Human-computer interaction method and system based on sEMG and multi-channel electrostimulation tactile feedback

Abstract

This invention relates to a human-computer interaction method and system based on sEMG and multi-channel electrical stimulation tactile feedback. The method includes acquiring and processing the user's surface electromyography (sEMG) signals to obtain EMG data; calculating the mean absolute value based on the EMG data, mapping the mean absolute value to motion control commands for a robotic hand, and sending the motion control commands to the robotic hand to control it to perform corresponding actions; receiving the robotic hand's state data in real time, generating electrical stimulation parameters based on the state data using an electrical stimulation strategy; and generating and outputting electrical stimulation signals to electrical stimulation electrodes based on the control signals to provide tactile feedback to the user. This invention allows users to grasp the opening and closing degree, movement speed, and grasping force of the robotic hand in real time solely through tactile perception, without excessive reliance on visual monitoring, and adjust their own muscle contractions accordingly to complete fine operations. This reduces the cognitive load during operation and improves the reliability of human-computer interaction.

Description

Technical Field

[0001] This invention relates to the field of human-computer interaction technology, specifically to a human-computer interaction method and system based on sEMG and multi-channel electrical stimulation tactile feedback. Background Technology

[0002] Surface electromyography (sEMG), as the most direct electrophysiological representation of human movement intention, has become a key signal source in human-computer interaction, rehabilitation medicine, and intelligent prosthetic control due to its non-invasiveness, ease of acquisition, and rich information on muscle activity. With the rapid development of flexible electronics, embedded systems, and pattern recognition algorithms, dexterous manipulators based on sEMG control have moved from laboratory research to preliminary clinical applications. Currently, the mainstream strategies for sEMG-controlled dexterous manipulators are mainly divided into two categories: one is to use algorithms such as support vector machines (SVM) and convolutional neural networks (CNN) to recognize specific gestures and achieve control of specific movements of the prosthetic hand; the other is based on continuous proportional control methods, which establish a model of the amplitude of sEMG signals and the speed and force of prosthetic movement to achieve continuous proportional control of the joint angle and opening / closing speed of the prosthetic limb.

[0003] However, regardless of the control strategy employed, current commercial and academic myoelectric prosthetic systems generally face a core bottleneck: they only achieve "one-way" decoding and control of motor intentions, lacking a "two-way" sensory feedback pathway. Without sensory feedback, users rely excessively on visual monitoring when using the prosthetic hand, often struggling to achieve precise force control, easily leading to damage or slippage of grasped objects, necessitating closed-loop control through visual compensation. Research indicates that the lack of tactile feedback is one of the main reasons for the high cognitive load, clumsy movements, and high abandonment rate of prosthetics after long-term use.

[0004] To address the lack of tactile feedback, researchers have explored various methods to provide sensory feedback to prosthetic users. Among these, electrical stimulation, due to its precisely controllable electrical pulse parameters and ability to safely activate superficial subcutaneous nerve endings to induce specific tactile sensations (such as pressure or vibration), is considered one of the most promising technological approaches for constructing tactile feedback loops. However, existing technologies still have many shortcomings: First, at the circuit implementation level, traditional multi-channel electrostimulation systems typically design independent boost, constant current, and H-bridge circuits for each channel. This results in complex circuitry, large printed circuit board (PCB) area, and high power consumption, making it difficult to meet the stringent miniaturization and integration requirements of wearable devices. Second, at the feedback strategy level, existing research mostly uses electrostimulation as an independent open-loop module, failing to establish a dynamic closed-loop feedback strategy that deeply integrates with sEMG intent recognition results and the real-time motion state of the robotic hand. Finally, at the feedback encoding level, existing electrostimulation tactile feedback schemes mostly employ simple linear mapping strategies, such as directly and linearly converting contact force sensor values ​​into a single stimulation intensity or frequency. This strategy fails to fully utilize the multi-dimensional adjustable parameters of electrostimulation, such as intensity, frequency, pulse width, and stimulation point, making it difficult to encode multi-modal state information of the robotic hand, such as finger opening and closing speed, and contact pressure, resulting in single-dimensional feedback information and ambiguous user perception. Summary of the Invention

[0005] Based on the above description, the present invention provides a human-computer interaction method and system based on sEMG and multi-channel electrical stimulation tactile feedback, aiming to solve the problems of heavy user cognitive burden and low operation accuracy caused by the lack of effective bidirectional closed-loop feedback in existing human-computer interaction systems based on surface electromyography signals, as well as the problems of large size and single dimension of feedback information in existing electrical stimulation feedback hardware.

