AI control interaction system of massage chair

Abstract

The invention provides an AI control interaction system of a massage chair, and relates to the technical field of intelligent control and man-machine interaction, and the system comprises a strategy generation and scheduling execution module which is used for generating a candidate control strategy based on an updated user portrait and the current state of the massage chair, according to the AI control interaction system of the massage chair, candidate control strategies are obtained, a target control strategy is determined from the candidate control strategies according to a preset scheduling rule, a control instruction for a massage chair execution mechanism is output to drive the massage chair to work, and the AI control interaction system of the massage chair generates scheduling through user portrait learning and strategy generation. Working parameters of the massage chair are dynamically adjusted according to preferences and physiological features of each user, pressure contact signals, pose displacement signals and user interaction are collected in real time, personalized optimization is performed according to the set portrait updating rule, and it is ensured that the user obtains massage experience meeting requirements and safety threshold values.

Description

Technical Field

[0001] This invention relates to the field of intelligent control and human-computer interaction technology, specifically to an AI control and interaction system for a massage chair. Background Technology

[0002] Existing massage chairs typically include a main control board, drive module, and actuators such as massage mechanisms, airbags, heating elements, and leg extension devices. Mode selection and parameter settings are achieved through a hand controller, panel, or mobile device. Some products incorporate voice interaction, APP integration, or simple body shape and posture detection to adjust parameters such as intensity, speed, and position based on preset programs. Overall control often employs a program control scheme with fixed procedures or limited parameter configurations.

[0003] However, existing solutions generally suffer from the following problems: comfort and safety are difficult to balance, multi-user preference learning and profile solidification are insufficient, and frequent manual adjustments are still required for repeated use. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an AI control and interaction system for massage chairs. The technical problem this invention aims to solve is how to address the issues of difficulty in balancing comfort and safety, insufficient preference fixation, and frequent manual adjustments through methods such as signal acquisition, user profile learning, strategy generation and scheduling execution, and safety constraint correction.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an AI control and interaction system for a massage chair, comprising:

[0006] Signal acquisition and interaction module: used to acquire pressure contact signals, posture displacement signals and operating status signals of the massage chair, and receive user interaction commands;

[0007] User identification and profile learning module: used to identify different users and build corresponding user profiles. The user profile includes the user's preference parameter set and safety threshold set. The user profile is updated according to a preset profile update rule. The profile update rule includes: when a user's manual adjustment of massage parameters is detected or the execution feedback represented by the pressure contact signal and posture displacement signal is detected to meet the update trigger condition, the preference parameter set is incrementally updated and the safety threshold set is updated synchronously.

[0008] Strategy generation and scheduling execution module: It is used to generate candidate control strategies based on the updated user profile and the current state of the massage chair, and determine the target control strategy from the candidate control strategies according to the preset scheduling rules, and output control commands to the massage chair actuator to drive the massage chair to work.

[0009] Safety constraint and closed-loop correction module: used to perform constraint verification on the control command based on the safety threshold set and the pressure contact signal, posture displacement signal and running status signal before and during the execution of the target control strategy. When it is detected that the control parameters in the control command violate the constraint conditions of the safety threshold set, the control command is corrected online, including limiting the control parameters to a safe range, switching to a conservative strategy or triggering a safety shutdown.

[0010] Preferably, the pressure contact signal is acquired by a pressure sensor array disposed on the seat cushion and / or backrest, the posture displacement signal is acquired by a backrest angle sensor and / or leg support displacement sensor, and the operating status signal includes the current signal of the massage motor, the temperature signal of the heating unit, and the air pressure signal of the airbag circuit.

[0011] Preferably, the signal acquisition and interaction module includes a panel hand controller and a mobile terminal or voice interface, and adds source identifiers to the instructions of different interaction interfaces so that the scheduling rules can determine the source priority.

[0012] Preferably, the user identification and profile learning module performs user identification based on mobile terminal account login information or voiceprint features, and binds the user identification result as a unique user identifier so as to automatically call the corresponding user profile each time it is started.

