Detection device, evaluation method and system for carsickness state, controller and vehicle

Abstract

The invention discloses a carsickness state detection device, evaluation method and system, a controller and a vehicle, and belongs to the technical field of intelligent driving. The detection device comprises a holding structure which is used for being held by a palm of a passenger; the sensor unit is arranged on the surface of the holding structure and used for collecting physiological feature data of the passenger, and the physiological feature data and the carsickness state have an incidence relation; the sensor unit is further used for transmitting the physiological feature data to the controller so that the controller can evaluate the carsickness state of the passenger. The carsickness state of the passenger is monitored and evaluated in real time, so that the riding comfort and the man-machine interaction experience of the intelligent cabin are remarkably improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent driving, and particularly relates to a motion sickness state detection device, an evaluation method and system, a controller and a vehicle. BACKGROUND

[0002] With the development of intelligent cockpits, passenger ride experience has become one of the important design considerations of vehicle-mounted systems. Motion sickness, as a typical problem affecting passenger comfort, its monitoring and intervention have gradually become a new hotspot in the research of intelligent cockpit systems. Especially in the automatic driving vehicle or long-distance travel scene, how to perceive the passenger motion sickness state in real time and actively adjust and intervene has become the focus of the vehicle manufacturer.

[0003] Related motion sickness evaluation technologies mostly use visual-based methods such as eye tracking, facial expression analysis, etc. However, the above-mentioned methods are easily disturbed by environmental light, the detection accuracy depends on the passenger behavior and head posture, it is difficult to run stably in actual complex working conditions, and the recognition process ignores individual physiological differences, which is easy to misjudge or miss. SUMMARY

[0004] The application aims to at least solve one of the technical problems in the related art. To this end, the application provides a motion sickness state detection device, an evaluation method and system, a controller and a vehicle to realize real-time monitoring and evaluation of passenger motion sickness state, and improve the ride comfort and human-computer interaction experience of the intelligent cockpit.

[0005] In a first aspect, the application provides a detection device, characterized in that it comprises: a holding structure for the passenger to hold with the palm; a sensor unit arranged on the surface of the holding structure, configured to collect physiological characteristic data of the passenger, the physiological characteristic data having a correlation with the motion sickness state; The sensor unit is further configured to transmit the physiological characteristic data to a controller, so that the controller evaluates the motion sickness state of the passenger.

[0006] According to the detection device provided by the application, the shape design conforming to human engineering facilitates the stable collection of physiological signals in the natural gripping process of the passenger, and the physiological characteristic data reflecting the physiological stress level of the passenger can be obtained at the same time, providing reliable data support for subsequent motion sickness state evaluation. In addition, the above-mentioned detection device has good human-computer adaptability and anti-interference ability, is easy to integrate into the vehicle seat armrest, has the advantages of convenient installation, high detection accuracy, strong adaptability, etc., and is suitable for popularization and application in various types of vehicles.

[0007] In a second aspect, the application provides a method for evaluating a car-sickness state, applied to a vehicle, wherein the vehicle is provided with a seat armrest structure, and a detection device with a physiological signal detection function is arranged on the seat armrest structure; the method comprises: acquiring physiological characteristic data of a passenger collected by the detection device, wherein the physiological characteristic data is correlated with the car-sickness state; determining a car-sickness state evaluation result of the passenger, wherein the evaluation basis of the car-sickness state evaluation result comprises the physiological characteristic data.

[0008] According to the method for evaluating a car-sickness state provided by the application, by arranging a detection device with a physiological signal detection function on the seat armrest structure of the vehicle, real-time collection of key physiological characteristics of a passenger is realized. The physiological characteristic data collected by the detection device can dynamically reflect the physiological stress level of the passenger. Compared with the traditional method of indirect evaluation through an external camera, the anti-interference ability is improved, the risk of interference by external conditions such as environmental light and camera recognition failure is avoided, the sensitivity and robustness of the car-sickness state evaluation are improved, and a more objective and quantifiable evaluation basis is established based on the internal physiological correlation between the physiological stress level and the car-sickness state. Then, the actual car-sickness state of the passenger is evaluated based on the physiological characteristic data, the accuracy of the car-sickness state evaluation is improved, and good integration and vehicle adaptation are achieved. The car-sickness state evaluation result can be combined with the vehicle to implement anti-car-sickness measures, thereby improving the ride comfort of the vehicle and the human-machine interaction experience of the intelligent cabin.

[0009] In a third aspect, the application provides a device for evaluating a car-sickness state, applied to a vehicle, wherein a detection device with a physiological signal detection function is arranged on the seat armrest of the vehicle; the device comprises: an acquisition module, configured to acquire physiological characteristic data of a passenger collected by the detection device, wherein the physiological characteristic data is used to reflect the physiological stress level of the passenger, and the physiological stress level is correlated with the car-sickness state; an evaluation module, configured to determine a car-sickness state evaluation result of the passenger, wherein the evaluation basis of the car-sickness state evaluation result comprises the physiological characteristic data.

[0010] According to the vehicle sickness state evaluation device provided in the application, the detection device with the physiological signal detection function is arranged on the vehicle seat armrest structure, so that the real-time collection of the key physiological characteristics of the passenger is realized. The physiological characteristic data collected by the detection device can dynamically reflect the physiological stress level of the passenger. Compared with the traditional method of indirect evaluation through an external camera, the anti-interference ability is improved, the risk of interference by external conditions such as environmental light and camera recognition failure is avoided, the sensitivity and robustness of the vehicle sickness state evaluation are improved, and a more objective and quantifiable evaluation basis is established based on the internal physiological correlation between the physiological stress level and the vehicle sickness state. Then, the actual vehicle sickness state of the passenger is evaluated based on the physiological characteristic data, the accuracy of the vehicle sickness state evaluation is improved, and the vehicle sickness state evaluation result can be combined with the vehicle to perform the anti-vehicle sickness measures, so that the ride comfort of the vehicle and the man-machine interaction experience of the intelligent cabin are improved.

[0011] In a fourth aspect, the application provides a vehicle sickness state evaluation system, characterized in that the system comprises: a seat armrest structure, wherein a detection device with a physiological signal detection function is arranged on the seat armrest structure; a controller connected with the detection device, used for executing the vehicle sickness state evaluation method according to the first aspect.

[0012] In a fifth aspect, the application provides a vehicle, which comprises the detection device according to the third aspect or the vehicle sickness state evaluation system according to the fourth aspect.

[0013] In a sixth aspect, the application provides a controller, which comprises a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the vehicle sickness state evaluation method according to the first aspect is realized.

[0014] In a seventh aspect, the application provides a non-transitory computer readable storage medium, which stores a computer program. When the computer program is executed by a processor, the vehicle sickness state evaluation method according to the first aspect is realized.

[0015] In an eighth aspect, the application provides a chip, which comprises a processor and a communication interface. The communication interface is coupled with the processor. The processor is used for running a computer program or instructions, so as to realize the vehicle sickness state evaluation method according to the first aspect.

[0016] In a ninth aspect, the application provides a computer program product, which comprises a computer program. When the computer program is executed by a processor, the vehicle sickness state evaluation method according to the first aspect is realized.

[0017] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0018] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a schematic diagram illustrating the application scenarios of the detection device provided in some embodiments of this application; Figure 2 This is a schematic diagram of the detection device provided in some embodiments of this application; Figure 3 This is a flowchart illustrating the motion sickness assessment method provided in some embodiments of this application; Figure 4 This is a schematic diagram of the overall framework of the motion sickness assessment method provided in some other embodiments of this application; Figure 5 This is a flowchart illustrating a motion sickness assessment method provided in other embodiments of this application; Figure 6 This is a schematic diagram of the motion sickness assessment device provided in some embodiments of this application; Figure 7 This is a schematic diagram of the controller provided in some embodiments of this application; Detection window 1; Electrode 2; Hemispherical shell structure 3; Display screen 4. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0020] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used in the description of this application is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms "comprising" and "having," and any variations thereof, in the description, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the description, claims, or accompanying drawings of this application are used to distinguish different objects, not to describe a specific order or hierarchy.