[0006] The technical solution of the present invention to solve the above-mentioned technical problems is as follows: Firstly, a human-computer interaction method based on sEMG and multi-channel electrical stimulation tactile feedback includes: The user's surface electromyography (EMG) signals are collected and processed to obtain EMG data; The average absolute value is calculated based on the electromyography data, the average absolute value is mapped to the motion control command of the robotic arm, and the motion control command is sent to the robotic arm to control the robotic arm to perform the corresponding action. The system receives real-time status data of the robotic hand and generates electrical stimulation parameters based on the status data using an electrical stimulation strategy. The status data includes at least finger spread, movement speed, and contact pressure, and the electrical stimulation parameters include at least stimulation channel selection, current amplitude, pulse frequency, and pulse width. A control signal is generated based on the electrical stimulation parameters; The control signal generates and outputs an electrical stimulation signal to the electrical stimulation electrode to provide tactile feedback to the user.

[0007] Furthermore, the electrical stimulation strategy includes: Spatial position encoding is used to select different stimulation channels to output the electrical stimulation pulses according to the degree of finger opening; Velocity encoding is used to linearly adjust the pulse frequency output by the selected stimulation channel according to the magnitude of the motion velocity. Pressure coding is used to adjust the pulse frequency or pulse width according to the magnitude of the contact pressure.

[0008] Furthermore, the pressure encoding further includes: When the contact pressure is lower than the contact pressure threshold, the pulse frequency is fixed and the pulse width is adjusted according to the magnitude of the contact pressure to achieve feedback for precise grasping. When the contact pressure is higher than the contact pressure threshold, the maximum pulse width is maintained, and the pulse frequency is adjusted according to the magnitude of the contact pressure to achieve feedback for strong gripping.

[0009] Based on the above technical solution, the present invention can be further improved as follows.

[0010] Secondly, a human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback, used to implement the method described in the first aspect, includes: The electromyography (EMG) acquisition module is configured to acquire and process the user's surface electromyography (EMG) signals to obtain EMG data. The lower-level machine is bidirectionally connected to the electromyography acquisition module. The lower-level machine is configured to receive and send the electromyography data, and to generate control signals based on the electrical stimulation parameters. The host computer is bidirectionally connected to the slave computer. The host computer is used to communicate bidirectionally with the robotic arm. The host computer is configured to receive the electromyography data uploaded by the slave computer and calculate the mean absolute value, map the mean absolute value to the motion control command of the robotic arm, and send the motion control command to the robotic arm. The host computer is also configured to receive the status data of the robotic arm in real time, generate the electrical stimulation parameters according to the status data using an electrical stimulation strategy, and send them to the slave computer. The electrostimulation module includes a stimulation driving circuit and a high-voltage channel switch. The voltage input terminal of the stimulation driving circuit is electrically connected to the voltage output terminal of the lower-level machine. The common input terminal group of the high-voltage channel switch is electrically connected to the current output terminal group of the stimulation driving circuit. The controlled terminal of the high-voltage channel switch is electrically connected to the control terminal of the lower-level machine. Each channel output terminal group of the high-voltage channel switch is used to connect to an electrostimulation electrode. The stimulation driving circuit is configured to generate an electrostimulation signal according to the control signal. The high-voltage channel switch is configured to select a stimulation channel according to the control of the lower-level machine to output the electrostimulation signal to the electrostimulation electrode. The electrostimulation electrode is configured to output electrostimulation pulses to the user's skin.