[0013] Preferably, the user profile uses structured data storage, the set of preference parameters includes the target massage area, intensity level, rhythm parameters and single session duration, and the set of safety thresholds includes the upper limit of the massage mechanism pressure or the upper limit of the motor current, the upper limit of the airbag pressure, the upper limit of the heating temperature, and the identification of prohibited areas.

[0014] Preferably, the profile update rule includes: when performing incremental updates on the preference parameter set, weighted fusion of historical preferences and current session preferences is performed, with the weight of current session preferences in the fusion being a preset learning rate; and when updating the security threshold set, a non-increment principle is adopted, wherein the updated security threshold is not higher than the original security threshold.

[0015] Preferably, the update triggering conditions include: the number of times the user manually adjusts the same massage parameter in a single session reaches a preset number threshold; the pressure distribution deviation represented by the pressure contact signal continuously reaches a preset deviation threshold and continuously reaches a preset duration threshold; and the change in the chair back angle or leg rest displacement represented by the posture displacement signal reaches a preset change threshold and continuously reaches a preset duration threshold.

[0016] Preferably, the candidate control strategy includes linkage control parameters for the massage mechanism drive mechanism and the airbag inflation / deflation mechanism. The strategy generation and scheduling execution module calculates comfort indexes based on pressure contact signals and / or user manual adjustment actions, and uses the comfort indexes as the basis for determining the target control strategy. The comfort indexes include pressure distribution uniformity, contact loss rate, and manual adjustment frequency per unit time.

[0017] Preferably, the scheduling rules include: emergency stop commands have the highest priority, followed by commands from the panel controller, and finally commands from the mobile terminal or voice. When commands from different sources are executed concurrently and the control parameters conflict with each other, the high-priority command overrides the low-priority command, and the overridden command is executed with a delay.

[0018] Preferably, the constraint verification includes at least upper limit constraint verification of airbag target pressure, mechanism pressing force or motor current, heating target temperature, and the travel range of the seat back or leg rest. When it is detected that the control parameter in the control command will trigger any upper limit constraint, the online correction performs amplitude limiting processing and / or strategy replacement processing. The conservative strategy includes reducing the strength and speed of the mechanism, reducing the airbag target pressure and performing depressurization, turning off or reducing the heating, and adjusting the seat back and leg rest to a preset safe posture. When the state of violating the set of safety thresholds continues to reach a preset duration threshold, the safety shutdown is triggered and an event record containing the triggering cause and triggering signal value is generated.

[0019] This invention provides an AI control and interaction system for a massage chair. It has the following beneficial effects:

[0020] The massage chair's AI control and interaction system, through user profile learning and strategy generation scheduling, dynamically adjusts the massage chair's working parameters according to each user's preferences and physiological characteristics. It collects pressure contact signals, posture displacement signals, and user interactions in real time, and performs personalized optimization according to the set profile update rules to ensure that users receive a massage experience that meets their needs and safety thresholds.

[0021] The system employs a safety constraint and closed-loop correction module, which provides real-time monitoring and correction of control commands, ensuring that the massage chair operates within a safe range. When any potential over-limit or abnormal situation is detected, the system automatically corrects or triggers a safety shutdown, preventing potential safety hazards and ensuring user safety. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the system structure of the present invention;

[0023] Figure 2 This is a flowchart illustrating the user identification and profiling process of the present invention.

[0024] Figure 3 This is a flowchart illustrating the strategy generation and priority scheduling process of this invention.

[0025] Figure 4 This is a flowchart of the security constraint verification process of the present invention;

[0026] Figure 5 This is a flowchart of the user profile update process for this invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Example 1

[0029] like Figure 1-5 As shown, this embodiment of the invention provides an AI control and interaction system for a massage chair, comprising:

[0030] Signal Acquisition and Interaction Module: This module collects pressure contact signals, posture displacement signals, and operating status signals from the massage chair, and receives user interaction commands. Pressure contact signals are collected by a pressure sensor array located on the seat cushion and / or backrest; posture displacement signals are collected by a backrest angle sensor and / or leg rest displacement sensor; and operating status signals include the current signal of the massage motor, the temperature signal of the heating unit, and the air pressure signal of the airbag circuit. The signal acquisition and interaction module includes a panel controller and a mobile terminal or voice interface, and adds source identifiers to commands from different interaction interfaces for source priority determination by the scheduling rules.