[0021] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0022] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," "linking," and "attachment" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0023] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0024] In this application, "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0025] In related technologies, methods for judging motion sickness based on the difference between line of sight and object vibration rely on cameras to capture the occupant's eye movements and accelerometers to detect the vibration state of the target object. These methods have several limitations: First, they are sensitive to ambient light conditions and are prone to detection failure in low light or when occupants are wearing reflective glasses. Furthermore, the vibration detection of the target object depends on a pre-installed accelerometer, making it difficult to cover items temporarily viewed by the occupant. A uniform vibration differential threshold is typically used during detection, failing to consider individual physiological differences, which can easily lead to misjudgments or missed detections. Second, this method requires high-performance hardware to simultaneously process and integrate line of sight and vibration information, resulting in a high computational load, making it unsuitable for low-cost platforms. Moreover, the overall solution lacks system integration with the vehicle, and the use of components such as LiDAR further increases the overall vehicle implementation cost, limiting its promotion and implementation in practical in-vehicle applications.

[0026] In view of this, embodiments of this application provide a detection device and supporting method for assessing motion sickness in passengers, aiming to overcome the problems of high susceptibility to environmental interference, difficulty in adapting to individual differences, high hardware costs, and poor system integration in related technologies. By integrating an optimized ergonomic detection component into the seat armrest, stable acquisition of multimodal physiological signals is achieved, and a comprehensive evaluation is performed in conjunction with the vehicle's operating status, thereby improving the accuracy, real-time performance, and vehicle adaptability of motion sickness detection.

[0027] It should be noted that the vehicles mentioned in the embodiments of this application include, but are not limited to, gasoline vehicles, plug-in hybrid electric vehicles or new energy vehicles, etc., and this application does not make specific limitations in this regard.

[0028] Figure 1 This is a schematic diagram illustrating an application scenario of the detection device provided in some embodiments of this application. The detection device is disposed in the armrest area of ​​a vehicle seat, and its overall structure includes a grip structure with a hemispherical curved surface and a sensor unit disposed on its surface. The sensor unit may include multiple sensor components. For example... Figure 1 As shown, when a passenger naturally grips the holding structure, their palm covers the surface of the device, enabling the collection of physiological characteristic data. Therefore, by integrating a physiological signal detection device into the seat armrest, employing a compact and naturally interactive ergonomic design, and combining a simple and reliable sensor structure, passenger physiological characteristic data can be stably acquired during vehicle operation, assisting in the intelligent identification and assessment of motion sickness.

[0029] The detection device provided in this application includes a gripping structure and a sensor unit.

[0030] The grip structure features a hemispherical curved surface that conforms to the shape of a human hand, guiding passengers to naturally wrap their hands around the structure during the journey to achieve stable signal acquisition.

[0031] For example, the grip structure can be a fixed hemispherical structure, or it can be designed in various ways, such as a rotatable hemispherical structure, a hidden structure, or a side-embedded nested structure, depending on the cabin layout, to adapt to the structural requirements of different vehicle models or seats.

[0032] The sensor unit is located on the surface of the grip structure and is used to collect the passenger's physiological characteristic data. The physiological characteristic data reflects the passenger's physiological stress level, which is related to motion sickness, and thus the passenger's motion sickness can be assessed.

[0033] The sensor unit can transmit physiological characteristic data to the controller, which then assesses the passenger's motion sickness based on the data. The controller can be integrated into the detection device or set up independently; for example, it can be a vehicle controller or a controller integrated into other terminals, etc.

[0034] The sensor unit includes multiple types of sensors, each type of sensor is used to detect physiological characteristic data of different physiological types, and the physiological characteristic data is used to characterize the physiological stress level of passengers.

[0035] For example, physiological characteristic data may include signals related to cardiac activity to assess sympathetic nerve activity and heart rate variability (HRV) data. Heart rate variability data includes, but is not limited to, RMSSD (Root Mean Square of Successive Differences, the root mean square of the difference between adjacent heartbeats) and LF / HF (Low Frequency / High Frequency Ratio, the ratio of low-frequency to high-frequency power, etc.).

[0036] Physiological data may also include electroskin signal data, used to reflect short-term stress responses (such as the electroskin response caused by sudden motion sickness), which belong to the body surface stress response signals. Electroskin signal data includes, but is not limited to, the skin conductance level (SCL) and conductance change characteristics such as the skin conductance response (SCR). The skin conductance level refers to the steady-state conductance value of the passenger's skin surface over a specific time period, typically used to reflect the basic activity level of the sympathetic nervous system and can serve as one of the basic physiological parameters for assessing motion sickness. The skin conductance response refers to the non-steady-state fluctuation of the passenger's skin conductance value within a short period after external stimuli or internal emotional changes, usually manifesting as a sudden increase or decrease, and can be used to reflect the instantaneous intensity of the sympathetic nervous system's response to stress events.

[0037] Physiological data may also include blood oxygen saturation or blood pressure, used to identify stress response trends in the circulatory system, which can indirectly reflect stress load over a long period. Of course, this application is not limited to the physiological types mentioned above.

[0038] In some embodiments, the sensor unit includes at least two sensor units. One sensor unit is, for example, a photoplethysmography (PPG) sensor, used to detect the passenger's heartbeat signal and extract the passenger's heart rate (HR) data and heart rate variability (HRV) data based on the signal.

[0039] Another type of sensor unit is a skin conductivity electrode, such as a GSR (Galvanic Skin Response) electrode, used to collect passengers' skin electrical signal data.

[0040] In some embodiments, the sensor unit has a detection window located on the surface of the grip structure where the palm and thumb naturally contact when the passenger's hand grips the grip structure.

[0041] In some embodiments, the sensor unit includes at least two electrodes and is spaced apart along the surface of the grip structure to form an electrical contact path with the palm when the passenger grips the grip structure.

[0042] Figure 2 This is a schematic diagram of the detection device provided in some embodiments of this application. For example, as shown... Figure 2 As shown, one sensor unit has a detection window 1 formed in a recess on the surface of the housing. The detection window 1 is arranged in the area corresponding to the pad of the thumb when the passenger's hand naturally grips the structure, to ensure a stable optical contact interface is formed during the gripping process. Another sensor unit includes at least two strip-shaped electrodes 2, which are respectively embedded at intervals along the left and right sides or the front and rear sides of the hemispherical gripping structure 3, to form a stable electrical contact path with the heel, side, or other parts of the passenger's hand when the passenger grips the device.

[0043] Through the above structural design, the detection device can collect physiological data without the need for external wearable devices, while also having good human body fit and anti-interference performance. It is suitable for real-time identification of passenger motion sickness risk while the vehicle is in operation, and provides data support for subsequent model evaluation and control linkage.

[0044] In some embodiments, the detection device further includes a display structure. The display structure is used to display physiological characteristic data, such as HR, HRV, GSR, etc., and / or motion sickness assessment results obtained based on the physiological characteristic data. This allows passengers to proactively obtain their own status and make appropriate adjustments, or it can be used in conjunction with the vehicle system.

[0045] For example, the display structure includes a display screen. (e.g.) Figure 2 As shown, the display screen is located in the front area of ​​the hemispherical detection device, making it easy for passengers to view relevant data while holding the device, thus enhancing the interactive experience.