[0011] Furthermore, the electromyography (EMG) acquisition module includes an EMG acquisition chip, the signal input terminal group of which is used to connect to the contact electrode, and the EMG acquisition chip is bidirectionally connected to the lower-level machine.

[0012] Furthermore, the electromyography (EMG) acquisition module includes a filtering circuit, the signal input terminal group of the filtering circuit is used to connect to the contact electrode, and the signal output terminal group of the filtering circuit is electrically connected to the signal input terminal group of the EMG acquisition chip.

[0013] Furthermore, the stimulation driving circuit includes a constant current source sub-circuit, a Wilson current mirror, and an H-bridge sub-circuit. The voltage input terminal of the constant current source sub-circuit serves as the voltage input terminal of the stimulation driving circuit. The current input terminal of the Wilson current mirror is electrically connected to the current output terminal of the constant current source sub-circuit. The current input terminal of the H-bridge sub-circuit is electrically connected to the current output terminal of the Wilson current mirror. The current output terminal group of the H-bridge circuit serves as the current output terminal group of the stimulation driving circuit.

[0014] Furthermore, it includes a communication module, through which the lower-level machine can communicate bidirectionally with the upper-level machine.

[0015] Furthermore, it includes a boost module, the voltage input terminal of which is used to connect to a power supply, and the voltage output terminal of which supplies power to the constant current source circuit, the Wilson current mirror, the H-bridge circuit and the high-voltage channel switch.

[0016] Furthermore, it includes a step-down power supply circuit, the voltage input terminal of which is used to connect to a power supply, and the voltage output terminal of which supplies power to the host computer and the electromyography acquisition chip.

[0017] Compared with the prior art, the technical solution of this application has the following beneficial technical effects: (1) In this invention, the lower-level computer collects surface electromyography (EMG) signals and uploads them to the upper-level computer. The upper-level computer maps the EMG signals into motion control commands to drive the robotic arm to perform actions. At the same time, it receives the status data of the robotic arm in real time and generates electrical stimulation parameters according to the electrical stimulation strategy. Finally, the tactile signals are fed back to the user through the electrical stimulation module. This allows the user to grasp the opening and closing degree, movement speed and grasping force of the robotic arm in real time by relying solely on tactile perception, and adjust their own muscle contraction accordingly to complete fine operations. This reduces the cognitive load during operation and improves the reliability of human-computer interaction.

[0018] (2) This invention maps the finger opening of the robotic hand to different stimulation channels through spatial position encoding, allowing users to judge the opening size by sensing the stimulation position; it linearly maps the movement speed to the stimulation pulse frequency through speed encoding, allowing users to grasp the movement speed by sensing the frequency; and it sets two modes, fine grasping and strong grasping, through pressure encoding. In fine grasping, the pulse width is adjusted at a fixed frequency to sense subtle force changes, while in strong grasping, the maximum pulse width is maintained and the frequency is adjusted to prompt the user to enter the strong grasping state. Through the joint encoding of space, frequency, and pulse width, the parallel and accurate transmission of multimodal state information such as position, speed, and force of the robotic hand is realized, enriching the connotation of feedback information and improving the clarity and accuracy of user perception. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a human-computer interaction method based on sEMG and multi-channel electrical stimulation tactile feedback provided in an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the operation of the electrical stimulation strategy in an embodiment of the present invention; Figure 3 This is a schematic diagram illustrating the spatial location encoding process in an embodiment of the present invention. Figure 4 This is a schematic diagram of the structure of a human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback provided in an embodiment of the present invention; Figure 5 This is a circuit diagram of the high-voltage channel switch in an embodiment of the present invention; Figure 6 This is a circuit diagram of the filter circuit in an embodiment of the present invention; Figure 7 This is a circuit diagram of the constant current source sub-power supply in an embodiment of the present invention; Figure 8 This is a circuit diagram of the Wilson current mirror in an embodiment of the present invention; Figure 9 This is a circuit diagram of the H-bridge circuit in an embodiment of the present invention; Figure 10 This is a circuit diagram of the electrical stimulation electrode interface in an embodiment of the present invention; Figure 11 This is a power supply circuit diagram for a human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback, provided in an embodiment of the present invention.

