High-speed rail intelligent sensing dynamic pressure adjusting seat

Abstract

The invention relates to a high-speed rail intelligent sensing dynamic pressure adjusting seat and method, and relates to the technical field of intelligent seats. The seat comprises a pressure sensing module, a dynamic pressure adjusting module and a control module. The pressure sensing module obtains passenger back pressure distribution data in real time through a flexible film pressure sensor matrix; the control module calculates a center track stability index and a muscle continuous activation index based on the data, and comprehensively judges the muscle fatigue state and the consciousness state of the passenger; and the dynamic pressure adjusting module executes a dynamic pressure adjusting strategy adaptive to the current state of the passenger according to the judgment result. According to the method, the waking period, the light waking period and the sleeping period of the passenger are accurately identified through double-index cross validation, and a non-inductive guarding, stretching guiding or active recovery strategy is intelligently executed, so that the travel fatigue is actively and efficiently prevented and relieved on the premise of no disturbance, and the riding comfort and the health guarantee level are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent seats and ergonomics, specifically to a high-speed rail seat with intelligent dynamic pressure adjustment. Background Technology

[0002] With the widespread use of high-speed rail, passengers are spending significantly more time sitting during their journeys. Maintaining a seated posture for extended periods, especially with poor static posture, can easily lead to stiffness in the back muscles, poor blood circulation, and consequently, deep fatigue, aches and pains, and even an increased risk of lumbar strain. This not only seriously affects passengers' travel experience and health but also negatively impacts their subsequent work and life.

[0003] To enhance comfort, various massage-equipped seats have been disclosed in existing technologies. These seats typically achieve massage modes such as tapping and kneading by integrating vibration motors or airbags into the seat cushion and backrest. However, such solutions have significant limitations: First, their operating modes are mostly pre-set fixed programs, manually triggered by the passenger or activated at set times, failing to sense the passenger's actual physiological state and exhibiting low levels of intelligence. For example, when a passenger is in deep sleep, a strong massage may disturb their rest; and when a passenger is already fatigued but does not actively seek help, the system cannot provide timely intervention. This lack of intelligent intervention results in a poor passenger experience and low energy efficiency.

[0004] To further optimize the experience, some improvement solutions attempt to introduce sensors for status awareness. For example, some solutions use pressure sensors to detect whether someone is seated to control the automatic start and stop of functions; others monitor the duration of sitting to determine whether intervention is needed. However, these methods are still relatively rudimentary. Simply relying on the presence of pressure or timing cannot accurately distinguish whether a passenger is in a distinctly different state—whether awake, asleep, or in a light, drowsy state. Different states of consciousness correspond to different causes of fatigue and intervention needs: the sleep stage requires imperceptible blood circulation maintenance; the light, drowsy state is suitable for guided stretching; while the awake stage requires active fatigue recovery. Current technology lacks the ability to recognize such subtle states, thus failing to achieve truly timely and appropriate personalized intervention.

[0005] Furthermore, at the level of perception technology, existing technologies mostly focus on macroscopic posture recognition or simple pressure distribution, failing to extract fatigue information from deeper physiological signals. For example, muscles generate specific high-frequency micro-motion signals under sustained tension, and a decline in voluntary posture control is reflected in the stability of the pressure center trajectory. The direct correlation between these key physiological indicators and fatigue states has not yet been effectively utilized in existing seating comfort systems.

[0006] Therefore, there is an urgent need for a seating system that can accurately and automatically identify passengers' consciousness and fatigue state, and intelligently select the optimal intervention strategy (including intervention timing, intervention site and intervention method) according to different states, so as to proactively and efficiently prevent and alleviate travel fatigue without disturbing passengers' rest. Summary of the Invention

[0007] This invention designs a high-speed rail seat with intelligent dynamic pressure adjustment. The technical problem it solves is that existing high-speed rail seats cannot intelligently and accurately identify passengers' real-time state of consciousness and muscle fatigue during long journeys, and thus cannot provide timely, appropriate, and personalized dynamic pressure adjustment. This leads to problems such as stiff back muscles, poor blood circulation, deep fatigue, and discomfort, affecting the travel experience and health of passengers.