[0031] The user identification and profile learning module is used to identify different users and build corresponding user profiles. Each user profile includes a set of preference parameters and a set of safety thresholds. The module updates the user profile according to preset profile update rules, including incremental updates to the preference parameter set and simultaneous updates to the safety threshold set when a user's manual adjustment of massage parameters or when the execution feedback represented by pressure contact signals and posture displacement signals meets the update trigger conditions. The module identifies users based on mobile terminal account login information or voiceprint features and binds the identification result to a unique user identifier, automatically retrieving the corresponding user profile upon each startup. User profiles use structured data storage. The preference parameter set includes the target massage area, intensity level, rhythm parameters, and single session duration. The safety threshold set includes the upper limit of the massage mechanism pressure or motor current, the upper limit of the airbag pressure, the upper limit of the heating temperature, and prohibited area markers. The profile update rules include: when performing incremental updates to the preference parameter set, historical preferences and current session preferences are weighted and fused, with the weight of the current session preference in the fusion being a preset learning rate; and when updating the safety threshold set, a non-increment principle is adopted, meaning the updated safety threshold is not higher than the original safety threshold. Update trigger conditions include: the number of times a user manually adjusts the same massage parameter in a single session reaches a preset number threshold; the pressure distribution deviation represented by the pressure contact signal continuously reaches a preset deviation threshold and a preset duration threshold; and the change in chair back angle or leg rest displacement represented by the posture displacement signal reaches a preset change threshold and a preset duration threshold.

[0032] The strategy generation and scheduling execution module generates candidate control strategies based on the updated user profile and the current state of the massage chair. It then determines the target control strategy from these candidate strategies according to preset scheduling rules, outputting control commands to the massage chair's actuators to drive its operation. Candidate control strategies include the linkage control parameters for the massage mechanism's drive mechanism and the airbag inflation / deflation mechanism. The module calculates comfort indices based on pressure contact signals and / or user manual adjustments, using these indices as the basis for determining the target control strategy. Comfort indices include pressure distribution uniformity, contact loss rate, and the frequency of manual adjustments per unit time. Scheduling rules prioritize emergency stop commands, followed by panel controller commands, and finally mobile terminal or voice commands. When commands from different sources are concurrent and their control parameters conflict, higher-priority commands override lower-priority commands, and the overridden commands are executed with a delay.

[0033] The safety constraint and closed-loop correction module is used to perform constraint verification on control commands based on a set of safety thresholds, pressure contact signals, posture displacement signals, and operating status signals before and during the execution of the target control strategy. When a control parameter in the control command is detected to violate the constraints of the safety threshold set, the control command is corrected online, including limiting the control parameter to a safe range, switching to a conservative strategy, or triggering a safety shutdown. The constraint verification includes at least upper limit constraint verification on the airbag target pressure, the mechanism pressing force or motor current, the heating target temperature, and the travel range of the seat back or leg rest. When a control parameter in the control command is detected to trigger any upper limit constraint, the module performs amplitude limiting processing and / or strategy replacement processing through online correction. Conservative strategies include reducing the mechanism strength and speed, reducing the airbag target pressure and performing depressurization, turning off or reducing the heating, and adjusting the seat back and leg rest to a preset safe posture. When the state of violating the safety threshold set continues to reach a preset duration threshold, a safety shutdown is triggered and an event record containing the trigger cause and trigger signal value is generated.

[0034] The personalized experience is enhanced through a user profile learning module and incremental update technology, ensuring automatic adjustments based on user needs each time it's used. A safety constraint and closed-loop correction module ensures the massage chair's safety during operation, mitigating potential risks through real-time verification and online correction. Multiple interaction methods and priority scheduling enhance responsiveness, while the introduction of comfort indicators ensures the accuracy and stability of the massage effect, further improving the overall user experience.