[0021] Explanation of reference numerals in the attached figures: 1. Electromyography (EMG) acquisition module; 11. EMG acquisition chip; 12. Filtering circuit; 2. Lower-level machine; 3. Host computer; 4. Electrical stimulation module; 41. Stimulation drive circuit; 411. Constant current source circuit; 412. Wilson current mirror; 413. H-bridge circuit; 42. High voltage channel switch; 5. Communication module; 6. Boost module; 7. Step-down power supply circuit. Detailed Implementation

[0022] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0024] It is understood that spatial relation terms such as "below," "under," "below," "below," "above," "above," etc., can be used here to describe the relationship between one element or feature shown in the figure and other elements or features. It should be understood that, in addition to the orientation shown in the figure, spatial relation terms also include different orientations of the device in use and operation. For example, if the device in the figure is flipped, the element or feature described as "below" or "below" of the other element or feature will be oriented "above" the other element or feature. Therefore, the exemplary terms "below" and "below" can include both upper and lower orientations. Furthermore, the device may also include other orientations (e.g., rotated 90 degrees or other orientations), and the spatial descriptive terms used herein will be interpreted accordingly.

[0025] When used herein, the singular forms of “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprising,” “including,” or “having,” etc., specify the presence of the stated feature, whole, step, operation, component, part, or combination thereof, but do not preclude the possibility of the presence or addition of one or more other features, wholes, steps, operations, components, parts, or combinations thereof.

[0026] Reference Figure 1 As shown, the present invention provides a technical solution: a human-computer interaction method based on sEMG and multi-channel electrical stimulation tactile feedback, comprising the following steps: S1 collects and processes the user's surface electromyography (EMG) signals to obtain EMG data.

[0027] Specifically, by attaching contact electrodes to key muscles such as the user's flexor and extensor fingers, surface electromyography signals generated during the user's actions are collected in real time.

[0028] S2 calculates the mean absolute value based on electromyography data, maps the mean absolute value to motion control commands for the robotic arm, and then sends the motion control commands to the robotic arm to control the robotic arm to perform corresponding actions.

[0029] Specifically, upon receiving electromyography (EMG) data, the mean absolute value (MAV) is calculated in real time using a sliding window method. The MAV effectively reflects the muscle contraction intensity. Calibration ensures that control commands can adapt to individual differences among users; calibration consists of two steps: first, the user is asked to relax their arm, the MAV during this period is accumulated, and the average value is calculated to obtain the baseline of the relaxed state; then, the user is asked to perform maximum voluntary contraction, and the maximum value of the MAV during this period is recorded as the contraction peak. After calibration, the host computer 3 normalizes the real-time calculated MAV to the [0, 1] interval using the formula: Normalized MAV = (Real-time MAV - Relaxation Baseline) / (Contraction Peak - Relaxation Baseline). Subsequently, the normalized MAV is linearly mapped to the motion control commands of the robotic arm (for example, mapping the [0, 1] interval to integers from 0 to 255, corresponding to the degree of the robotic arm's fingers from fully open to fully closed), and the commands are sent to the robotic arm via the TCP / IP protocol to drive the robotic arm to perform corresponding grasping or releasing actions. This process, through personalized calibration and normalized mapping, achieves precise and continuous proportional control from the user's motion intention to the robot's movements.

[0030] S3 receives the status data of the robotic hand in real time and generates electrical stimulation parameters based on the status data using an electrical stimulation strategy. The status data includes at least finger opening, movement speed, and contact pressure, and the electrical stimulation parameters include at least stimulation channel selection, current amplitude, pulse frequency, and pulse width.

[0031] S4 generates control signals based on electrical stimulation parameters; S5 generates and outputs electrical stimulation signals to the electrical stimulation electrodes based on the control signals to provide tactile feedback to the user.

