E-sports chair and dynamic support adjusting system and control method thereof

Abstract

The invention discloses an electronic sports chair and a dynamic support adjusting system and a control method thereof, and the system comprises an electronic sports chair main body; the power supply module is configured to provide a working power supply; the sitting posture sensing module is configured to collect multi-dimensional sitting posture data of a user; the dynamic support execution module is configured to provide dynamic support force for a user; the control module is respectively connected with the sitting posture sensing module and the dynamic support execution module, and is configured to obtain a predicted fatigue level through an LSTM fatigue prediction algorithm according to the multi-dimensional sitting posture data of the user, and obtain a corresponding dynamic support adjustment instruction according to the predicted fatigue level; and the dynamic support execution module is controlled to work according to the dynamic support adjustment instruction. Therefore, an accurate predicted fatigue level is obtained based on the multi-dimensional sitting posture data of the user in combination with the LSTM fatigue prediction algorithm, so that seat adjustment is intervened in advance, muscle fatigue accumulation is avoided, and intervention timeliness is improved.

Description

Technical Field

[0001] This invention relates to the field of seat control system technology, and in particular to a dynamic support adjustment system for a gaming chair, a gaming chair, and a control method for a gaming chair. Background Technology

[0002] With the rapid development of the e-sports industry, e-sports players generally play for more than 4 hours a day, and some professional players even play for 8-10 hours. Maintaining a fixed sitting posture for a long time (such as leaning forward and hunching over, with a tight back) will cause the back muscles to be in a state of tension, resulting in abnormal electromyographic signals and fatigue symptoms such as muscle soreness and stiffness. In severe cases, it may lead to chronic lumbar muscle strain, affecting the player's operational stability and health.

[0003] Currently, gaming chairs are core equipment for gamers, and their support performance directly affects the degree of muscle fatigue. However, existing products struggle to achieve targeted dynamic support adaptation. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the first objective of this invention is to provide a dynamic support adjustment system for a gaming chair, capable of intervening in seat adjustments in advance to avoid muscle fatigue accumulation and improve the timeliness of intervention.

[0005] The second objective of this invention is to provide a gaming chair. The third objective of this invention is to provide a control method for a gaming chair.

[0006] To achieve the above objectives, the first aspect of the present invention provides a dynamic support adjustment system for a gaming chair, comprising: a gaming chair body; a power module configured to provide operating power; a posture sensing module configured to collect multi-dimensional posture data of a user; a dynamic support execution module configured to provide dynamic support force to the user; and a control module connected to both the posture sensing module and the dynamic support execution module. The control module is configured to obtain a predicted fatigue level based on the user's multi-dimensional posture data using an LSTM fatigue prediction algorithm, and to obtain a corresponding dynamic support adjustment command based on the predicted fatigue level, thereby controlling the dynamic support execution module to operate according to the dynamic support adjustment command.

[0007] The dynamic support adjustment system of the gaming chair according to an embodiment of the present invention is connected to a posture sensing module and a dynamic support execution module via a control module. The control module obtains a predicted fatigue level based on the user's multi-dimensional posture data using an LSTM fatigue prediction algorithm, and then obtains corresponding dynamic support adjustment commands based on the predicted fatigue level. The dynamic support execution module is then controlled to operate according to these commands. Therefore, by combining multi-dimensional posture data with the LSTM fatigue prediction algorithm, an accurate predicted fatigue level is obtained, allowing for early intervention in seat adjustment, preventing muscle fatigue accumulation, and improving the timeliness of intervention.

[0008] In addition, the dynamic support adjustment system of the gaming chair according to the above embodiments of the present invention may also have the following additional technical features: According to one embodiment of the present invention, the user's multidimensional sitting posture data includes the user's lumbar and back electromyography signals, the user's sitting posture holding time, and the user's heart rate data.

[0009] According to one embodiment of the present invention, the control module includes: a data preprocessing unit configured to preprocess the user's multidimensional sitting posture data; an LSTM fatigue prediction algorithm unit configured to output the predicted fatigue level based on the preprocessed user multidimensional sitting posture data, wherein the predicted fatigue level includes mild fatigue, moderate fatigue, and severe fatigue; and a control decision unit configured to obtain corresponding dynamic support adjustment instructions based on the predicted fatigue level.