[0008] To solve the aforementioned technical problems, the present invention adopts the following solution:

[0009] A high-speed rail seat with intelligent dynamic pressure adjustment includes: a pressure sensing module comprising a flexible thin-film pressure sensor matrix laid on the seat back for real-time acquisition of pressure distribution data on the passenger's back; a dynamic pressure adjustment module comprising multiple independently controllable actuators disposed in the seat back and / or seat cushion, each actuator including an airbag for generating lifting displacement and a massage motor for generating vibration; and a control module electrically connected to the pressure sensing module and the dynamic pressure adjustment module. Based on the pressure distribution data, the control module calculates the passenger's center trajectory stability index and muscle sustained activation index; based on the center trajectory stability index and muscle sustained activation index, it comprehensively judges the passenger's muscle fatigue state and consciousness state, including sleep, light wakefulness, and alertness; and based on the judgment results of the muscle fatigue state and consciousness state, it generates and executes a corresponding pressure adjustment strategy, controlling the actuators to work to dynamically change the pressure distribution between the passenger's body and the seat contact surface.

[0010] Preferably, the center trajectory stability index is obtained by: calculating the instantaneous pressure center coordinates based on each frame of pressure distribution data, and analyzing the minimum envelope rectangle area or total path length of the pressure center coordinate movement trajectory within a preset time window; wherein, the larger the minimum envelope rectangle area or path length of the trajectory, the lower the stability index; the muscle sustained activation index is obtained by: extracting high-frequency micro-motion signals from the pressure distribution data, and calculating the power spectral density of the high-frequency micro-motion signals within a preset frequency band; wherein, the higher the power spectral density value, the higher the muscle sustained activation index.

[0011] Preferably, the control module is configured to determine the state of consciousness and muscle fatigue state in the following ways: if the central trajectory stability index is higher than a first stability threshold and the muscle continuous activation index is consistently higher than the first activation threshold, it is determined to be a waking state; if the central trajectory stability index is lower than a second stability threshold and the muscle continuous activation index is consistently lower than the second activation threshold, it is determined to be a sleeping state; if the central trajectory stability index rises from a low level and the muscle continuous activation index rises rapidly from a low level with fluctuations, it is determined to be a light waking state; when it is determined to be a waking state, and the central trajectory stability index is lower than a third stability threshold, and the muscle continuous activation index is higher than the third activation threshold, and this continues for a first preset duration, it is determined that the passenger's muscles are in a fatigued state.

[0012] Preferably, when the passenger is determined to be asleep, a non-intrusive protection strategy is implemented, controlling the execution unit to operate in a random, asynchronous manner, with a lifting amplitude below a first amplitude threshold and an action frequency below a first frequency threshold; when the passenger is determined to be in a light awakening state, a guided relaxation strategy is implemented, controlling the execution unit to operate in a wave-like pressure migration mode, wherein the wave-like pressure migration mode controls the execution units arranged horizontally or vertically to lift and fall sequentially in a preset direction to form a directional mechanical pressure wave; when the passenger is determined to be awake and the muscles are determined to be fatigued, an active recovery strategy is implemented, controlling the execution unit to operate in a fixed-point cyclic decompression mode targeting high-pressure areas or an enhanced wave-like pressure migration mode; the fixed-point cyclic decompression mode identifies high-pressure areas in the pressure distribution and controls the execution unit corresponding to that high-pressure area to perform periodic lifting and falling actions.

[0013] Preferably, when the guided stretching strategy is executed, the vibration motor and airbag are controlled synchronously to generate a tactile guiding flow in the same direction as the wave-like pressure migration pattern.

[0014] Preferably, the wave-like pressure migration mode in the guided stretching strategy specifically involves controlling a row or column of execution units to rise and fall sequentially in a preset direction, forming a directional mechanical pressure wave.

[0015] Preferably, the fixed-point cyclic decompression mode in the active recovery strategy specifically involves: identifying high-pressure areas in the pressure distribution and controlling the execution unit corresponding to the high-pressure area to perform periodic lifting actions.

[0016] Preferably, the flexible thin-film pressure sensor matrix is ​​a piezoresistive sensor array, a capacitive pressure sensor array, or an optical waveguide pressure sensor array based on carbon nanotube composite materials.

[0017] A dynamic pressure adjustment method for high-speed rail seats, applied to the aforementioned intelligent dynamic pressure adjustment seats for high-speed rail, includes the following steps: acquiring pressure distribution data of the passenger's back in real time through a pressure sensor matrix; processing the data to calculate a center trajectory stability index and a muscle continuous activation index; determining the passenger's muscle fatigue state and consciousness state based on the dual indices; and, according to the determination results, driving the execution unit to execute a dynamic pressure adjustment strategy adapted to the passenger's current consciousness state to alleviate fatigue.