[0032] In this embodiment, a closed-loop human-computer interaction method is formed by repeating steps S1 to S5. After receiving tactile feedback, the user can consciously adjust the intensity of their muscle contraction based on the perceived finger opening, speed, and pressure information, thereby changing the surface electromyographic signal and achieving secondary fine control of the robotic hand. This improves the intuitiveness and accuracy of the operation and reduces reliance on vision.

[0033] Reference Figures 2 to 3 As shown, in some embodiments, the electrical stimulation strategy includes: Spatial location coding is used to select different stimulation channels for electrical stimulation pulse output based on the degree of finger opening.

[0034] Velocity encoding is used to linearly adjust the pulse frequency output by the selected stimulation channel according to the magnitude of the motion speed.

[0035] For example, the faster the robotic hand's fingers close, the higher the frequency of the electrical stimulation pulses; conversely, the slower the pulses, the lower the frequency. By sensing the frequency of the electrical stimulation pulses, users can perceive the speed of the robotic hand's movement in real time.

[0036] Pressure coding is used to adjust the pulse frequency or pulse width according to the magnitude of the contact pressure.

[0037] Reference Figures 2 to 3 As shown, in some embodiments, the pressure encoding further includes: When the contact pressure is lower than the contact pressure threshold, the pulse frequency is fixed and the pulse width is adjusted according to the magnitude of the contact pressure to achieve precise gripping feedback. When the contact pressure is higher than the contact pressure threshold, the maximum pulse width is maintained, and the pulse frequency is adjusted according to the magnitude of the contact pressure to achieve feedback for strong gripping.

[0038] Pressure coding is designed as a dual-mode adaptive coding to adapt to the force feedback requirements of different grasping scenarios.

[0039] Specifically, the contact pressure threshold is used to distinguish between two modes: fine gripping and strong gripping.

[0040] In the precision gripping mode, when the contact pressure is below the contact pressure threshold, the frequency of the electrical stimulation pulses is fixed, and the pulse width is linearly adjusted only according to the magnitude of the contact pressure. The greater the contact pressure, the wider the pulse width. Because the human body is highly sensitive to changes in pulse width, this method allows users to precisely perceive subtle changes in gripping force, thereby achieving a gentle and stable grip on fragile objects.

[0041] In the strong grip mode, when the contact pressure exceeds the contact pressure threshold, the maximum pulse width is maintained, and the frequency of the electrical stimulation pulses is linearly adjusted according to the magnitude of the contact pressure. The greater the contact pressure, the higher the frequency of the electrical stimulation pulses. This method alerts the user that a strong grip has been entered, preventing damage to the object or user fatigue due to excessive force, while ensuring the reliability of the grip.

[0042] The dual-mode pressure coding described above can adaptively select the optimal coding dimension for feedback based on the magnitude of the gripping force, enabling users to obtain clear and accurate force perception throughout the entire range.

[0043] Reference Figures 4 to 5 As shown, this invention provides a technical solution: a human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback, used to implement the above-mentioned method, including an electromyography (EMG) acquisition module 1, a lower-level machine 2, a higher-level machine 3, and an electrical stimulation module 4; the EMG acquisition module 1 is configured to acquire the user's surface EMG signals; the lower-level machine 2 is bidirectionally connected to the EMG acquisition module 1, and is configured to receive and send surface EMG signals, process the surface EMG signals to obtain EMG data, and generate control signals according to electrical stimulation parameters; the higher-level machine 3 is bidirectionally connected to the lower-level machine 2, and is used for bidirectional communication with a robotic arm, and is configured to receive the EMG data uploaded by the lower-level machine 2 and calculate the average absolute value, map the average absolute value to the motion control commands of the robotic arm, and then send the motion control commands to the robotic arm. The system receives real-time status data from the robotic arm, generates electrical stimulation parameters based on the status data using an electrical stimulation strategy, and sends them to the lower-level machine 2. The electrical stimulation module 4 includes a stimulation drive circuit 41 and a high-voltage channel switch 42. The voltage input terminal of the stimulation drive circuit 41 is electrically connected to the voltage output terminal of the lower-level machine 2. The common input terminal group of the high-voltage channel switch 42 is electrically connected to the current output terminal group of the stimulation drive circuit 41. The controlled terminal of the high-voltage channel switch 42 is electrically connected to the control terminal of the lower-level machine 2. Each channel output terminal group of the high-voltage channel switch 42 is used to connect to the electrical stimulation electrode. The stimulation drive circuit 41 is configured to generate an electrical stimulation signal according to the control signal. The high-voltage channel switch 42 is configured to select the stimulation channel according to the control of the lower-level machine 2 to output an electrical stimulation signal to the electrical stimulation electrode. The electrical stimulation electrode is configured to output electrical stimulation pulses to the user's skin.