[0010] According to one embodiment of the present invention, the control module is further configured to re-obtain the predicted fatigue level based on the user's multidimensional sitting posture data at preset time intervals.

[0011] According to one embodiment of the present invention, the control module is further configured to output a dynamic support reset command if the predicted fatigue level changes from moderate or severe fatigue to mild fatigue; and to output a dynamic support fine-tuning command if the predicted fatigue level remains at moderate or severe fatigue.

[0012] According to one embodiment of the present invention, the sitting posture sensing module includes: an electromyography (EMG) sensing module configured to acquire the user's lumbar and back EMG signals; and a physiological parameter acquisition module configured to acquire the user's sitting posture holding time and the user's heart rate data.

[0013] According to one embodiment of the present invention, the dynamic support execution module includes: a lumbar support unit, the lumbar support unit including an electric airbag, the lumbar support unit being configured to inflate or deflate the electric airbag via a micro air pump and a solenoid valve to provide corresponding support for the user's lower back; a backrest side wing unit, the backrest side wing unit being configured to retract inward by a stepper motor to wrap around the user's lower back; and a seat tilt adjustment unit, the seat tilt adjustment unit being configured to be driven by a DC geared motor to tilt the seat backward by a preset angle.

[0014] According to one embodiment of the present invention, the system further includes an interaction module, the interaction module comprising: a touch screen configured to display the user's sitting posture and acquire user operation commands; a status indicator light configured to display the predicted fatigue level; and a wireless communication unit configured to synchronize the predicted fatigue level and adjustment record to a mobile terminal.

[0015] To achieve the above objectives, the second aspect of the present invention provides a gaming chair that includes the dynamic support adjustment system of the gaming chair described in the above-described embodiment of the present invention.

[0016] According to an embodiment of the present invention, the gaming chair employs the aforementioned dynamic support adjustment system, which can obtain an accurate fatigue level based on the user's multi-dimensional sitting posture data combined with the LSTM fatigue prediction algorithm. This allows for early intervention in seat adjustment, preventing muscle fatigue accumulation and improving the timeliness of intervention.

[0017] To achieve the above objectives, the third aspect of the present invention provides a control method for a gaming chair, comprising: acquiring multi-dimensional user posture data; obtaining a predicted fatigue level based on the multi-dimensional user posture data using an LSTM fatigue prediction algorithm, and obtaining a corresponding dynamic support adjustment command based on the predicted fatigue level; and controlling a dynamic support execution module to operate according to the dynamic support adjustment command.

[0018] According to the control method of the gaming chair of the present invention, multi-dimensional sitting posture data of the user is acquired. Then, based on the multi-dimensional sitting posture data, a predicted fatigue level is obtained using an LSTM fatigue prediction algorithm. A corresponding dynamic support adjustment command is obtained based on the predicted fatigue level. Finally, the dynamic support execution module is controlled to operate according to the dynamic support adjustment command. Therefore, based on the user's multi-dimensional sitting posture data combined with the LSTM fatigue prediction algorithm, an accurate predicted fatigue level is obtained, thereby allowing for early intervention in seat adjustment, avoiding muscle fatigue accumulation, and improving the timeliness of intervention.

[0019] Additional aspects and advantages of the invention 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 the invention. Attached Figure Description

[0020] Figure 1 This is a block diagram of the dynamic support adjustment system of a gaming chair according to an embodiment of the present invention; Figure 2 This is a block diagram of a dynamic support adjustment system for a gaming chair according to an embodiment of the present invention. Figure 3 This is a block diagram of a gaming chair according to an embodiment of the present invention; Figure 4 This is a flowchart illustrating the control method for a gaming chair according to an embodiment of the present invention. Detailed Implementation

[0021] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be configured to explain the present invention, and should not be construed as limiting the present invention.

[0022] The following description, with reference to the accompanying drawings, describes a dynamic support adjustment system for a gaming chair, a gaming chair, and a control method for a gaming chair according to embodiments of the present invention.