[0046] It should be noted that the installation position of the display screen is not limited to the illustrated structure. As a variant, the display screen can also be set at other positions of the seat armrest, such as the area near the elbow on the top surface of the armrest, the side of the armrest, the embedded folding panel, or integrated into the secondary display screen system on the back of the seat. The specific layout method can be flexibly adjusted according to the space layout of the vehicle cockpit, interaction habits, and visual visibility requirements, with strong structural compatibility and adaptability.

[0047] In some embodiments, the detection device can be installed at the front end, top surface, side surface, or bottom surface of the vehicle seat armrest. The specific installation position can be flexibly selected according to the vehicle model structure to ensure that passengers can easily and naturally contact it during the ride without affecting the riding experience.

[0048] In some embodiments, the detection device can be integrated into the rear armrest of the vehicle. When a rear passenger grasps the detection device, the detection device can collect the physiological characteristic data of the rear passenger in the vehicle to detect the motion sickness situation of the rear passenger.

[0049] To achieve the linkage control with the whole vehicle, the detection device is electrically connected to a preset data interface module in the seat armrest through an internal cable. The data interface can adopt forms such as CAN bus (Controller Area Network), LIN bus (Local Interconnect Network), UART (Universal Asynchronous Receiver / Transmitter), or USB-C interface, etc., for transmitting the collected physiological characteristic data to the central controller or cockpit domain controller of the vehicle for processing.

[0050] Based on the above structural design and signal acquisition ability of the detection device, the present application further provides a motion sickness detection method, which combines the physiological characteristic data of passengers obtained by the detection device with the vehicle operation information to dynamically evaluate the motion sickness state of passengers. Through a reasonable signal processing process and evaluation model, it is possible to achieve real-time identification and intervention control of motion sickness risks, and improve the comfort and active response ability of the in-vehicle intelligent cockpit. The specific steps of this method are as follows.

[0051] The motion sickness state evaluation method provided by the embodiments of the present application, the execution subject of this motion sickness state evaluation method can be a controller or a functional module or functional entity in the controller that can implement this motion sickness state evaluation method. This method is adapted to a vehicle environment equipped with a physiological signal detection device on the seat armrest, and is used to dynamically monitor and intelligently evaluate the motion sickness state of passengers during the vehicle operation.

[0052] For example, the controller may be an Electronic Control Unit (ECU), a Central Control Unit (CCU), a Cockpit Domain Controller (CDC), an Intelligent Seat Controller (ISC), a Body Control Module (BCM), or other in-vehicle electronic control units with signal processing capabilities.

[0053] The following uses the controller as the execution subject as an example to illustrate the motion sickness assessment method provided in the embodiments of this application.

[0054] Figure 3 This is a flowchart illustrating the motion sickness assessment method provided in some embodiments of this application.

[0055] like Figure 3 As shown, this method is applied to a vehicle, and the vehicle's seat armrest structure is equipped with a detection device with physiological signal detection function. This detection device is the detection device described in any of the foregoing embodiments or combinations thereof. The method includes: steps 310 to 320.

[0056] Step 310: Obtain the physiological characteristic data of the passenger collected by the detection device; the physiological characteristic data is related to motion sickness.

[0057] The controller can detect motion sickness detection trigger operations, such as a passenger pressing the start detection button, the driver issuing a detection start command, or the vehicle automatically starting detection after a delay after starting.

[0058] After the detection process is initiated, the controller responds to the trigger operation by acquiring the passenger's physiological characteristic data collected by the seat armrest detection device. This physiological characteristic data reflects the passenger's physiological stress level. The physiological characteristic data and / or physiological stress level are correlated with motion sickness.

[0059] For example, the physiological characteristic data may include signals related to cardiac activity to assess sympathetic nerve activity and heart rate variability indices. The physiological characteristic data may also include skin conductance or skin temperature to reflect short-term stress responses (such as skin conductance caused by sudden motion sickness) or temperature regulation, which are surface stress response signals. The physiological characteristic data may also include blood oxygen saturation or blood pressure to identify stress response trends in the circulatory system, indirectly reflecting stress load over a long period. Of course, this application is not limited to the physiological types exemplified above.

[0060] In an optional implementation, the controller receives skin conductance signal data, heart rate data, and heart rate variability data transmitted by the detection device via a CAN bus upon detection initiation. The skin conductance signal data includes, but is not limited to, SCL and SCR, and can be acquired using skin conductance electrodes such as GSR electrodes mounted on the detection device. The heart rate data and heart rate variability data can be extracted from heartbeat signals acquired by a PPG sensor mounted on the detection device.

[0061] Step 320: Determine the assessment result of the passenger's motion sickness status, wherein the assessment basis for the motion sickness status assessment result includes the physiological characteristic data.

[0062] The controller assesses the passenger's motion sickness based on the collected physiological characteristic data and obtains the motion sickness assessment result.

[0063] In some embodiments, the controller can directly compare physiological characteristic data with preset thresholds to determine whether a passenger is experiencing motion sickness. For example, if heart rate variability exceeds a certain threshold, the passenger is determined to be experiencing motion sickness.

[0064] In some embodiments, the controller uses the aforementioned physiological characteristic data as evaluation input to input into a motion sickness assessment model that is deployed locally or invoked remotely, and comprehensively judges the current motion sickness status of the passenger based on the input HRV abnormality, skin conductance intensity and motion conditions, and outputs the corresponding motion sickness assessment result.

[0065] Single-type physiological signals (such as heart rate or skin conductance) may be affected by environmental interference, individual differences, or unforeseen factors, leading to instability and incompleteness in motion sickness identification. Therefore, in some embodiments, the assessment result of a passenger's motion sickness is determined based on physiological feature data, including: fusing physiological feature data to obtain multimodal features; and inputting the multimodal features into a preset motion sickness assessment model for inference to obtain the passenger's motion sickness assessment result. Thus, by fusing multiple physiological feature data to construct a unified multimodal input feature, the robustness and accuracy of the judgment are improved.

[0066] The controller performs feature fusion on physiological characteristic data from different physiological types. Feature fusion methods include, but are not limited to, concatenation, normalization, or embedding mapping, combining the data into a unified vector representation to form a unified multimodal feature vector. Subsequently, the controller inputs the multimodal feature vector into a pre-set motion sickness assessment model for inference processing. This model can employ pre-trained neural networks, support vector machines (SVM), decision trees, or other algorithmic structures. Based on the input physiological response pattern, the model outputs the passenger's motion sickness assessment result.

[0067] The assessment results can be presented as discrete levels (e.g., "no motion sickness / mild / moderate / severe") or continuous scores (e.g., a motion sickness risk score of 0–100). For example, motion sickness assessment results can be represented by motion sickness levels or motion sickness level scores. Motion sickness levels can be graded as: no motion sickness, mild, moderate, severe; or, level 1, level 2, level 3, level 4, etc. Motion sickness level scores can be represented by quantitative scores, for example, 0–100.

[0068] It should be noted that the deployment method of the motion sickness assessment model is not limited to a specific form. In some embodiments, the model can be deployed locally in the vehicle's controller to achieve edge computing and real-time judgment during vehicle operation, which has advantages such as fast response speed and closed-loop data processing.

[0069] In other embodiments, the model can also be deployed as a cloud service. The controller can upload the collected physiological characteristic data and vehicle motion information to a remote server via wireless communication. The cloud performs the evaluation calculation and returns the evaluation results to the vehicle to execute the corresponding control strategy. Whether to use local deployment or cloud access can be flexibly selected based on the vehicle architecture, computing power allocation strategy, and network communication conditions, exhibiting good scalability and adaptability.