[0044] For example, the high-voltage channel switch 42 can be set to three stimulation channels corresponding to large, medium, and small opening ranges, respectively. When the robotic hand fingers open a large distance, channel 1 is selected; when the opening distance is medium, channel 2 is selected; and when the opening distance is small, channel 3 is selected. This invention uses four stimulation channels, see reference. Figure 10 As shown, the electrical stimulation module 4 includes four electrical stimulation electrode interfaces, and the high-voltage channel switch 42 has at least four channel output terminal groups. The current input terminal groups of the electrical stimulation electrode interfaces are electrically connected one-to-one with the channel output terminal groups of the high-voltage channel switch 42. Thus, the user can intuitively determine the current opening state of the robotic arm by sensing the body part where the stimulation occurs (i.e., the activated electrode position). The host computer 3 can be a computer, etc. The slave computer 2 can be a microcontroller such as an STM32F103RCT6. The host computer 3 and the robotic arm can communicate via TCP / IP protocol. The high-voltage channel switch 42 can be a MAX14803, etc.

[0045] In this embodiment, the electromyography (EMG) data read by the lower-level computer 2 is packaged and sent to the upper-level computer 3. The upper-level computer 3 calculates the average absolute value, generates control commands for the robotic arm, and sends them to the robotic arm via TCP protocol. The robotic arm executes the actions and transmits its status data back to the upper-level computer 3 via TCP. The upper-level computer 3 generates electrical stimulation parameters based on the status data and sends them to the lower-level computer 2. After parsing the commands, the lower-level computer 2 controls the stimulation drive circuit 41 to generate constant current pulses and selects the corresponding channel through the high-voltage channel switch 42, finally applying electrical stimulation to the user through electrodes. This forms a complete closed-loop interaction.

[0046] Reference Figure 4 and Figure 6 As shown, in some embodiments, the electromyography (EMG) acquisition module 1 includes an EMG acquisition chip 11, the signal input terminal group of the EMG acquisition chip 11 is used to connect to the contact electrode, and the EMG acquisition chip 11 is bidirectionally connected to the lower-level machine 2.

[0047] For example, the electromyography (EMG) acquisition chip 11 can be an ADS1298 or similar model. The EMG acquisition chip 11 communicates with the lower-level computer 2 via SPI protocol or similar means.

[0048] In this embodiment, the electromyography (EMG) acquisition chip 11 can simultaneously sample multiple surface EMG signals and output the acquired surface EMG signals after digitization via the SPI interface.

[0049] In some embodiments, the electromyography (EMG) acquisition module 1 includes a filter circuit 12, the signal input terminal group of the filter circuit 12 is used to connect to the contact electrode, and the signal output terminal group of the filter circuit 12 is electrically connected to the signal input terminal group of the EMG acquisition chip 11.

[0050] For example, the filter circuit 12 can be a second-order RC low-pass filter.

[0051] In this embodiment, the filter circuit 12 can effectively filter out high-frequency interference, retain effective surface electromyography signals, and reduce the processing pressure of subsequent stages.