[0035] Example 2

[0036] This embodiment demonstrates an AI-based control and interaction system for massage chairs, showcasing how user profiles can be dynamically updated using user interaction data and feedback signals to achieve a personalized and precise massage experience. The specific implementation method is as follows:

[0037] 1. User identification

[0038] Identity verification process:

[0039] Users log in to the system using their mobile terminal accounts. After authentication, they are assigned a unique identifier, ID A12345.

[0040] The registration voiceprint feature system based on user A further confirms the user's identity using voiceprint recognition technology and binds it to user A's profile.

[0041] 2. Load user profile

[0042] Preference parameter set:

[0043] Target massage areas:

[0044] The data comes from the system's records of the user's past 50 massage sessions, and statistics show that user A's preferred massage areas are:

[0045] Back: User A's massages mainly focused on the back, supported by data showing that back massages accounted for 65% of the total massages in historical data.

[0046] Lower back: Historical data shows that user A chooses a lower back massage about once out of every five massages, with lower back massages accounting for 20% of the total number of massages.

[0047] Legs: Of the remaining 15%, user A sometimes chooses leg massage.

[0048] Intensity level:

[0049] Based on user A's records of manually adjusting massage intensity over the past 30 times, user A's massage intensity preference is level 6. The data comes from system logs, which summarize the intensity parameters adjusted by the user each time.

[0050] Average intensity adjustment record: In 30 massages, users adjusted the intensity to level 6 in 20 of them.

[0051] Rhythm parameters:

[0052] Based on the rhythm parameters selected by the user in the past 20 times, User A's rhythm preference is medium rhythm, i.e., level 5. Data shows that the user prefers level 5 rhythm 80% of the time.

[0053] Single session duration:

[0054] The system interaction log records that the preferred massage duration is 30 minutes each time. Historical data shows that user A has selected a duration of 30 minutes in the past 15 sessions.

[0055] Set of safety thresholds:

[0056] Maximum pressure of the massage mechanism: Based on the hardware specifications of the massage chair, to ensure that it will not cause harm to the user under maximum pressure, the maximum pressure is 100N.

[0057] Motor current limit: According to the motor safety parameters provided by the hardware manufacturer, the current limit is 3A.

[0058] Airbag pressure limit: According to the design specifications of the airbag control system, the upper limit is 200Pa.

[0059] Upper limit of heating temperature: The safe upper limit of the heating system is 40℃, and the data comes from the heating module manufacturer.

[0060] Forbidden areas are marked: Based on the user's preferences in the system, the neck and knees are marked as forbidden areas in user A's profile.

[0061] 3. Portrait Update Process

[0062] Based on user A's real-time interaction data and feedback signals, the system triggered an incremental update of the profile. The specific update steps and data basis are as follows:

[0063] Incremental update of preference parameters:

[0064] In this session, User A manually adjusted the massage intensity from level 6 to level 8. The data, based on the adjustment log in the system interaction record, details each intensity adjustment made by the user.

[0065] Intensity Update: The system performs a weighted fusion of historical intensity level 6 and the current adjustment intensity level 8.

[0066] The purpose of weighted fusion is to combine historical preference data with feedback from the current session to form new preference parameters, thereby achieving personalized and dynamic adjustments. The formula is:

[0067] .

[0068] in, For users' historical preference parameters, Feedback for this session, This is the weighted learning rate.

[0069] Learning rate setting: Based on the frequency of changes in user behavior and the system's responsiveness to personalized adjustments.

[0070] A weighted learning rate of 0.5 was set by analyzing the frequency of user preference changes and the sensitivity to immediate feedback. This aims to balance the weights of historical preferences and current needs, enabling the system to quickly adapt to users' immediate needs while maintaining the stability of long-term preferences.

[0071] The historical intensity was level 6, and this adjustment is level 8, using a learning rate weighting of 0.5:

[0072] .

[0073] The calculated new preference intensity is level 7.

[0074] Back pressure update: Based on data from the pressure contact sensor, User A's back pressure preference has been adjusted from 60N to 65N.