[0070] According to the motion sickness assessment method provided in this application, a detection device with physiological signal detection function is installed in the armrest structure of the vehicle seat to realize the real-time collection of key physiological characteristics of passengers. The physiological characteristic data collected by the detection device can dynamically reflect the physiological stress level of passengers. Compared with the traditional indirect assessment method through external cameras, it improves the anti-interference ability and avoids the risk of interference from external conditions such as ambient light and camera recognition failure. It also improves the sensitivity and robustness of motion sickness assessment and establishes a more objective and quantifiable assessment basis based on the inherent physiological correlation between physiological stress level and motion sickness. Furthermore, it assesses the actual motion sickness state of passengers based on physiological characteristic data, improves the accuracy of motion sickness assessment, and has good integration and vehicle adaptability. It can combine the motion sickness assessment results to link the vehicle to implement anti-motion sickness measures, improve the overall vehicle ride comfort and the human-computer interaction experience of the smart cockpit.

[0071] Furthermore, based on the above method, passengers do not need to wear additional equipment, and it can adapt to the physiological differences of different individuals, exhibiting good real-time performance, anti-interference capability, and individual adaptability. The overall hardware cost is low, and it is easy to integrate into the vehicle, facilitating its application in passenger cars, tour buses, or autonomous vehicles, effectively improving passenger comfort and active protection experience during the journey.

[0072] In in-vehicle scenarios, whether passengers correctly grip the seat armrest structure directly affects the effectiveness of physiological signal detection. If passengers do not have sufficient contact with the detection device, especially if they do not cover the PPG detection window or the electrodermal electrode, complete or effective data such as heart rate and electrodermal activity cannot be collected, leading to the inability to conduct subsequent motion sickness assessments or the output of incorrect results. Existing technologies often neglect contact confirmation before detection and lack awareness of passenger interaction status, affecting the stability and automation of the assessment process. Therefore, this embodiment introduces a grip detection and guidance mechanism to proactively confirm whether the passenger is in an effective gripping state before physiological signal collection, improving the overall system's interactivity and data integrity.

[0073] Therefore, in some embodiments, before triggering the motion sickness detection, the method further includes: detecting whether the passenger is holding the seat armrest structure; if the passenger is not holding the seat armrest structure, outputting a holding prompt message; the holding prompt message is used to guide the passenger to hold the seat armrest structure; and if the passenger is holding the seat armrest structure, triggering the motion sickness detection operation.

[0074] The controller uses the sensor unit of the detection device to determine in real time whether the passenger is holding the seat armrest structure. This determination can be achieved through one of the following methods: The PPG sensor detects the presence of periodic light reflection signals caused by blood flow; Electrodermal electrode assays are used to detect whether a stable electrical conduction pathway has been formed. Alternatively, combine signals from multiple sensors to confirm the skin contact status.

[0075] When the controller detects that a passenger is not holding the armrest structure, or that the holding state has not formed an effective detection loop, the controller controls the display screen on the armrest to output holding prompts, such as "Please cover the armrest sensing area with your palm" or graphic guidance animations, to guide the passenger to hold the seat armrest structure correctly.

[0076] When it is detected that the passenger has gripped the seat armrest structure and at least one type of physiological signal has begun to be effectively collected (such as the appearance of a valid PPG waveform), the subsequent motion sickness detection process is automatically triggered, including steps such as physiological signal collection, motion information collection, calibration processing and evaluation inference.

[0077] Therefore, by setting up a grip detection and prompting mechanism, the system can proactively identify whether data collection conditions are met before motion sickness detection, avoiding data gaps and misjudgments caused by accidental triggering. Outputting grip prompts through the armrest display screen or other interactive modules helps guide passengers to quickly establish the correct contact posture, improving user experience and system adaptability. At the same time, this approach also helps improve the robustness and accuracy of subsequent assessments, making it particularly suitable for rear-seat children, the elderly, or users unfamiliar with in-vehicle health systems.

[0078] After obtaining the motion sickness assessment results, the controller can determine whether the preset triggering conditions for motion sickness measures are met. For example, if the condition level is "moderate" or above, or if three consecutive assessment cycles are all "mild," then the anti-motion sickness measures will be automatically triggered.

[0079] In some embodiments, the controller automatically triggers motion sickness prevention measures based on the motion sickness assessment results.

[0080] That is, after outputting the motion sickness assessment results, the controller further executes intervention decisions. If it detects that the passenger's motion sickness level is higher than the preset level threshold, or the motion sickness level score is higher than the preset score threshold, or high-risk physiological reactions are identified (such as a sudden increase in heart rate, significant fluctuations in skin conductance, etc.), the controller can automatically trigger one or more anti-motion sickness measures.

[0081] Among them, motion sickness prevention measures include at least one of the following: controlling the ventilation of windows and / or seats in the vehicle; controlling the speakers to play music; controlling the fragrance release mechanism to release fragrance; adjusting the interior lighting of the vehicle; implementing motion sickness warning; adjusting the vehicle speed and / or route planning.

[0082] Specifically, the controller can control the raising and lowering of windows or the activation of seat ventilation to enhance airflow.

[0083] The controller can control the vehicle's speakers to play soothing background music. It can also control the fragrance module to release anti-motion sickness scents such as mint or lemon. The controller can adjust the cabin lighting brightness or color temperature to create a stable visual environment. Finally, the controller can send "motion sickness warning" messages to passengers to help them adjust their seating position.

[0084] Furthermore, if the vehicle possesses driving strategy control capabilities, the controller can also intervene in active driving behavior by reducing vehicle speed and optimizing the route, such as updating the route to avoid high-frequency curves. This strategy boasts extremely high practical flexibility, scalability, and potential for enhancing passenger experience, making it particularly suitable for high-end intelligent cockpits or autonomous driving scenarios.

[0085] In the above embodiments, by introducing a multi-dimensional, multi-modal anti-motion sickness mechanism, automated intervention can be achieved to alleviate motion sickness in passengers at an early stage, preventing it from developing into severe discomfort. Compared with traditional fixed thresholds or manual operation modes, this is more proactive, personalized, and precise, improving the comfort of the travel experience.

[0086] In some embodiments, based on the motion sickness assessment results, motion sickness prevention measures are automatically triggered, including at least one of the following: when the motion sickness level is higher than a level threshold, the vehicle is automatically triggered to execute preset motion sickness prevention measures; when the motion sickness level score is higher than a score threshold, the vehicle is automatically triggered to execute preset motion sickness prevention measures; or, based on the target motion sickness level range hit by the motion sickness level, one or more target motion sickness prevention measures that match the target motion sickness level range are determined, and the vehicle is controlled to execute one or more target motion sickness prevention measures.

[0087] The controller supports multi-level intervention strategies. If the motion sickness level exceeds the level threshold, a preset combination of motion sickness prevention measures will be triggered immediately; if the motion sickness level score exceeds the score threshold, a preset combination of motion sickness prevention measures will be triggered immediately; or, multiple motion sickness level ranges (such as mild, moderate, and severe) can be preset, with each range bound to a corresponding combination of motion sickness prevention measures.

[0088] After obtaining the current motion sickness level score, the controller determines which level range the score falls into. For example, the score can be divided into the following level ranges: A score of 0-40 indicates "no motion sickness" and monitoring should continue. A score of 41-65 indicates "mild motion sickness," and passengers may be advised to rest or have the ventilation slightly improved. A score of 66-85 indicates "moderate motion sickness," and the system will automatically activate seat ventilation, fragrance, and play soothing music. A score of 86-100 indicates "severe motion sickness." In addition to implementing all motion sickness prevention measures, passengers can be advised to close their eyes and rest. If necessary, the vehicle can be slowed down or the route optimized.

[0089] Alternatively, for mild cases: turn on seat ventilation and play background music; for moderate cases: simultaneously activate fragrance spray and adjust headlights; for severe cases: combine adjusting vehicle speed and route replanning.