[0023] Figure 1 This is a block diagram of the dynamic support adjustment system of a gaming chair according to an embodiment of the present invention.

[0024] Specifically, in some embodiments of the present invention, such as Figure 1 As shown, the dynamic support adjustment system 100 of the gaming chair includes: gaming chair body 10, power module 20, posture sensing module 30, dynamic support execution module 40 and control module 50.

[0025] The power module 20 is configured to provide operating power; the posture sensing module 30 is configured to collect multi-dimensional posture data of the user; the dynamic support execution module 40 is configured to provide dynamic support force to the user; the control module 50 is connected to the posture sensing module 30 and the dynamic support execution module 40 respectively. The control module 50 is configured to obtain the predicted fatigue level based on the user's multi-dimensional posture data through the LSTM fatigue prediction algorithm, and obtain the corresponding dynamic support adjustment command based on the predicted fatigue level, so as to control the dynamic support execution module 40 to work according to the dynamic support adjustment command.

[0026] It is understood that, in this embodiment of the present invention, the dynamic support adjustment system 100 of the gaming chair consists of a gaming chair body 10, a power module 20, a posture sensing module 30, a dynamic support execution module 40, and a control module 50. The specific arrangement of the gaming chair body 10, power module 20, posture sensing module 30, dynamic support execution module 40, and control module 50 is as follows: The main body 10 of the gaming chair is made of high-strength aluminum alloy frame and breathable PU leather material, specifically including seat, backrest, headrest, armrest and leg assembly. The inner side of the backrest is provided with the installation area of ​​posture sensing module 30 (e.g., electromyography sensor) and dynamic support execution module 40 (e.g., lumbar support). The bottom of the seat is provided with the installation area of ​​dynamic support execution module 40 (e.g., tilt adjustment drive mechanism).

[0027] The power module 20 has an input voltage of 12V, supports AC power supply and lithium battery power supply (power supply time ≥12 hours), includes overcurrent, overvoltage and overtemperature protection circuits, and has an output power of ≥20W to meet the stable operation requirements of each module.

[0028] The control module 50 is installed in the central cavity inside the chair back and is connected to the posture sensing module 30 and the dynamic support execution module 40 respectively. Based on the user's multi-dimensional posture data (collected and uploaded by the posture sensing module 30), the control module 50 obtains the predicted fatigue level through the LSTM fatigue prediction algorithm and obtains the corresponding dynamic support adjustment command based on the predicted fatigue level. The control module 50 is then controlled to work according to the dynamic support adjustment command (received and executed by the dynamic support execution module 40).

[0029] Specifically, in the above embodiments of the present invention, the predicted fatigue level is calculated by combining the user's multidimensional sitting posture data with the LSTM fatigue prediction algorithm, with a prediction accuracy of ≥90%. Compared with the existing "passive response" scheme, early intervention and adjustment can avoid the accumulation of muscle fatigue and improve the timeliness of intervention by 70%.

[0030] Furthermore, in some embodiments of the present invention, the user's multidimensional sitting posture data includes the user's lumbar and back electromyographic signals, the user's sitting posture holding time, and the user's heart rate data.

[0031] It is understood that, in this embodiment of the present invention, compared with the prior art that judges fatigue solely by pressure or subjective feelings, using the user's lumbar and back electromyography signals, the user's sitting posture holding time, and the user's heart rate data as multidimensional sitting posture data for predicting fatigue levels can improve the accuracy of assessment and enhance the seat adjustment effect.

[0032] Specifically, in the above embodiments of the present invention, the user's lumbar and back electromyographic signals (core fatigue index), the user's sitting posture holding time (cumulative fatigue factor) and the user's heart rate data (indirect fatigue correlation index) are integrated. Compared with the single parameter assessment scheme, the accuracy of fatigue level judgment is improved by 50%, avoiding misadjustment.

[0033] Furthermore, in some embodiments of the present invention, such as Figure 2 As shown, the control module 50 includes: a data preprocessing unit 501, an LSTM fatigue prediction algorithm unit 502, and a control decision unit 503.