[0052] Reference Figure 4 and Figures 7 to 9 As shown, in some embodiments, the stimulation driving circuit 41 includes a constant current source circuit 411, a Wilson current mirror 412, and an H-bridge circuit 413. The voltage input terminal of the constant current source circuit 411 serves as the voltage input terminal of the stimulation driving circuit 41. The current input terminal of the Wilson current mirror 412 is electrically connected to the current output terminal of the constant current source circuit 411. The current input terminal of the H-bridge circuit 413 is electrically connected to the current output terminal of the Wilson current mirror 412. The current output terminal group of the H-bridge circuit 413 serves as the current output terminal group of the stimulation driving circuit 41.

[0053] In this embodiment, the constant current source sub-circuit 411 receives a control signal from the lower-level machine 2 to generate a precise and stable reference current. The Wilson current mirror 412 accurately replicates and mirrors the reference current output by the constant current source to improve the stability and accuracy of the current output and reduce the impact of temperature drift. The H-bridge sub-circuit 413, according to the control of the lower-level machine 2, converts the DC current into an electrical stimulation pulse current (i.e., an electrical stimulation pulse) to meet the requirements of electrical stimulation safety and effectiveness.

[0054] Reference Figure 4 As shown, in some embodiments, the human-computer interaction system includes a communication module 5, and the lower-level machine 2 is bidirectionally connected to the upper-level machine 3 through the communication module 5.

[0055] For example, the communication module 5 can be a Bluetooth module or a WiFi module, etc. The model of the Bluetooth module can be JDY-33 or MS-DB021A, etc.

[0056] Reference Figure 11 As shown, in some embodiments, the human-computer interaction system includes a boost module 6, the voltage input terminal of which is used to connect to a power supply, and the voltage output terminal of the boost module 6 supplies power to the constant current source circuit 411, the Wilson current mirror 412, the H-bridge circuit 413 and the high-voltage channel switch 42.

[0057] In this embodiment, the boost module 6 supplies power (e.g., 100V) to the constant current source circuit 411, Wilson current mirror 412, H-bridge circuit 413 and high-voltage channel switch 42 to meet the high voltage requirements of electrical stimulation.

[0058] Reference Figure 11As shown, in some embodiments, the human-computer interaction system includes a step-down power supply circuit 7, the voltage input terminal of which is used to connect to a power supply, and the voltage output terminal of which supplies power to the host computer 3 and the electromyography acquisition chip 11.

[0059] In this embodiment, the step-down power supply circuit 7 supplies power to the lower-level computer 2 (e.g., 5V, 3.3V) and the electromyography acquisition chip 11 (e.g., 2.5V, -2.5V), as well as other low-voltage digital circuits.

[0060] The aforementioned end group includes at least one positive end and one negative end.

[0061] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A human-computer interaction method based on sEMG and multi-channel electrical stimulation tactile feedback, characterized in that, include: The user's surface electromyography (EMG) signals are collected and processed to obtain EMG data; The average absolute value is calculated based on the electromyography data, the average absolute value is mapped to the motion control command of the robotic arm, and the motion control command is sent to the robotic arm to control the robotic arm to perform the corresponding action. The system receives real-time status data of the robotic hand and generates electrical stimulation parameters based on the status data using an electrical stimulation strategy. The status data includes at least finger spread, movement speed, and contact pressure, and the electrical stimulation parameters include at least stimulation channel selection, current amplitude, pulse frequency, and pulse width. A control signal is generated based on the electrical stimulation parameters; The control signal generates and outputs an electrical stimulation signal to the electrical stimulation electrode to provide tactile feedback to the user.

2. The human-computer interaction method based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 1, characterized in that, The electrical stimulation strategy includes: Spatial position encoding is used to select different stimulation channels to output the electrical stimulation pulses according to the degree of finger opening; Velocity encoding is used to linearly adjust the pulse frequency output by the selected stimulation channel according to the magnitude of the motion velocity. Pressure coding is used to adjust the pulse frequency or pulse width according to the magnitude of the contact pressure.