[0090] Based on the target level range identified by the score, the controller queries a preset mapping table to determine a set of matching anti-motion sickness measures and controls the vehicle to execute these measures. For example, when the controller detects a score of 74, which falls within the "moderate motion sickness" level range, it will automatically trigger various relief measures, such as turning on ventilation, playing soft music, controlling the fragrance system to release a refreshing aroma, and displaying a message on the armrest display screen: "Moderate motion sickness reaction detected, anti-motion sickness plan being implemented."

[0091] Therefore, by introducing an automatic triggering mechanism for motion sickness prevention measures and a graded motion sickness prevention intervention strategy, it is possible to intervene in advance before passengers have obvious subjective feedback on their physiological state. It has a high level of early warning and automation, and improves the initiative of the overall comfort experience and the intelligence of the system response. It is particularly suitable for long-distance driving, rear-seat passengers, or scenarios where passengers are unable to actively report motion sickness.

[0092] In some scenarios, passengers may wish to proactively monitor their motion sickness or intervene in triggering mechanisms. Therefore, in some embodiments, the method further includes: displaying physiological characteristic data and / or motion sickness assessment results to the passenger via a display structure; and manually triggering anti-motion sickness measures in response to the passenger's operation on the display screen.

[0093] The display structure can show passengers real-time heart rate, HRV, electrodermatology (EDS) curves, current motion sickness rating and risk level, recommended motion sickness prevention options, and more. Passengers can choose whether to enable the motion sickness prevention function, such as by clicking a button on the display screen, confirming with gestures, or using voice commands.

[0094] The controller can continuously monitor passenger actions, including but not limited to screen taps, swipes, long presses, or voice commands. When a passenger actively selects an anti-motion sickness function, such as "activate ventilation" or "spray fragrance," the controller responds immediately and executes the corresponding measures.

[0095] Therefore, on the one hand, a display structure is introduced to provide a human-computer interaction interface, enhance detection transparency, and improve the user interaction experience; on the other hand, manual triggering capability is provided to adapt to individual subjective feelings, and a dual-channel control architecture of automatic and manual is constructed to enhance the flexibility of motion sickness measures and user participation.

[0096] To avoid the influence of vehicle movement on the assessment of motion sickness, embodiments of this application can further calibrate the collected physiological characteristic data. Therefore, in some embodiments, the method further includes: collecting vehicle motion information; using the motion information to calibrate the physiological characteristic data to obtain calibrated physiological characteristic data. Accordingly, the assessment basis for the motion sickness assessment result also includes the vehicle motion information.

[0097] The controller simultaneously collects the vehicle's current motion information. This motion information includes at least parameters such as the vehicle's real-time speed, acceleration, and yaw rate, which can be obtained through an acceleration sensor, the vehicle's ECU, or an inertial navigation module.

[0098] Since dynamic changes such as vehicle acceleration / deceleration and turning can interfere with electrodermal signals, the controller uses this motion information to dynamically calibrate the original physiological characteristic data, including but not limited to: removing data samples during periods of high interference and adjusting the baseline level of electrodermal signals, thereby obtaining more stable calibrated physiological characteristic data that conforms to the physiological response trend.

[0099] For example, the controller is based on whether the vehicle's lateral acceleration exceeds a preset threshold (e.g., ±2). Determine if there is strong driving interference; if so, remove or weight attenuate the skin conductance signal in the corresponding time period, and perform baseline normalization on the remaining signal segment to obtain calibrated skin-related signals.

[0100] In the above embodiments, by introducing vehicle motion information as a calibration factor, noise interference caused by vehicle acceleration, bumps and other operating conditions on physiological characteristics can be identified and eliminated, and physiological characteristic data can be calibrated to generate stable and reliable calibrated physiological characteristic data, thereby further improving the accuracy of motion sickness assessment results.

[0101] During actual vehicle operation, the contact state between passengers' hands and seat armrests is easily affected by factors such as bumps, acceleration, and steering, leading to non-physiological abrupt changes or fluctuations in the electrodermal signal (GSR). This interference not only masks the true physiological stress response but may also cause misjudgments in motion sickness assessment models. Therefore, it is necessary to dynamically identify interference periods by incorporating vehicle motion information, and to screen and baseline-calibrate the GSR to enhance its physiological indicative significance and modeling stability.

[0102] Therefore, in some embodiments, the above method further includes: removing skin signal data belonging to abnormal time periods from the skin signal data to obtain calibrated skin signal data.

[0103] The abnormal period is the period in which the acceleration in the motion information exceeds the acceleration threshold or the angular velocity exceeds the angular velocity threshold.

[0104] For example, longitudinal acceleration greater than ±1.0 When one or more of the following conditions are met, such as a steering angular velocity greater than ±10° / s or vibration intensity exceeding a certain threshold, the controller determines that the period is an abnormal period with strong interference.

[0105] Subsequently, the controller removes the sampling points in the EDS signal that correspond to the EDS signal data during the abnormal period, and obtains the calibrated EDS signal data, which is the remaining part used for subsequent analysis.

[0106] By calibrating the electrodermal signal data, the true trend of changes in the passenger's autonomic nervous system can be reflected, serving as a reliable input feature for motion sickness inference and ensuring stable operation and judgment accuracy in complex in-vehicle scenarios.

[0107] In some embodiments, calibrating the physiological characteristic data includes: after removing the skin electrodermal signal data belonging to abnormal time periods, redetermining the baseline level of the skin electrodermal signal data, such as the mean of the skin electrodermal signal data, and performing normalization processing on the target skin electrodermal signal data based on the baseline level to obtain calibrated skin electrodermal signal data.

[0108] The controller can also calibrate its baseline level based on the moving average trend, local extreme value changes, or resting interval mean of the electrodermal signal data. For example, the baseline value can be set as the mean of a stable segment over the past 60 seconds, or fitted to a first-order smooth curve to offset the effects of environmental fluctuations. The resulting calibrated electrodermal signal data can reflect the true trend of changes in the passenger's autonomic nervous system, serving as a reliable input feature for inferring motion sickness.

[0109] By combining dynamic calibration of the baseline level, the model can effectively address the differences in basic electrical conductance among different passengers, improve the generalization performance and robustness of motion sickness assessment models across different population groups and environmental conditions, and thus ensure stable operation and judgment accuracy in complex vehicle scenarios.

[0110] As a result, the subsequent signal discrimination is more in line with the passenger's physiological state, significantly improving the anti-interference ability, evaluation stability and adaptability in actual road scenarios, and is particularly suitable for complex scenarios such as highways and mountain roads.

[0111] Of course, in addition to calibrating electrodermal signal data, similar interference removal and baseline adjustment can be performed on other types of physiological signals to further improve the overall quality and discrimination efficiency of multimodal physiological data. For example, for heart rate variability data, segments with poor signal quality can be removed by superimposing the period of intense vehicle movement with the PPG signal waveform quality score, thus avoiding interference from PPG waveform distortion caused by vehicle vibration on the accuracy of heart rate interval calculation.

[0112] For example, the temperature of the hand's skin acquired by the temperature sensor can be compensated for during the transition period when a passenger first grasps the detection device or when the vehicle's air conditioning is first turned on. This multi-dimensional calibration mechanism is not only applicable to a single signal channel, but also provides a stable and consistent data foundation for subsequent multi-modal fusion.