[0034] The data preprocessing unit 501 is configured to preprocess the user's multidimensional sitting posture data; the LSTM fatigue prediction algorithm unit 502 is configured to output a predicted fatigue level based on the preprocessed user multidimensional sitting posture data, wherein the predicted fatigue level includes mild fatigue, moderate fatigue and severe fatigue; and the control decision unit 503 is configured to obtain the corresponding dynamic support adjustment command based on the predicted fatigue level.

[0035] It is understood that, in this embodiment of the present invention, the control module 50 consists of a data preprocessing unit 501, an LSTM fatigue prediction algorithm unit 502, and a control decision unit 503. The specific configuration of the data preprocessing unit 501, the LSTM fatigue prediction algorithm unit 502, and the control decision unit 503 is as follows: The data preprocessing unit 501 preprocesses the user's multidimensional sitting posture data (user's back electromyography signal, user's sitting posture holding time, user's heart rate data) (e.g., low-pass filtering, normalization processing, etc.) to remove environmental interference and outliers.

[0036] The LSTM fatigue prediction algorithm unit 502 has a built-in LSTM fatigue prediction model (for example, a model trained based on 2000 sets of historical data from 100 users (each set of historical data includes 4 consecutive hours of user lumbar and back electromyography signals, user sitting time, user heart rate data, and corresponding predicted fatigue level labels). The input of this training model is the user's lumbar and back electromyography signals, user sitting time, and user heart rate data, and the output is the predicted fatigue level (mild fatigue, moderate fatigue, and severe fatigue).

[0037] The control decision unit 503 has a built-in dynamic support adjustment instruction strategy library, which can determine the corresponding dynamic support adjustment instruction based on the predicted fatigue level output by the LSTM fatigue prediction algorithm unit 502, and send the dynamic support adjustment instruction to the dynamic support execution module 40.

[0038] Furthermore, in some embodiments of the present invention, the control module 50 is also configured to re-obtain the predicted fatigue level based on the user's multidimensional sitting posture data at preset time intervals.

[0039] It is understood that, in this embodiment of the present invention, the control module 50 can re-obtain the predicted fatigue level based on the user's multidimensional sitting posture data at preset time intervals (e.g., every 5 minutes), thereby realizing cyclic monitoring and adjustment optimization.

[0040] Furthermore, in some embodiments of the present invention, the control module 50 is also configured to output a dynamic support reset command if the predicted fatigue level changes from moderate or severe fatigue to mild fatigue; and to output a dynamic support fine-tuning command if the predicted fatigue level remains moderate or severe fatigue.

[0041] It is understood that, in this embodiment of the present invention, when the predicted fatigue level changes from moderate or severe fatigue to mild fatigue, it can be considered that the dynamic support adjustment based on the predicted fatigue level has effectively alleviated user fatigue. At this time, the control module 50 restores the dynamic support execution module 40 to its original position by outputting a dynamic support reset command, so as to facilitate the next dynamic support adjustment. When the predicted fatigue level remains at moderate or severe fatigue, it can be considered that the dynamic support adjustment based on the predicted fatigue level has not yet alleviated user fatigue. At this time, the control module 50 outputs a dynamic support fine-tuning command to fine-tune the dynamic support execution module 40 (e.g., increase the support force by 3%), thereby further alleviating user fatigue.

[0042] Furthermore, in some embodiments of the present invention, such as Figure 2 As shown, the sitting posture sensing module 30 includes: an electromyography sensing module 301 and a physiological parameter acquisition module 302.

[0043] Among them, the electromyography sensing module 301 is configured to collect the user's lumbar and back electromyography signals; the physiological parameter acquisition module 302 is configured to collect the user's sitting posture holding time and user heart rate data.