[0018] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described above.

[0019] The intelligent dynamic pressure adjustment seat on this high-speed train has the following beneficial effects:

[0020] (1) By integrating two deep physiological indicators, namely the stability of the center of pressure trajectory and the sustained activation of muscles, the system can accurately and automatically identify the three core states of consciousness and muscle fatigue of passengers. This makes pressure regulation no longer a simple timed or manual trigger, but a timely and appropriate personalized intervention based on the real-time physiological needs of passengers, with a high degree of intelligence.

[0021] (2) By implementing different optimization strategies under different conditions, the system can effectively promote blood circulation, relieve muscle tension, and prevent numbness and pressure sores without disturbing passengers' rest, thereby significantly improving the comfort of long-distance travel and reducing the risk of muscle strain caused by prolonged sitting.

[0022] (3) The stability of the pressure center trajectory in this invention reflects macroscopic posture control, while the sustained activation of muscles reflects the tension of local muscles through high-frequency signal analysis. The combination of the two forms a cross-validation mechanism, which can effectively distinguish between true physiological fatigue and body swaying caused by external environments such as train operation, greatly reducing the misjudgment rate and making the system decision more reliable and accurate.

[0023] (4) Based on accurate state judgment, the system can drive the execution unit to perform various dynamic pressure regulation modes such as wave-like pressure migration and fixed-point cyclic decompression. These modes can simulate physiotherapy techniques, specifically relieve high-pressure areas, and guide the body to stretch, realizing a leap from indiscriminate massage to precise adaptive regulation, resulting in better intervention effects.

[0024] (5) During passenger sleep, the system employs a low-amplitude, low-frequency, non-intrusive protection strategy to maintain basic blood circulation while maximizing energy savings and minimizing disturbance to passengers. This on-demand allocation mode, compared to traditional fixed-program seats, provides continuous health protection while achieving a higher energy efficiency ratio and a superior passenger experience. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the arrangement of a high-precision flexible pressure sensor matrix in the seat back of the high-speed rail intelligent dynamic pressure adjustment seat of the present invention.

[0026] Figure 2 This is a schematic diagram of the stability analysis of the pressure center trajectory in this invention;

[0027] Figure 3 This is a block diagram of the overall system architecture of the present invention.

[0028] Explanation of reference numerals in the attached figures:

[0029] 1—Seat backrest; 2—Flexible thin-film pressure sensor matrix. Detailed Implementation

[0030] The following is combined with Figures 1 to 3 The present invention will be further described as follows:

[0031] To enable those skilled in the art to fully understand the technical solution of the present invention, the following describes in detail the state judgment method based on the stability of the center of pressure trajectory and the continuous activation of muscles, taking a specific passenger scenario as an example.

[0032] S1. Data Acquisition and Preprocessing:

[0033] like Figure 1 As shown, in this embodiment, the seat back 1 has a built-in flexible thin-film pressure sensor matrix 2 with 16 rows x 20 columns and a sampling frequency of 10Hz. The control module continuously reads the pressure values ​​of all 320 sensing units at a rate of 10 frames per second to form a real-time pressure distribution map.

[0034] The flexible thin-film pressure sensor matrix 2 is seamlessly embedded under the seat upholstery, without affecting ride comfort. Flexible thin-film pressure sensors can be selected from Tekscan's I-Scan series, Pressure Profile Systems' TactArray sensors, or Interlink Electronics' FSR sensors.

[0035] S2, Calculation of central trajectory stability index and muscle sustained activation index:

[0036] The stability of the center of pressure trajectory refers to the body's ability to maintain postural stability in three-dimensional space. Its advantage lies in its macroscopic and holistic nature, directly reflecting the stability of the final output of the posture control system. However, its drawback is its susceptibility to interference: train cornering, acceleration, or deceleration can directly cause the center of pressure to shift, generating noise.

[0037] Muscle sustained activation measures the degree of effort a muscle exerts to maintain a current posture. Muscle tension levels are assessed by analyzing the muscular vibrations of high-frequency micro-motion signals from pressure sensors. Its advantages include strong anti-interference capabilities: the macroscopic motion frequency of a train is typically low (<1Hz), while the micro-motion frequency of muscles is higher, reaching 2-10Hz or more. High-frequency bandpass filtering effectively separates muscle signals, minimizing the influence of vehicle motion. However, its drawback is that it reflects the state of a localized muscle group beneath a specific sensor and may not represent the fatigue level of the entire back.