[0113] Heart rate and heart rate variability (HRV) are important physiological indicators reflecting the activity level of the human autonomic nervous system. Especially during motion sickness, an imbalance between the sympathetic and parasympathetic systems can cause an increase in heart rate and a decrease in HRV. Compared to subjective inquiries or behavioral manifestations alone, HR and HRV provide a more objective, physiological-level basis for judgment. Therefore, to accurately assess a passenger's motion sickness status, it is necessary to extract these features from the collected raw heartbeat signals. To this end, in some embodiments, the above method further includes: acquiring the passenger's heartbeat signal collected by a detection device; and extracting features from the heartbeat signal to obtain heart rate data and heart rate variability data.

[0114] The controller acquires the passenger's heartbeat signal through a PPG sensor or ECG electrode installed in the seat armrest detection device. The heartbeat signal refers to the raw time series data that reflects the periodic characteristics of the heartbeat, usually manifested as a PPG waveform or R peak sequence.

[0115] The controller performs feature extraction processing on the heartbeat signal, which mainly includes identifying the heartbeat cycle or RR interval (i.e., the time interval between two adjacent heartbeats), calculating the number of heartbeats per unit time, obtaining heart rate data, and further extracting heart rate variability data based on multiple adjacent heartbeat cycles.

[0116] The controller uses the aforementioned heart rate data and heart rate variability data as part of the physiological characteristic data for subsequent motion sickness assessment.

[0117] Therefore, by integrating heart rate acquisition and feature extraction functions into the detection device, it is possible to obtain HR and HRV indicators that are closely related to the state of the passenger's autonomic nervous system regulation. In particular, when fused with multimodal signals such as skin conductance signals and vehicle motion information, it can enhance the sensitivity of perception of mild or early motion sickness and improve the accuracy and timeliness of motion sickness assessment.

[0118] In practical applications, while a comprehensive analysis of passengers' physiological signals using a motion sickness assessment model can produce relatively objective evaluation results, in certain emergency or specific scenarios, to improve response efficiency, anti-motion sickness measures can sometimes be directly triggered based on abnormal changes in the passenger's physiological characteristic data to achieve rapid intervention. For example, when heart rate rises sharply, heart rate variability decreases significantly, or skin conductance signals show abrupt changes, it often indicates that the passenger is in a high stress state, which may be significantly associated with the risk of motion sickness. Therefore, in some embodiments, preset abnormal conditions for physiological characteristic data can be set. When these conditions are met, the controller can trigger the anti-motion sickness mechanism without relying on the motion sickness assessment model, achieving a more flexible control method.

[0119] In some embodiments, after the controller acquires the physiological characteristic data of passengers collected by the detection device, it can set corresponding thresholds for key physiological indicators (such as heart rate, heart rate variability, and electrodermal signal). For example, if the heart rate exceeds the corresponding threshold, such as 100 bpm, or the RMSSD in heart rate variability (HRV) is lower than the corresponding threshold, such as 15 ms, or the conductance mutation value of electrodermal response (SCR) in electrodermal signal is greater than the corresponding threshold, such as 0.05 μS and the rate of change is higher than a set threshold, then it is considered to meet the preset abnormal conditions.

[0120] Once the controller determines that an anomaly has occurred, it can skip the motion sickness model inference and directly control the vehicle to implement corresponding anti-motion sickness measures, such as turning on seat ventilation, playing soothing music, releasing anti-motion sickness fragrance, or issuing reminders to improve riding comfort and reduce the risk of motion sickness.

[0121] By introducing a direct judgment mechanism based on abnormal changes in physiological characteristics, rapid intervention can be made to assess passenger motion sickness risk without the need for model evaluation. This is particularly suitable for situations where the model fails to output assessment results in a timely manner or where a sudden, strong stress response is detected. This mechanism, as a supplementary approach to the motion sickness assessment scheme in this application, not only improves the system's response efficiency and flexibility but also enhances the overall adaptability and robustness of the system. When used in conjunction with the detection device and signal calibration mechanism of this application, it can provide faster motion sickness prevention services while ensuring accuracy, thus optimizing the user experience.

[0122] The motion sickness assessment method provided in this application will be explained below in specific scenarios.

[0123] Figure 4 This is a schematic diagram of the motion sickness assessment process provided in some embodiments of this application. For example... Figure 4 As shown, Figure 4 As shown, this method is executed by the controller and mainly includes the following steps: First, the controller acquires vehicle operation information from vehicle motion sensors, including dynamic data such as acceleration, speed, and attitude angles. Simultaneously, the controller also receives passenger physiological signal data from a multimodal physiological data acquisition system. This physiological signal data includes photoplethysmography (PPG) signals acquired by a PPG sensor and skin conductance signals acquired by a skin conductance activity sensor.

[0124] The controller can perform preliminary processing on the received physiological signals, including but not limited to: ADC (Analog-to-Digital Converter) conversion: Converting analog signals into digital signals that can be processed; Adaptive differential amplification: enhances and suppresses noise in the signal, improving feature quality; Environmental noise filtering: Eliminates environmental noise components such as light interference, power supply interference, or vibration noise.

[0125] For example, for photoplethysmography (PPG) signals, the controller performs analog-to-digital conversion, signal gain adjustment, and noise filtering to enhance the stability and resolution of the heart rate signal. For electrodermal (EDS) signals, the controller simultaneously performs PPG and background interference suppression to extract skin conductance characteristics.

[0126] Based on the processed signal, the controller extracts heart rate-related time-domain and frequency-domain features, including heart rate and heart rate variability parameters such as RMSSD, SDNN, and LF / HF ratio. Simultaneously, the controller identifies the heartbeat cycle in the PPG waveform to support subsequent assessment of motion sickness severity. The controller also extracts baseline and nonlinear characteristics of skin conductance from the electrodermal signal, such as the number of skin conductance spikes, rise rate, and maximum conductance.

[0127] After extracting physiological features, the controller combines the previously acquired vehicle operation information to determine whether there is a significant dynamic disturbance. When the vehicle acceleration or speed exceeds a preset threshold, the controller removes the skin conductance signal data collected during that period and updates the skin conductance baseline based on the motion state during that period to complete the dynamic calibration of the skin conductance signal.

[0128] Subsequently, the controller integrates heart rate, heart rate variability, calibrated skin conductance characteristics, and vehicle motion information as input features, which are then fed into the motion sickness assessment model (i.e., the motion sickness level mapping model in the figure) for analysis. The assessment model is pre-trained and can output the passenger's current motion sickness level in the form of a quantitative score or a level classification. Based on the model's output, the controller generates comprehensive physiological parameters including heart rate, HRV index, skin conductance characteristics, and motion sickness level score, and determines whether the triggering intervention conditions are met. By employing the fusion analysis of three multimodal signals—skin conductance, heart rate, and heart rate variability—and combining them with vehicle motion information, motion sickness symptoms can be detected more accurately and promptly, thereby activating the vehicle's anti-motion sickness mode in advance and providing a more comfortable travel experience. When the motion sickness score exceeds the set threshold, the controller will execute one or more preset anti-motion sickness measures, including but not limited to controlling the seat ventilation system, activating the aroma release device, playing soothing music, adjusting the cabin lighting, or prompting passengers to close their eyes and rest.

[0129] In conclusion, Figure 4 This application demonstrates the complete motion sickness assessment process executed by the controller, from signal acquisition, processing, feature extraction, dynamic interference correction to state assessment and linkage control. It has the technical advantages of strong real-time performance, good anti-interference ability, and intelligent response, and is suitable for active comfort management in various intelligent cockpit environments.

[0130] To more clearly illustrate the execution process of the motion sickness assessment method provided in this application, Figure 5 This is a flowchart illustrating the logic processing of motion sickness detection and assessment in some embodiments of this application. For example... Figure 5As shown, this method is executed by the controller and combines data collected by sensors to complete the entire process from detection initialization to motion sickness level assessment and result output, including the following steps: First, the controller initiates the detection process and acquires signals from the PPG sensor. The PPG sensor is mounted on the hemispherical structure of the seat armrest and is used to acquire photoplethysmography (PPG) signals from the passenger's fingertips.