[0044] It is understood that, in this embodiment of the present invention, the posture sensing module 30 is composed of an electromyography (EMG) sensing module 301 and a physiological parameter acquisition module 302, wherein the specific configuration of the EMG sensing module 301 and the physiological parameter acquisition module 302 is as follows: The electromyography (EMG) sensing module 301 employs multiple dry electrode EMG sensors (skin fit ≥90%) or flexible dry electrode EMG sensors (skin fit ≥95%), which are installed on the chair back corresponding to the erector spinae muscles (5cm away from both sides of the lumbar spine). By acquiring the user's lumbar and back EMG signals in real time, the module calculates and outputs the root mean square (RMS) value of the EMG signal. The sensing parameters of the dry electrode EMG sensor or the flexible dry electrode EMG sensor are as follows: sampling frequency of 200Hz, detection range of 0-1001μV, and accuracy of ±1μV.

[0045] The physiological parameter acquisition module 302 includes a sitting posture timing unit and a heart rate acquisition unit. The sitting posture timing unit is integrated into the seat pressure sensor, which detects the user's sitting state and accumulates the sitting posture holding time (accuracy ±1 minute). The heart rate acquisition unit includes a photoelectric heart rate sensor integrated into the front end of the armrest, which collects the user's heart rate data in real time. The sensing parameters of the heart rate acquisition unit are as follows: sampling frequency of 1Hz, detection range of 50-180 beats / minute, and accuracy of ±2 beats / minute.

[0046] Furthermore, in some embodiments of the present invention, such as Figure 2 As shown, the dynamic support execution module 40 includes: a lumbar support unit 401, a backrest side wing unit 402, and a seat tilt adjustment unit 403.

[0047] The lumbar support unit 401 includes an electric airbag, which is configured to inflate or deflate the electric airbag via a micro air pump and a solenoid valve to provide corresponding support for the user's lower back. The backrest side wing unit 402 is configured to retract inward by a stepper motor to wrap around the user's lower back. The seat tilt adjustment unit 403 is configured to be driven by a DC geared motor to tilt the seat backward at a preset angle.

[0048] It is understood that, in this embodiment of the present invention, the dynamic support execution module 40 is composed of a lumbar support unit 401, a backrest side wing unit 402, and a seat tilt adjustment unit 403. The specific arrangement of the lumbar support unit 401, the backrest side wing unit 402, and the seat tilt adjustment unit 403 is as follows: The lumbar support unit 401 adopts an electric airbag structure (or a composite structure of memory foam and airbag to improve support comfort) and has a built-in micro air pump, solenoid valve and pressure sensor. The specific adjustment process is that after receiving the dynamic support adjustment command, the electric airbag is inflated or deflated by the micro air pump and solenoid valve to enhance or weaken the support force of the electric airbag. The adjustment range of the lumbar support unit 401 is 112%-115% of the initial support force, the support force accuracy is ±0.5N, and the response time is ≤300ms.

[0049] The backrest side wing unit 402 adopts an electric telescopic structure or a pneumatic telescopic structure (with a faster adjustment response time). The specific adjustment process is that after receiving the dynamic support adjustment command, it is driven by a stepper motor to retract inward, thereby increasing the wrapping degree by 20% (reducing the side wing spacing by 3-5cm). The adjustment accuracy of the backrest side wing unit 402 is ±0.1cm, and the response time is ≤400ms.

[0050] The seat tilt adjustment unit 403 is driven by a DC geared motor. The specific adjustment process is as follows: after receiving the dynamic support adjustment command, the DC geared motor drives the seat to tilt backward by a preset angle (e.g., 2°). The adjustment accuracy of the seat tilt adjustment unit 403 is ±0.1°, and the response time is ≤500ms.

[0051] Specifically, in the above embodiments of the present invention, a triple dynamic support strategy of "lumbar support pressure increase + side wing wrapping + tilt angle fine adjustment" is designed for areas prone to fatigue, such as erector spinae, trapezius, and sacrum. This reduces muscle fatigue by 65%, improves player operation stability by 40%, and effectively prevents chronic lumbar muscle strain.

[0052] Furthermore, in some embodiments of the present invention, such as Figure 2 As shown, the dynamic support adjustment system 100 of the gaming chair also includes an interaction module 60, which includes a touch screen 601, a status indicator light 602, and a wireless communication unit 603.

[0053] The touch screen 601 is configured to display the user's sitting posture and acquire user operation commands; the status indicator 602 is configured to display the predicted fatigue level; and the wireless communication unit 603 is configured to synchronize the predicted fatigue level and adjustment record to the mobile terminal.