[0075] Historical data shows that user A had set the back massage pressure to 65N 5 times in the previous 50 sessions, and during this session, the system detected user A's need for stronger back pressure.

[0076] Pace and duration not updated: Pace remains at medium, level 5, duration is 30 minutes.

[0077] In User A's past 30 conversations, 90% of the conversations maintained a 5-level pace and a duration of 30 minutes.

[0078] The safety threshold has not changed:

[0079] Safety thresholds for mechanism pressure, airbag pressure, and motor current remained unchanged. System logs show that User A did not trigger any safety threshold alarms during this session, and all control parameters were within safe limits.

[0080] 4. Data support and user interaction

[0081] Real-time signal acquisition:

[0082] Pressure contact signal: Pressure sensors from the seat cushion and backrest monitor user A's massage feedback in real time. Data shows that user A's back pressure requirement increased from 60N to 65N.

[0083] Posture displacement signals: Data from the backrest angle sensor and leg rest sensor show changes in user A's posture, and the system adjusts the massage chair angle in real time to adapt.

[0084] User manually adjusts records:

[0085] The system records the massage intensity and area manually adjusted by user A each time through interaction logs, and applies the data to profile updates to ensure that each massage meets the user's real-time needs.

[0086] 5. User Experience and System Response

[0087] Massage process:

[0088] User A started a 30-minute massage. The system adjusted the massage intensity and pressure areas based on real-time signals and user input. User A adjusted the intensity to level 8 and requested increased back pressure during the massage. The system responded in real time and adjusted the back pressure to 65N.

[0089] Treatment of contraindicated areas:

[0090] Throughout the process, the system strictly avoids massage operations on the neck and knees based on the data on prohibited areas recorded in the user profile, ensuring that the system always meets user A's safety requirements.

[0091] Through the above steps, the system can weightedly integrate users' historical preferences and immediate needs, updating user profiles in real time to ensure accurate matching of personalized needs. In practice, the system dynamically updates relevant parameters based on user interactions, optimizing the comfort and safety of the massage experience. The system employs strict measures regarding handling contraindicated areas and monitoring safety thresholds, ensuring user safety and providing a flexible and efficient intelligent massage control solution.

[0092] Example 3

[0093] This embodiment is an AI control and interaction system based on a massage chair. It combines multiple sensor signals with real-time control algorithms and employs a closed-loop correction mechanism to ensure the device operates within safe parameter ranges during the massage process, thus protecting user safety. The specific implementation method is as follows:

[0094] 1. Data Sources and Basis

[0095] All data comes from the sensors and system control modules actually deployed on the massage chair, as detailed below:

[0096] Pressure contact signal: The pressure changes of the seat cushion and backrest are monitored in real time through the pressure sensor array built into the massage chair.

[0097] Position and displacement signals: backrest angle sensor and leg rest displacement sensor, using angle sensor and displacement sensor.

[0098] Operating status signals: The current sensor integrated into the massage chair control system monitors the motor current in real time, the airbag pressure sensor monitors the airbag pressure, and the heating unit temperature sensor detects the heating temperature in real time.

[0099] 2. Set of safety thresholds

[0100] To ensure safe operation, the manufacturer has set safety thresholds based on long-term experiments and user safety tests, which comply with international standards. The following are the upper limits of the parameters:

[0101] The maximum airbag pressure is 50 kPa, the maximum pressing force of the mechanism is 20 N, the maximum motor current is 2.5 A, the maximum heating temperature is 50 ℃, and the backrest / leg rest travel range is: backrest angle ±30°, leg rest displacement ±20 cm.

[0102] 3. Implementation Steps

[0103] During actual operation, the sensors inside the massage chair continuously collect signals and transmit them to the control system. The system then verifies and compares the collected signals with a set of safety thresholds in real time.

[0104] Data collection:

[0105] The actual pressure collected for the airbag was 45.5 kPa, the actual measured pressure of the mechanism was 18.2 N, the real-time monitored current of the motor was 2.1 A, the actual heating temperature was 48 °C, and the backrest angle was 28 °.

