instruction for controlling the photoelectric sensor according to a pressure value signal fed back by the pressure sensor; the control instruction is used to collect physiological signals of the driver.

2. The smart steering wheel according to claim 1, characterized in that: The measurement area includes a palm measurement area and / or at least one finger measurement area.

3. The intelligent steering wheel according to claim 1, characterized in that: The guide groove is made of a flexible material.

4. The intelligent steering wheel according to claim 1, characterized in that: The controller comprises: Intelligent control module; the intelligent control module is configured as: Obtain the pressure value signal fed back by the pressure sensor in each measuring area; If there is a pressure value corresponding to the pressure value signal that is within a preset interval, a control instruction is generated for controlling the photoelectric sensor in the same measurement area of ​​the pressure sensor to turn on, so as to obtain the physiological signal collected by the photoelectric sensor.

5. The intelligent steering wheel according to claim 4, characterized in that: The controller further comprises: The data transmission module is configured to send the physiological signals collected by the photoelectric sensor to the car central control, cloud platform or mobile terminal, so that the user can obtain the analysis results corresponding to the physiological signals through the car central control, cloud platform or mobile terminal.

6. The intelligent steering wheel according to claim 5, characterized in that: The physiological signal sent by the data transmission module is a qualified signal; the intelligent control module is also configured as follows: In response to a control instruction for controlling the photoelectric sensor to turn on, acquiring a physiological signal collected by the photoelectric sensor; Performing denoising processing on the physiological signal; Detect whether there is pulse interference in the physiological signal after denoising; If not, then detecting whether there is a missing segment in the physiological signal after the pulse interference detection; If not, then the physiological signal after the missing segment detection is tested for motion artifacts; If not, the physiological signal after motion artifact detection is marked as a qualified signal.

7. The intelligent steering wheel according to claim 6, characterized in that: The intelligent control module is also configured as: If there is pulse interference in the physiological signal after denoising, and / or there is a missing segment in the physiological signal after pulse interference detection, and / or there is a motion artifact in the physiological signal after missing segment detection; Then, an unqualified label is added to the physiological signal, and the step of acquiring the physiological signal collected by the photoelectric sensor is continued.

8. The intelligent steering wheel according to claim 7, characterized in that: The intelligent control module is also configured as: The measurement area information of the photoelectric sensor corresponding to the physiological signal with the unqualified label is sent to the car central control, cloud platform or mobile terminal.

9. A method for collecting hand physiological signals, applied to the smart steering wheel according to any one of claims 1 to 8, characterized in that: The method comprises: Acquire a pressure value signal fed back by a pressure sensor in at least one measuring area of ​​the smart steering wheel; If the pressure value corresponding to the pressure value signal is within a preset interval, obtaining a physiological signal collected by a photoelectric sensor located in the same measuring area of ​​the pressure sensor; The physiological signal is sent to the car central control, cloud platform or mobile terminal, so that the user can obtain the analysis result corresponding to the physiological signal through the car central control, cloud platform or mobile terminal.

10. The method for collecting hand physiological signals according to claim 9, characterized in that: The method further comprises: Acquire a collection mode of the smart steering wheel; the collection mode includes full-area collection and single-area collection; If the acquisition mode is full-area acquisition, then if the pressure value corresponding to the pressure value signal is within a preset interval, the step of acquiring the physiological signal acquired by the photoelectric sensor located in the same measurement area of ​​the pressure sensor includes: If the pressure values ​​corresponding to the pressure value signals fed back by the pressure sensors in all the measuring areas are within the preset interval, then the physiological sub-signals collected by all the photoelectric sensors are obtained, and all the physiological sub-signals are combined into a physiological signal, or the physiological sub-signals are used as the physiological signal; If the acquisition mode is single-area acquisition, the method includes: Obtain the pressure value signal fed back by the pressure sensor in any measurement area of ​​the smart steering wheel.

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