[0054] It is understood that in this embodiment of the present invention, the interaction module 60 consists of a touch screen 601, a status indicator light 602, and a wireless communication unit 603. The specific configuration of the touch screen 601, the status indicator light 602, and the wireless communication unit 603 is as follows: The touch screen 601 is installed on the side of the chair back and can be used to display the user's sitting posture status (e.g., current fatigue level prediction result, user sitting posture holding time, user heart rate data and support adjustment status, etc.) and to obtain user operation commands (e.g., user manually sets fatigue equals threshold and adjusts sensitivity, etc.).

[0055] The status indicator light 602 is installed on the top of the chair back. The status indicator light 602 uses different colors to indicate different predicted fatigue levels. For example, if the predicted fatigue level is mild fatigue, it will be green to indicate that no adjustment is needed; if the predicted fatigue level is moderate fatigue, it will be yellow to indicate that adjustment is in progress; and if the predicted fatigue level is severe fatigue, it will be red to indicate an over-fatigue warning.

[0056] The wireless communication unit 603 supports Bluetooth 5.2 communication, can connect with the user's mobile APP to synchronize fatigue data and adjustment records, and supports remote parameter settings.

[0057] The working principle of the dynamic support adjustment system 100 of the gaming chair according to the present invention will be explained below with reference to specific embodiments of the present invention (divided into initialization stage, data acquisition stage, fatigue prediction stage, dynamic adjustment stage and cycle monitoring stage): Initialization phase (1) When the user turns on the power of the gaming chair, the control module 50 completes the self-test of each module, and the touch screen 601 displays that the initialization is complete; (2) After the user sits down, the seat pressure sensor triggers the sitting posture timing unit to start, and at the same time the heart rate acquisition unit and electromyography sensor module 301 start to warm up and complete the baseline calibration (record the RMS value and heart rate baseline value in the initial state).

[0058] Data collection phase (1) The electromyography sensor module 301 collects the electromyography signals of the lumbar back in real time, calculates the RMS value every 500ms and transmits it to the control module 50; (2) The sitting posture timing unit continuously accumulates the time the player maintains the sitting posture and synchronizes it to the control module 50 in real time; (3) The heart rate acquisition unit collects the user's heart rate data once every 1 second and transmits it to the control module 50; (4) The three types of data are stored synchronously to form a time-series data sequence.

[0059] Fatigue prediction stage (1) The data preprocessing unit 501 performs filtering and normalization processing on the collected RMS value, sitting posture holding time and heart rate data; (2) The LSTM fatigue prediction algorithm unit 502 calls the trained model and inputs "current RMS value + RMS value change trend in the last 30 minutes + cumulative sitting time + real-time heart rate" to calculate and output the predicted fatigue level (mild fatigue, moderate fatigue and severe fatigue) 10 minutes later. (3) The control decision unit 503 obtains the corresponding dynamic support adjustment command based on the predicted fatigue level.

[0060] Dynamic adjustment stage (1) If the predicted fatigue level is mild fatigue: the status indicator 602 shows green, the system continues to collect data and update the prediction results in real time, and does not perform any adjustment actions; (2) If the predicted fatigue level is moderate fatigue: Status indicator 602 turns yellow, and control module 50 synchronously outputs three sets of adjustment commands: Lumbar support unit 401: When the miniature air pump is activated, the lumbar support airbag inflates, increasing the support force by 12-15%. The pressure sensor provides real-time feedback of the pressure value, and inflation stops once the target value is reached. Chair back side wing unit 402: The stepper motor drives the side wing to retract inward, increasing the wrapping effect by 20%, and sends a positioning signal after it is in place; Seat tilt adjustment unit 403: The DC geared motor drives the seat to tilt back 2°, and the action stops after the tilt sensor sends a signal indicating that the seat has reached the target position. (3) If the predicted fatigue level is severe fatigue: the status indicator 602 switches to red, and at the same time, a severe fatigue warning is sent to the user's mobile phone APP through the wireless communication unit 603 to remind them to take appropriate rest.