[0131] The controller determines whether a periodic heartbeat signal exists in the current PPG signal, that is, whether a continuous and valid PPG waveform can be identified within a certain time window. This determination is used to confirm that the passenger has correctly gripped the hemispherical detection structure, ensuring stable contact between the sensor and the finger.

[0132] If no periodic signal is detected, the controller will output a prompt to guide the passenger to complete the hand fixation operation, such as re-gripping the handrail and adjusting the palm contact angle so that the thumb covers the PPG detection area, until a valid signal is collected.

[0133] If a periodic signal is detected, the controller acquires waveform data from the PPG sensor and simultaneously acquires signals from the electrodermal sensor. Electrodermal signals reflect the level of sympathetic nerve activity in passengers and are used to identify their stress state.

[0134] The controller simultaneously acquires motion signal information of the vehicle, such as acceleration or steering angular velocity, for baseline calibration of subsequent electrodermal signals and to determine the degree of disturbance in the current riding environment.

[0135] After acquiring the above three types of signals, the controller performs comprehensive data processing, extracts characteristic indicators such as heart rate, heart rate variability, and skin conductance level changes, and performs data fusion in combination with the vehicle's motion status.

[0136] Subsequently, the controller uses the extracted physiological characteristic data and vehicle motion information to call the motion sickness assessment model to comprehensively analyze the passenger's current state and output the corresponding motion sickness level score or level classification result.

[0137] Finally, the controller displays the evaluation results to the passenger on the screen, allowing the passenger to understand their own status in real time and choose whether to manually activate anti-motion sickness measures based on the prompts, or wait for the system to automatically implement the linkage control strategy.

[0138] By introducing processes such as initial grip validity judgment, signal acquisition verification, state score calculation and result output, the system ensures that motion sickness recognition tasks are completed under the premise of guaranteed signal acquisition quality. It has the advantages of clear process, rigorous judgment and instant feedback, and is suitable for the human-computer interaction needs of intelligent cockpits in various car travel scenarios.

[0139] Furthermore, this application's embodiments are based on two types of simple and easily integrated sensors (such as PPG sensors and electrodermal sensors), and fully utilize existing vehicle hardware resources, such as seat armrest displays and accelerometers, to effectively identify passenger motion sickness without significantly increasing system hardware complexity and cost. The overall hardware configuration of this solution is simple, cost-effective, and possesses good signal acquisition stability and evaluation accuracy. It is applicable to various vehicle models and cabin structures, demonstrating strong engineering feasibility and application scalability.

[0140] Based on the same inventive concept, this application also provides a motion sickness assessment device for use in a controller.

[0141] The motion sickness assessment method provided in this application can be executed by a motion sickness assessment device. This application uses a motion sickness assessment device to perform the motion sickness assessment method as an example to illustrate the motion sickness assessment device provided in this application.

[0142] Figure 6 This is a schematic diagram of the motion sickness assessment device provided in some embodiments of this application. For example... Figure 6 As shown, the motion sickness assessment device includes an acquisition module 601 and an assessment module 602. Wherein: The acquisition module 601 is used to acquire the physiological characteristic data of passengers collected by the detection device; the physiological characteristic data is used to reflect the physiological stress level of passengers, and the physiological stress level is related to motion sickness.

[0143] Assessment module 602 is used to determine the assessment results of a passenger's motion sickness status based on physiological characteristic data.

[0144] According to the motion sickness assessment device provided in this application, by installing a detection device with physiological signal detection function in the vehicle seat armrest structure, real-time acquisition of key physiological characteristics of passengers is realized. The physiological characteristic data collected by the detection device can dynamically reflect the physiological stress level of passengers. Compared with the traditional indirect assessment method through external cameras, it improves the anti-interference ability, avoids the risk of interference from external conditions such as ambient light and camera recognition failure, and improves the sensitivity and robustness of motion sickness assessment. Based on the inherent physiological correlation between physiological stress level and motion sickness, a more objective and quantifiable assessment basis is established. Furthermore, the actual motion sickness state of passengers is assessed based on physiological characteristic data, improving the accuracy of motion sickness assessment. It also has good integration and vehicle adaptability, and can combine the motion sickness assessment results to link the vehicle to implement anti-motion sickness measures, improving the overall vehicle ride comfort and the human-computer interaction experience of the smart cockpit.

[0145] In some embodiments, the above-described device further includes a calibration module for collecting vehicle motion information; calibrating the physiological characteristic data based on the motion information to obtain calibrated physiological characteristic data, which is then used to determine the passenger's motion sickness assessment result.

[0146] In some embodiments, the physiological characteristic data includes at least electrodermal signal data; the calibration module determines the corresponding time period as the target time period when the acceleration in the motion information exceeds an acceleration threshold or the angular velocity exceeds an angular velocity threshold; in the electrodermal signal data, the electrodermal signal data belonging to the target time period is removed to obtain the target electrodermal signal data within the non-target time period; the mean of the target electrodermal signal data is used as the baseline level, and the target electrodermal signal data is normalized based on the baseline level to obtain the calibrated electrodermal signal data.

[0147] In some embodiments, the assessment module is further configured to input physiological characteristic data into a preset motion sickness assessment model for inference, thereby obtaining the motion sickness assessment result of the passenger.

[0148] In some embodiments, the device further includes a triggering module for detecting whether a passenger is holding the seat armrest structure; outputting a holding prompt message when the passenger is not holding the seat armrest structure; the holding prompt message is used to guide the passenger to hold the seat armrest structure; and triggering a motion sickness detection operation when the passenger is holding the seat armrest structure.

[0149] In some embodiments, the above-described device further includes an execution module for automatically triggering anti-motion sickness measures based on motion sickness assessment results; wherein the anti-motion sickness measures include at least one of the following: controlling the ventilation of windows and / or seats in the vehicle; controlling the speakers to play music; controlling the fragrance mechanism to release fragrance; adjusting the lighting inside the vehicle; executing a motion sickness warning; adjusting the vehicle speed and / or route planning.

[0150] In some embodiments, the motion sickness assessment result is represented by a motion sickness level score; the execution module is also used to automatically trigger the vehicle to perform preset motion sickness prevention measures when the motion sickness level score is higher than the score threshold; or, based on the target motion sickness level range hit by the motion sickness level score, determine one or more target motion sickness prevention measures that match the target motion sickness level range, and control the vehicle to perform one or more target motion sickness prevention measures.

[0151] In some embodiments, the device further includes an interaction module for displaying physiological characteristic data and / or motion sickness assessment results to passengers through a display structure; and for manually triggering anti-motion sickness measures in response to a passenger's triggering operation on the display structure.

[0152] The motion sickness assessment device provided in this application embodiment can realize the various processes implemented in the various method embodiments, and will not be described again here to avoid repetition.

[0153] The motion sickness assessment device in this application embodiment can also be an on-board computing device or its components, such as a domain controller, electronic control unit (ECU), integrated circuit, or functional chip module. This device can be deployed in the vehicle's air conditioning control system, smart cockpit control system, central gateway, central computing platform, or other on-board electronic architecture with computing capabilities. For example, the motion sickness assessment device can be a body domain controller, air conditioning controller (HVAC control unit), smart cockpit domain controller, central processing platform, or its embedded processor and memory module. This application does not limit the specific type and deployment structure of the controller; as long as it has data acquisition, logic operation, and control output capabilities, it can be applied to the motion sickness assessment method of this application.