[0106] During the data acquisition process, none of the signals exceeded the set safety threshold, so no calibration was required.

[0107] 4. Correction Processing

[0108] If a user exceeds the limits during a massage, the following are some possible scenarios and their handling procedures:

[0109] Airbag pressure over-limit check: When the real-time monitoring shows that the airbag pressure is 55kPa, exceeding the upper limit of 50kPa, the system will trigger the correction logic within 5 seconds after the over-limit detection to ensure timely restoration to the safe parameter range.

[0110] Limiting treatment: The airbag pressure is adjusted to 50 kPa through the airbag control system, and a depressurization operation is performed.

[0111] Movement pressure over-limit check: When the movement pressing force is 22N, exceeding the upper limit of 20N, the system will immediately trigger a correction.

[0112] Limiting: Adjust the pressure to within 20N to ensure that excessive pressure is not caused.

[0113] Motor current over-limit check: When the motor current is 2.8A, exceeding the upper limit of 2.5A, the system will immediately execute the check.

[0114] Limiting: Reduce the current to below 2.5A to prevent motor overload.

[0115] The system will prioritize calibrating airbag pressure and motor current, as these directly affect user safety and comfort. If airbag pressure exceeds limits, the system will first depressurize; if motor current exceeds limits, the system will prioritize adjusting the current to prevent motor overload.

[0116] Heating temperature over-limit check: When the heating temperature is 52℃, it exceeds the upper limit of 50℃, and the system will execute immediately.

[0117] Cooling measures: Adjust the temperature to below 50℃ to prevent the heating device from overheating.

[0118] Backrest angle over-limit check: When the backrest angle is 35°, exceeding the ±30° range, the system will execute immediately.

[0119] Adjust the backrest angle to within 30° to ensure it does not exceed the safe range.

[0120] 5. Execution Results and Event Log

[0121] During execution, the system successfully adjusted all out-of-limit parameters to the safe range through amplitude limiting, without triggering a safety shutdown.

[0122] If the system fails to recover to a safe range through limiting, it will perform a safety shutdown and generate a trigger event log.

[0123] Final corrected parameters:

[0124] The airbag pressure was adjusted to 50 kPa, the mechanism pressing force was adjusted to 20 N, the motor current was adjusted to 2.5 A, the heating temperature was adjusted to 50 ℃, and the backrest angle was adjusted to 30°, all of which meet safety requirements.

[0125] Event Log:

[0126] Trigger time: 10:30 on January 29, 2026.

[0127] Triggering causes: airbag pressure, mechanism pressure, motor current, heating temperature, or backrest angle exceeding limits.

[0128] Processing method: Limit and adjust various parameters.

[0129] Event Log: Records all triggered signal values ​​and their correction processes in the system database, including the specific value at the time of triggering, changes before and after correction, and processing results.

[0130] 6. Safety shutdown judgment

[0131] All out-of-limit signals were successfully corrected without triggering a safety shutdown. If the system cannot restore the out-of-limit parameters to the safe range through limiting processing, and the out-of-limit state persists for more than 10 seconds, the system will trigger a safety shutdown.

[0132] After a safety shutdown is triggered, the system will immediately generate an event log, including the trigger time, cause, and specific signal value, and save it to the database for subsequent analysis and system optimization.

[0133] In summary, the intelligent massage chair successfully achieves automatic detection and real-time correction of control commands during operation, ensuring that all parameters remain within safe ranges. The closed-loop correction mechanism significantly improves the safety and reliability of the device, ensuring user comfort and safety. In practical applications, when multiple parameters exceed limits, the system can automatically adjust within seconds, minimizing the risk of equipment damage and safety hazards.