[0061] Cyclic monitoring phase (1) After adjustment, the system continues to collect data and re-acquires the predicted fatigue level every 5 minutes; (2) If the predicted fatigue level drops to mild fatigue: the dynamic support execution module 40 is reset along the original path, and the status indicator 602 returns to green; (3) If the predicted fatigue level is still moderate or severe fatigue: adjust the support parameters (such as increasing the lumbar support force by 3%) according to the new RMS value change trend to ensure the fatigue relief effect; (4) After the user finishes using the device, the sitting posture timing unit is reset, and the system stores the fatigue data and adjustment records of this use and synchronizes them to the mobile APP.

[0062] In summary, the dynamic support adjustment system of the gaming chair according to an embodiment of the present invention connects a control module to a posture sensing module and a dynamic support execution module. The control module obtains a predicted fatigue level based on the user's multi-dimensional posture data using an LSTM fatigue prediction algorithm, and then obtains corresponding dynamic support adjustment commands based on the predicted fatigue level. These commands are then used to control the dynamic support execution module to operate. Therefore, by combining multi-dimensional posture data with the LSTM fatigue prediction algorithm, an accurate predicted fatigue level is obtained, allowing for early intervention in seat adjustment, preventing muscle fatigue accumulation, and improving the timeliness of intervention.

[0063] Figure 3 This is a block diagram of a gaming chair according to an embodiment of the present invention.

[0064] Specifically, in some embodiments of the present invention, such as Figure 3 As shown, the gaming chair 1000 includes the dynamic support adjustment system 100 of the gaming chair according to the above embodiment of the present invention.

[0065] It should be understood that the specific implementation of the gaming chair 1000 in the embodiments of the present invention can refer to the specific implementation of the dynamic support adjustment system 100 of the gaming chair in the foregoing embodiments of the present invention. To reduce redundancy, it will not be described again here.

[0066] In summary, the gaming chair according to the embodiments of the present invention, employing the aforementioned dynamic support adjustment system, can accurately predict fatigue levels based on multi-dimensional user posture data combined with the LSTM fatigue prediction algorithm. This allows for early intervention in seat adjustment, preventing muscle fatigue accumulation and improving the timeliness of intervention.

[0067] Figure 4 This is a flowchart illustrating the control method for a gaming chair according to an embodiment of the present invention.

[0068] Specifically, in some embodiments of the present invention, such as Figure 4 As shown, the control method of the gaming chair includes: S101, acquires multi-dimensional sitting posture data of the user.

[0069] It is understood that, in this embodiment of the present invention, the user's multidimensional sitting posture data includes the user's lumbar and back electromyographic signals, the user's sitting posture holding time, and the user's heart rate data.

[0070] S102 obtains the predicted fatigue level based on the user's multidimensional sitting posture data through the LSTM fatigue prediction algorithm, and obtains the corresponding dynamic support adjustment command based on the predicted fatigue level.

[0071] It is understood that in this embodiment of the present invention, the user's multi-dimensional sitting posture data is combined with the LSTM fatigue prediction algorithm to obtain an accurate predicted fatigue level, so as to obtain the corresponding dynamic support adjustment command through the predicted fatigue level.

[0072] S103 controls the dynamic support execution module to work according to the dynamic support adjustment command.

[0073] It is understood that in this embodiment of the present invention, the dynamic support execution module is controlled by the dynamic support adjustment command to intervene in the seat adjustment in advance, avoid muscle fatigue accumulation, and improve the timeliness of intervention.

[0074] It should be understood that the specific implementation of the control method of the gaming chair in the embodiments of the present invention can be found in the specific implementation of the dynamic support adjustment system 100 of the gaming chair in the foregoing embodiments of the present invention. To reduce redundancy, it will not be described again here.

[0075] In summary, the control method for the gaming chair according to embodiments of the present invention acquires multi-dimensional user posture data, then obtains a predicted fatigue level based on the multi-dimensional user posture data using an LSTM fatigue prediction algorithm, obtains corresponding dynamic support adjustment commands based on the predicted fatigue level, and controls the dynamic support execution module to operate according to the dynamic support adjustment commands. Therefore, by combining multi-dimensional user posture data with the LSTM fatigue prediction algorithm, an accurate predicted fatigue level is obtained, thereby allowing for early intervention in seat adjustment, preventing muscle fatigue accumulation, and improving the timeliness of intervention.