[0154] Figure 7 This is a schematic diagram of the controller provided in some embodiments of this application. In some embodiments, such as Figure 7 As shown, this application embodiment also provides a controller 700, including a processor 701, a memory 702, and a computer program stored in the memory 702 and executable on the processor 701. When the program is executed by the processor 701, it implements the various processes of the above-described method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here.

[0155] Based on the same inventive concept, this application also provides a motion sickness assessment system, which includes a seat armrest structure and a controller installed on a vehicle seat, and the seat armrest structure is provided with a detection device with physiological signal detection function.

[0156] The detection device includes a hemispherical gripping structure for acquiring passenger physiological data. The gripping structure is equipped with a PPG sensor and skin conductance detection electrodes to collect heart rate-related signals and skin conductance signals, respectively. A data interface is also provided on the seat armrest for transmitting the collected physiological signals to the controller. The interface can be wired (e.g., CAN bus, LIN bus, or UART serial port) or wireless (e.g., BLE, Wi-Fi).

[0157] The controller may be an electronic control unit of the vehicle, such as a central controller or a cabin domain controller, and is communicatively connected to the detection device to perform the motion sickness assessment method described in any of the above embodiments or combinations thereof.

[0158] After receiving physiological characteristic data and vehicle motion information, the controller identifies the passenger's motion sickness state based on a preset evaluation model, and, when conditions are met, links the vehicle to implement anti-motion sickness control strategies, such as seat ventilation, fragrance release, and music playback, to improve riding comfort.

[0159] The motion sickness assessment system provided in this application makes full use of the existing cabin structure for integration, with a clear signal path. It is suitable for mass-produced passenger vehicles, autonomous driving cabins, or high-end comfort platforms, and has the advantages of strong structural feasibility, complete logical closed loop, and good scalability.

[0160] This application also provides a vehicle that includes the motion sickness assessment device described in any of the above embodiments, or the vehicle includes the motion sickness assessment system described in the above embodiments.

[0161] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described motion sickness assessment method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0162] The processor is the processor in the computer device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0163] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described motion sickness assessment method.

[0164] The processor is the processor in the computer device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0165] This application also provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled. The processor is used to run programs or instructions to implement the various processes of the above-described motion sickness assessment method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0166] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0167] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0168] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the related technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0169] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0170] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0171] Unless otherwise specified, all embodiments and optional embodiments of this application can be combined to form new technical solutions.

[0172] Unless otherwise specified, all technical features and optional technical features of this application may be combined to form new technical solutions.

[0173] Unless otherwise specified, all steps in this application may be performed sequentially or randomly, preferably sequentially. For example, if the method includes steps (a) and (b), it means that the method may include steps (a) and (b) performed sequentially, or it may include steps (b) and (a) performed sequentially. For example, if the method may also include step (c), it means that step (c) may be added to the method in any order. For example, the method may include steps (a), (b), and (c), or it may include steps (a), (c), and (b), or it may include steps (c), (a), and (b), etc.

[0174] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A detection device, characterized in that, include: The grip structure is designed for passengers to hold with their palms; A sensor unit, disposed on the surface of the grip structure, is used to collect physiological characteristic data of passengers, and the physiological characteristic data is related to motion sickness. The sensor unit is also used to transmit the physiological characteristic data to the controller so that the controller can assess the passenger's motion sickness.

2. The detection device according to claim 1, characterized in that, The gripping structure has a hemispherical curved surface and includes at least one of the following: a fixed hemispherical structure, a rotatable hemispherical structure, a hidden hemispherical structure, or a side-hidden embedded structure.

3. The detection device according to claim 1, characterized in that, The sensor unit includes multiple types of sensors, each type of sensor being used to detect physiological characteristic data of different physiological types.

4. The detection device according to claim 1 or 3, characterized in that, The physiological characteristic data includes at least heart rate data, heart rate variability data, and skin conductance data.

5. The detection device according to claim 3, characterized in that, The sensor unit includes: a first sensor for collecting the passenger's heartbeat signal and extracting features from the heartbeat signal to obtain heart rate data and heart rate variability data; and a second sensor for collecting the passenger's skin conductance signal data.

6. The detection device according to claim 1, characterized in that, The sensor unit has a detection window located on the surface of the grip structure where the palm and thumb naturally contact when the passenger's hand grips the grip structure. And / or, The sensor unit includes at least two electrodes, which are spaced apart and embedded along the surface of the grip structure to form an electrical contact path with the palm when the passenger grips the grip structure.

7. The detection device according to claim 1, characterized in that, The detection device further includes a display structure; the display structure is used to display physiological characteristic data and / or motion sickness assessment results; the motion sickness assessment results are obtained based on the physiological characteristic data to assess motion sickness.

8. A method for assessing motion sickness, characterized in that, Applied to a vehicle, the vehicle is equipped with a seat armrest structure, and the seat armrest structure is equipped with a detection device having a physiological signal detection function; the method includes: Acquire physiological characteristic data of passengers collected by a detection device; the physiological characteristic data is correlated with motion sickness. The assessment results of the passenger's motion sickness status are determined, and the assessment basis for the motion sickness status assessment results includes the physiological characteristic data.

9. The method according to claim 8, characterized in that, The assessment of motion sickness also includes information about the vehicle's movement.

10. The method according to claim 8, characterized in that, The vehicle's motion information is used to calibrate the physiological characteristic data to obtain calibrated physiological characteristic data, and the calibrated physiological characteristic data is used to evaluate the motion sickness assessment result.

11. The method according to claim 10, characterized in that, The physiological characteristic data includes at least skin electrical signal data; the method further includes: In the electrodermal signal data, the electrodermal signal data belonging to abnormal periods are removed to obtain calibrated electrodermal signal data. The abnormal periods are the periods in the motion information where the acceleration exceeds the acceleration threshold or the angular velocity exceeds the angular velocity threshold.

12. The method according to claim 8, characterized in that, The assessment results for determining the passenger's motion sickness include: The physiological characteristic data is input into a preset motion sickness assessment model to obtain the motion sickness assessment results of the passenger.

13. The method according to claim 8, characterized in that, The method further includes: If the passenger is not holding the seat armrest, a holding prompt message is output; the holding prompt message is used to guide the passenger to hold the seat armrest.

14. The method according to claim 8, characterized in that, The method further includes: Based on the motion sickness assessment results, motion sickness prevention measures are automatically triggered; wherein, the motion sickness prevention measures include at least one of the following: Control the ventilation of windows and / or seats inside the vehicle; Control the speaker to play music; Control the release of fragrance by the fragrance mechanism; Adjust the vehicle interior lighting; Implement motion sickness warning; Adjust vehicle speed and / or route planning.

15. The method according to claim 14, characterized in that, The automatically triggered motion sickness prevention measures also include: When at least one of the physiological characteristic data meets the preset abnormality judgment condition, the motion sickness prevention measure is triggered; The physiological characteristic data includes skin conductance signal data, heart rate data and / or heart rate variability data. The abnormality determination conditions include, but are not limited to: rapid changes in skin conductance signal, heart rate exceeding a preset upper limit threshold, or heart rate variability falling below a preset lower limit threshold.

16. The method according to claim 8, characterized in that, The method further includes: The display structure presents passengers with physiological data and / or motion sickness assessment results. In response to a passenger's triggering action on the display structure, anti-motion sickness measures are manually activated.

17. A motion sickness assessment system, characterized in that, include: A seat armrest structure, wherein a detection device with physiological signal detection function is provided on the seat armrest structure; A controller, connected to the detection device, is used to perform the motion sickness assessment method as described in any one of claims 8-16.

18. A vehicle, characterized in that, The vehicle includes the detection device as described in any one of claims 1-7, or the motion sickness assessment system as described in claim 17.

19. A controller, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the motion sickness assessment method as described in any one of claims 8-16.

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