[0038] The combination of pressure center trajectory stability and muscle sustained activation in this invention, a cross-validation mechanism, can greatly reduce the false alarm rate and improve the detection rate of true fatigue, thus making the intelligent seat system more intelligent.

[0039] like Figure 2 As shown, the specific calculation steps are as follows:

[0040] S2.1 Calculate the stability index of the center trajectory:

[0041] Calculate the instantaneous pressure center: For each frame of data, based on the coordinates (X, Y, Z) of each sensing unit... i ,Y j ) and its pressure value P ij The pressure center coordinates (X and X) of the frame are calculated using a weighted average formula. cog Y cog ).

[0042] The calculation formula is as follows: X cog =(Σ(P ij * X i )) / ΣP ij ;Y cog =(Σ(P ij * Y j )) / ΣP ij ;

[0043] Where Σ represents the summation over all valid sensing units (a total of 16 rows x 20 columns, 320 units).

[0044] Within a 30-second observation window, the system records 300 consecutive pressure center coordinates and forms a moving trajectory on a two-dimensional plane.

[0045] The 320 sensing units represent the physical number of hardware sensors. The system operates continuously at a frequency of 10Hz, calculating the pressure at a pressure center point every 0.1 seconds, resulting in 300 pressure center points over 30 seconds. These 300 pressure center coordinate points are virtual points, representing the centroid or equilibrium point of the entire pressure distribution. A single coordinate point (X) representing the entire distribution is calculated through a weighted average. cog Y cog ).

[0046] Calculate the area of ​​the minimum envelope rectangle of the trajectory formed by these 300 points. In this embodiment, the stability index of the central trajectory = 1 / area of ​​the minimum envelope rectangle. Therefore, the larger the area, the more dispersed the trajectory, and the lower the stability index.

[0047] S2.2 Calculate the muscle sustained activation index:

[0048] Signal separation: The raw pressure signal within the same observation time window is bandpass filtered at 5-15 Hz to separate the high-frequency AC component generated by muscle tremors.

[0049] Power spectral analysis: Perform a Fast Fourier Transform on the filtered signal to calculate its average power spectral density in the 5-15Hz frequency band. This value is an indicator of muscle sustained activation. A higher value indicates more active muscle nerve activity and greater muscle tension.

[0050] S3. Specific logic and examples of state determination:

[0051] The system has preset the following judgment thresholds, which can be pre-calibrated through machine learning:

[0052] The central trajectory stability threshold includes a first stability threshold, a second stability threshold, and a third stability threshold. The muscle sustained activation threshold includes a first activation threshold, a second activation threshold, and a third activation threshold.

[0053] The first stability threshold > the third stability threshold > the second stability threshold; the first activation threshold ≥ the third activation threshold > the second activation threshold. The first stability threshold is higher than the second stability threshold, and the first activation threshold is higher than the second activation threshold. For fatigue assessment during the awake phase, the third stability threshold is lower than the first stability threshold, and the third activation threshold is close to or slightly lower than the first activation threshold. By setting thresholds with this relationship, a necessary lag interval is formed in the state assessment logic, effectively preventing misjudgments due to minor data fluctuations and ensuring the stability and accuracy of system intervention.

[0054] The first stability threshold for the center trajectory stability threshold: A stable = 0.5 mm -2Second stability threshold: A stable = 0.3 mm -2 Third stability threshold: A stable = 0.4 mm -2 .

[0055] The first activation threshold for sustained muscle activation: P active =50μV 2 / Hz, Second activation threshold: P active =30μV 2 / Hz and the third activation threshold: P active =50μV 2 / Hz.

[0056] Scenario 1: Steps to determine if someone is in a lucid state:

[0057] The trajectories are tightly clustered within a very small area (e.g., the area of ​​the minimum envelope rectangle is only 1.5 mm). -2 The calculated center trajectory stability index is 1 / 1.5 ≈ 0.67, which is higher than A. stable (0.5).

[0058] Muscle activation: Due to the passenger's concentration, the back muscles remained tense to maintain an upright posture, resulting in active high-frequency micro-motion signals. The calculated average power spectral density was 65 μV. 2 / Hz, this value is consistently higher than P active (50)

[0059] If the system determines that both the central trajectory stability index and the muscle sustained activation index are greater than the central trajectory stability threshold, it classifies the state as a state of wakefulness. If the system simultaneously detects that this state lasts too long, such as exceeding 30 minutes, it will trigger a targeted active recovery strategy.