[0076] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions configured to perform logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0077] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates configured to perform logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0078] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "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 the invention. 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.

[0079] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0080] Furthermore, the terms "first" and "second" are configured for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0081] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0082] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0083] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A dynamic support adjustment system for a gaming chair, the system comprising: The system comprises: an e-sports chair body; a power module configured to provide working power; a sitting posture sensing module configured to collect multi-dimensional sitting posture data of a user; a dynamic support execution module configured to provide dynamic support force for the user; a control module connected with the sitting posture sensing module and the dynamic support execution module, respectively, and configured to obtain a predicted fatigue level by an LSTM fatigue level prediction algorithm according to the multi-dimensional sitting posture data of the user, and obtain corresponding dynamic support adjustment instructions according to the predicted fatigue level, so as to control the dynamic support execution module to work according to the dynamic support adjustment instructions.

2. The dynamic support adjustment system of an e-sports chair of claim 1, wherein, The multi-dimensional sitting posture data of the user comprises user lumbar muscle electrical signals, user sitting posture holding time and user heart rate data.

3. The dynamic support adjustment system of an e-sports chair of claim 2, wherein, The control module comprises: a data preprocessing unit configured to preprocess the multi-dimensional sitting posture data of the user; an LSTM fatigue level prediction algorithm unit configured to output the predicted fatigue level according to the preprocessed multi-dimensional sitting posture data of the user, wherein the predicted fatigue level comprises mild fatigue, moderate fatigue and severe fatigue; a control decision unit configured to obtain corresponding dynamic support adjustment instructions according to the predicted fatigue level.

4. The dynamic support adjustment system of an e-sports chair of claim 3, wherein, The control module is further configured to obtain a predicted fatigue level again according to the multi-dimensional sitting posture data of the user every interval of a preset time.

5. The dynamic support adjustment system of an e-sports chair of claim 4, wherein, The control module is further configured to output a dynamic support reset instruction if the predicted fatigue level changes from moderate fatigue or severe fatigue to mild fatigue, and output a dynamic support fine-tuning instruction if the predicted fatigue level remains moderate fatigue or severe fatigue.

6. The dynamic support adjustment system of an e-sports chair of claim 2, wherein, The sitting posture sensing module comprises: a muscle electrical sensing module configured to collect the user lumbar muscle electrical signals; a physiological parameter collection module configured to collect the user sitting posture holding time and the user heart rate data.

7. The dynamic support adjustment system of an e-sports chair of claim 1, wherein, The dynamic support execution module comprises: a lumbar support unit comprising an electric air bag, the lumbar support unit being configured to inflate or deflate the electric air bag by a micro air pump and a solenoid valve, so as to provide corresponding support force for the user's lumbar back; a chair back side wing unit configured to be driven by a stepping motor to shrink inwardly to wrap the user's lumbar back; a seat inclination adjustment unit configured to be driven by a DC speed reduction motor to drive the seat to tilt backward by a preset angle.

8. The dynamic support adjustment system of an e-sports chair of claim 1, wherein, The system further comprises an interaction module comprising: a touch operation screen configured to display a user sitting posture state and obtain a user operation instruction; a state indicating lamp configured to display the predicted fatigue level; a wireless communication unit configured to synchronize the predicted fatigue level and adjustment records to a mobile terminal.

9. An e-sports chair, characterized in that, The e-sports chair comprises the dynamic support adjustment system of the e-sports chair according to any one of claims 1-8.

10. A control method of the e-sports chair according to claim 9, characterized by, The method comprises: Obtaining multi-dimensional sitting posture data of a user; Obtaining a predicted fatigue level through an LSTM fatigue prediction algorithm according to the multi-dimensional sitting posture data of the user, and obtaining a corresponding dynamic support adjustment instruction according to the predicted fatigue level; Controlling the dynamic support execution module to work according to the dynamic support adjustment instruction.

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