3. The human-computer interaction method based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 2, characterized in that, The pressure encoding further includes: When the contact pressure is lower than the contact pressure threshold, the pulse frequency is fixed and the pulse width is adjusted according to the magnitude of the contact pressure to achieve feedback for precise grasping. When the contact pressure is higher than the contact pressure threshold, the maximum pulse width is maintained, and the pulse frequency is adjusted according to the magnitude of the contact pressure to achieve feedback for strong gripping.

4. A human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback, used to implement the method described in any one of claims 1 to 3, characterized in that, include: Electromyography (EMG) acquisition module (1) is configured to acquire and process the user's surface EMG signals to obtain EMG data; The lower-level machine (2) is bidirectionally connected to the electromyography acquisition module (1). The lower-level machine (2) is configured to receive and send the electromyography data, and generate control signals according to the electrical stimulation parameters. The host computer (3) is bidirectionally connected to the lower computer (2). The host computer (3) is used to bidirectionally communicate with the robotic arm. The host computer (3) is configured to receive the electromyographic data uploaded by the lower computer (2) and calculate the average absolute value, map the average absolute value to the motion control command of the robotic arm, and then send the motion control command to the robotic arm. It also receives the status data of the robotic arm in real time, generates the electrical stimulation parameters according to the status data using an electrical stimulation strategy, and sends them to the lower computer (2). The electrostimulation module (4) includes a stimulation driving circuit (41) and a high-voltage channel switch (42). The voltage input terminal of the stimulation driving circuit (41) is electrically connected to the voltage output terminal of the lower-level machine (2). The common input terminal group of the high-voltage channel switch (42) is electrically connected to the current output terminal group of the stimulation driving circuit (41). The controlled terminal of the high-voltage channel switch (42) is electrically connected to the control terminal of the lower-level machine (2). Each channel output terminal group of the high-voltage channel switch (42) is used to connect to the electrostimulation electrode. The stimulation driving circuit (41) is configured to generate an electrostimulation signal according to the control signal. The high-voltage channel switch (42) is configured to select the stimulation channel according to the control of the lower-level machine (2) to output the electrostimulation signal to the electrostimulation electrode. The electrostimulation electrode is configured to output the electrostimulation pulse to the user's skin.

5. The human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 4, characterized in that, The electromyography (EMG) acquisition module (1) includes an EMG acquisition chip (11), the signal input terminal group of the EMG acquisition chip (11) is used to connect to the contact electrode, and the EMG acquisition chip (11) is bidirectionally connected to the lower computer (2).

6. The human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 5, characterized in that, The electromyography acquisition module (1) includes a filter circuit (12), the signal input terminal group of the filter circuit (12) is used to connect to the contact electrode, and the signal output terminal group of the filter circuit (12) is electrically connected to the signal input terminal group of the electromyography acquisition chip (11).

7. The human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 5, characterized in that, The stimulation driving circuit (41) includes a constant current source circuit (411), a Wilson current mirror (412), and an H-bridge circuit (413). The voltage input terminal of the constant current source circuit (411) serves as the voltage input terminal of the stimulation driving circuit (41). The current input terminal of the Wilson current mirror (412) is electrically connected to the current output terminal of the constant current source circuit (411). The current input terminal of the H-bridge circuit (413) is electrically connected to the current output terminal of the Wilson current mirror (412). The current output terminal group of the H-bridge circuit (413) serves as the current output terminal group of the stimulation driving circuit (41).

8. The human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 5, characterized in that, Includes a communication module (5), through which the lower-level machine (2) is bidirectionally connected to the upper-level machine (3).

9. The human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 7, characterized in that, It includes a boost module (6), the voltage input terminal of which is used to connect to a power supply, and the voltage output terminal of the boost module (6) supplies power to the constant current source circuit (411), the Wilson current mirror (412), the H-bridge circuit (413) and the high voltage channel switch (42).

10. The human-computer interaction system based on sEMG and multi-channel electrical stimulation tactile feedback according to claim 7, characterized in that, It includes a step-down power supply circuit (7), the voltage input terminal of which is used to connect to a power supply, and the voltage output terminal of which supplies power to the host computer (3) and the electromyography acquisition chip (11).

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