[0060] The system first identified that the pressure was mainly concentrated in the right quadratus lumborum muscle area. Then, it controlled the airbag below this area to perform a fixed-point cyclic decompression mode: first lift it up by 1.5 cm, hold for 5 seconds, and then lower it back down and hold for 15 seconds, repeating this cycle for 3 minutes.

[0061] If the system detects that fatigue has not been effectively relieved during subsequent monitoring, and if muscle activation has not decreased, it will activate an enhanced wave-like stress migration mode. This mode features larger wave amplitudes and slower speeds, guiding the body to engage in greater range of motion.

[0062] The passenger felt his aching right lower back being rhythmically and forcefully lifted and relaxed, effectively relieving his muscle tension.

[0063] Scenario 2: Steps to determine if it is a sleep period:

[0064] Passengers' muscles are completely relaxed, and their bodies sway unconsciously with the train's movement. The center of pressure diffuses, for example, the area of ​​the minimum envelope rectangle expands to 5 mm. -2 The center trajectory stability index = 1 / 5 = 0.2, which is lower than the center trajectory stability threshold A. stable (0.3).

[0065] The overall muscle tension is reduced to a minimum, the high-frequency micro-motion signal is weak, and the average power spectral density is reduced to 20μV. 2 / Hz, this value remains below the muscle sustained activation threshold P. active (30).

[0066] If both the central trajectory stability index and the muscle sustained activation index are below the central trajectory stability threshold, the system is considered to be in a sleep state. The system will automatically switch to a non-intrusive mode, operating the airbags only with extremely gentle amplitude and frequency to avoid disturbing the passenger's sleep.

[0067] The system controls the airbag actuators within the seat back and cushion to operate. The airbag elevation is limited to less than 0.8 cm, and the activation frequency is once every 90 seconds. The first elevation threshold is 0.8 cm, and the first frequency threshold is once every 90 seconds.

[0068] Each airbag inflates and deflates gently in a random, asynchronous manner. The pressure points on the passenger's back and buttocks undergo extremely slow and minute changes, which effectively promotes local blood circulation and prevents numbness and pressure sores, but the movements are so gentle that they will not wake the passenger from sleep.

[0069] Scenario 3: Steps to determine if it is a light awakening period:

[0070] The passenger began to regain consciousness, but control was not yet fully restored, and the body made significant, unconscious adjustments. The trajectory value increased from 0.2 in the diffuse state of sleep to 0.5, becoming unstable and irregular. For example, within a 30-second window, the central trajectory stability index value fluctuated between 0.3 and 0.6.

[0071] The nervous system begins to reactivate the muscles, resulting in a sudden increase and fluctuation in electromyographic signals. The power spectral density value increases from 20 μV during sleep. 2 / Hz rapidly climbed to 55μV in a short period of time. 2 / Hz, and at 45-70μV 2 Fluctuations within the range of / Hz may be accompanied by signal spikes caused by body twitching.

[0072] If the system determines that the central trajectory stability index rises from a low level and is unstable, and the muscle sustained activation index rises rapidly from a low level and fluctuates, then it is considered a light awakening period. The system will then activate a guided stretching strategy, using gentle, wave-like pressure migration to help the traveler comfortably transition from sleep to wakefulness.

[0073] The system activates a wave-like pressure migration mode. The airbags controlling the waist inflate sequentially from the left to the right, creating a slow, mechanical wave that spans the waist for approximately 15 seconds. This wave may then repeat upwards from the lower back.

[0074] It can be configured to synchronize with a tactile flow of vibration in the same direction to enhance the guiding effect. Passengers can comfortably transition from sleep to wakefulness, avoiding the stiffness of waking up abruptly.

[0075] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the implementation of the present invention is not limited to the above-described manner. Any improvements made using the inventive concept and technical solution of the present invention, or the direct application of the inventive concept and technical solution of the present invention to other occasions without modification, are all within the protection scope of the present invention.

Claims

1. A high-speed rail seat with intelligent dynamic pressure adjustment, characterized in that, include: The pressure sensing module includes a flexible thin-film pressure sensor matrix laid on the seat back to acquire pressure distribution data on the passenger's back in real time. A dynamic pressure adjustment module includes multiple independently controllable actuators disposed within the seat back and / or seat cushion, the actuators including airbags for generating lifting displacement and / or massage motors for generating vibration; A control module is electrically connected to the pressure sensing module and the dynamic pressure regulation module. Based on the pressure distribution data, the control module calculates the passenger's center trajectory stability index and muscle sustained activation index. Based on the center trajectory stability index and muscle sustained activation index, the control module comprehensively judges the passenger's muscle fatigue state and consciousness state, including sleep, light wakefulness, and wakefulness. Based on the judgment results of the muscle fatigue state and consciousness state, the control module generates and executes a corresponding pressure regulation strategy, controlling the execution unit to work, so as to dynamically change the pressure distribution between the passenger's body and the seat contact surface.

2. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 1, characterized in that: The stability index of the center trajectory is obtained by calculating the instantaneous pressure center coordinates based on each frame of pressure distribution data, and analyzing the minimum envelope rectangle area or total path length of the pressure center coordinate movement trajectory within a preset time window; wherein, the larger the minimum envelope rectangle area or path length of the trajectory, the lower the stability index. The muscle sustained activation index is obtained by extracting a high-frequency micro-motion signal from the pressure distribution data and calculating the power spectral density of the high-frequency micro-motion signal within a preset frequency band; wherein, the higher the power spectral density value, the higher the muscle sustained activation index.

3. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 2, characterized in that: The control module is configured to determine the state of consciousness and muscle fatigue in the following ways: If the central trajectory stability index is higher than the first stability threshold and the muscle continuous activation index is higher than the first activation threshold, then it is determined to be a period of wakefulness. If the central trajectory stability index is lower than the second stability threshold and the muscle continuous activation index is lower than the second activation threshold, then it is determined to be a sleep period. If the central trajectory stability index rises from a low level and the muscle sustained activation index rises rapidly from a low level with fluctuations, it is determined to be a shallow awakening period. When the passenger is determined to be in a state of wakefulness, and the central trajectory stability index is lower than the third stability threshold, and the muscle continuous activation index is higher than the third activation threshold, and this continues for a first preset duration, then the passenger's muscles are determined to be in a state of fatigue.

4. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 3, characterized in that: When it is determined that the passenger is in a sleep period, a non-intrusive protection strategy is implemented, and the execution unit is controlled to work in a random, asynchronous manner, with a lifting amplitude below the first amplitude threshold and an action frequency below the first frequency threshold. When it is determined that the passenger is in a light awakening period, a guidance and relaxation strategy is implemented, and the execution unit is controlled to work in a wave-like pressure migration mode. The wave-like pressure migration mode is to control the execution units arranged in the horizontal or vertical direction to rise and fall in sequence according to a preset direction to form a directional mechanical pressure wave. When it is determined that the passenger is awake and the muscles are fatigued, an active recovery strategy is implemented, controlling the execution unit to operate in a fixed-point cyclic decompression mode or an enhanced wave-like pressure migration mode targeting high-pressure areas; the fixed-point cyclic decompression mode identifies high-pressure areas in the pressure distribution and controls the execution unit corresponding to that high-pressure area to perform periodic lifting and lowering actions.

5. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 4, characterized in that: When the guided stretching strategy is executed, the vibration motor and airbag are synchronously controlled to generate a tactile guiding flow in the same direction as the wave-like pressure migration pattern.

6. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 4, characterized in that: The wave-like pressure migration mode in the guided stretching strategy is as follows: control a row or column of execution units to rise and fall sequentially in a preset direction, forming a directional mechanical pressure wave.

7. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 4, characterized in that: The fixed-point cyclic decompression mode in the active recovery strategy is as follows: identify high-pressure areas in the pressure distribution and control the execution unit corresponding to the high-pressure area to perform periodic lifting actions.

8. The high-speed rail intelligent dynamic pressure adjustment seat according to claim 1, characterized in that: The flexible thin-film pressure sensor matrix is ​​a piezoresistive sensor array, a capacitive pressure sensor array, or an optical waveguide pressure sensor array based on carbon nanotube composite materials.

9. A method for dynamic pressure adjustment of high-speed rail seats, characterized in that: The method, when applied to the intelligent dynamic pressure adjustment seat of a high-speed rail as described in any one of claims 1-8, includes the following steps: Real-time pressure distribution data on the passenger's back is obtained through a pressure sensor matrix; Process the data to calculate the center trajectory stability index and the muscle sustained activation index; Based on the aforementioned dual indicators, the passenger's muscle fatigue state and consciousness state are determined. Based on the assessment results, the drive unit executes a dynamic stress regulation strategy adapted to the passenger's current state of consciousness to alleviate fatigue.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by the processor, it implements the steps of the dynamic pressure adjustment method for high-speed rail seats as described in claim 9.

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