[0134] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An AI control and interaction system for a massage chair, characterized in that, include: Signal acquisition and interaction module: used to acquire pressure contact signals, posture displacement signals and operating status signals of the massage chair, and receive user interaction commands; User identification and profile learning module: used to identify different users and build corresponding user profiles. The user profile includes the user's preference parameter set and safety threshold set. The user profile is updated according to a preset profile update rule. The profile update rule includes: when a user's manual adjustment of massage parameters is detected or the execution feedback represented by the pressure contact signal and posture displacement signal is detected to meet the update trigger condition, the preference parameter set is incrementally updated and the safety threshold set is updated synchronously. Strategy generation and scheduling execution module: It is used to generate candidate control strategies based on the updated user profile and the current state of the massage chair, and determine the target control strategy from the candidate control strategies according to the preset scheduling rules, and output control commands to the massage chair actuator to drive the massage chair to work. Safety constraint and closed-loop correction module: used to perform constraint verification on the control command based on the safety threshold set and the pressure contact signal, posture displacement signal and running status signal before and during the execution of the target control strategy. When it is detected that the control parameters in the control command violate the constraint conditions of the safety threshold set, the control command is corrected online, including limiting the control parameters to a safe range, switching to a conservative strategy or triggering a safety shutdown.

2. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The pressure contact signal is collected by a pressure sensor array installed on the seat cushion and / or backrest, the posture displacement signal is collected by a backrest angle sensor and / or leg support displacement sensor, and the operating status signal includes the current signal of the massage motor, the temperature signal of the heating unit, and the air pressure signal of the airbag circuit.

3. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The signal acquisition and interaction module includes a panel hand controller and a mobile terminal or voice interface, and adds source identifiers to the instructions of different interaction interfaces so that the scheduling rules can determine the source priority.

4. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The user identification and profile learning module identifies users based on mobile terminal account login information or voiceprint features, and binds the user identification results as a unique user identifier so as to automatically call the corresponding user profile each time it is started.

5. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The user profile uses structured data storage. The set of preference parameters includes the target massage area, intensity level, rhythm parameters and single session duration. The set of safety thresholds includes the upper limit of the massage mechanism pressure or motor current, the upper limit of the airbag pressure, the upper limit of the heating temperature, and the identification of prohibited areas.

6. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The profile update rules include: when performing incremental updates on the preference parameter set, weighted fusion of historical preferences and current session preferences is performed, with the weight of current session preferences in the fusion being a preset learning rate; and when updating the security threshold set, a non-increment principle is adopted, meaning that the updated security threshold is not higher than the original security threshold.

7. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The update triggering conditions include: the number of times the user manually adjusts the same massage parameter in a single session reaches a preset number threshold; the pressure distribution deviation represented by the pressure contact signal continuously reaches a preset deviation threshold and continues to reach a preset duration threshold; and the change in the chair back angle or leg rest displacement represented by the posture displacement signal reaches a preset change threshold and continues to reach a preset duration threshold.

8. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The candidate control strategy includes linkage control parameters for the massage mechanism drive mechanism and the airbag inflation / deflation mechanism. The strategy generation and scheduling execution module calculates comfort indexes based on pressure contact signals and / or user manual adjustment actions, and uses the comfort indexes as the basis for determining the target control strategy. The comfort indexes include pressure distribution uniformity, contact loss rate, and manual adjustment frequency per unit time.

9. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The scheduling rules include: emergency stop commands have the highest priority, followed by commands from the control panel, and finally commands from the mobile terminal or voice. When commands from different sources are executed concurrently and the control parameters conflict with each other, the high-priority command overrides the low-priority command, and the overridden command is executed with a delay.

10. The AI ​​control and interaction system for a massage chair according to claim 1, characterized in that: The constraint verification includes at least upper limit constraint verification of airbag target pressure, mechanism pressing force or motor current, heating target temperature, and the travel range of the seat back or leg rest. When it is detected that the control parameter in the control command will trigger any upper limit constraint, the online correction performs amplitude limiting processing and / or strategy replacement processing. The conservative strategy includes reducing the strength and speed of the mechanism, reducing the airbag target pressure and performing depressurization, turning off or reducing the heating, and adjusting the seat back and leg rest to a preset safe posture. When the state of violating the set of safety thresholds continues to reach a preset duration threshold, the safety shutdown is triggered and an event record containing the triggering cause and triggering signal value is generated.

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