A prosthesis closed-loop control system and feedback method based on vibration coding feedback

Abstract

This invention discloses a closed-loop control system and feedback method for prostheses based on vibration-encoded feedback. The system includes a prosthetic hand with grip force sensing capability, an electromyography (EMG) sensor module, a wearable vibration feedback device, and a data processor. The prosthetic hand includes a force sensor, worn through a prosthetic socket on the user's residual limb for force and tactile sensing. The EMG sensor module is integrated into the inner surface of the prosthetic socket where it fits against the residual limb. The wearable vibration feedback device consists of four vibration motors evenly distributed on the anterior, posterior, lateral, and medial sides of the upper arm. The data processor is integrated within the prosthetic socket for decoding the user's EMG intent, controlling the prosthetic hand, controlling the vibration feedback device, and executing key programs within the system. The user obtains their current grip force level based on the vibration location and number of vibration sources perceived through their skin, dynamically adjusting their muscle contractions to adjust the grip force, achieving closed-loop adjustment through human-computer interaction. This invention realizes closed-loop control of the prosthesis, effectively improving the grip force perception ability of people with disabilities.

Description

Technical Field

[0001] This invention relates to the field of prosthesis and human-computer interaction technology, and in particular to a closed-loop control system and feedback method for prostheses based on vibration coding feedback. Background Technology

[0002] Touch is an essential sensory system for humans to perceive the external environment and interact physically with it. For upper limb amputees, the loss of the limb not only leads to the loss of motor function but also means the severance of the tactile perception pathway. Currently, amputees mainly rely on commercial myoelectric prostheses to rebuild basic motor functions such as grasping. However, most mainstream prosthetic products only provide basic motor functions and generally lack effective feedback reconstruction of force and tactile perception when the prosthesis interacts with the environment.

[0003] Due to the lack of tactile feedback, most amputees must rely heavily on their visual senses to compensate when using their prostheses to grasp objects, in order to confirm the contact state and grasping force between the prosthesis and the object. However, when vision is obstructed or other visual tasks need to be performed simultaneously, patients cannot accurately perceive the force state during the interaction between the prosthetic hand and the object, making it easy for them to break fragile items or drop objects due to insufficient grip strength. This significantly reduces the practicality of the prosthesis and the patient's ability to live independently. Therefore, designing a feedback device that allows amputees to quickly and accurately perceive grasping force and achieve stable closed-loop control of the prosthesis has become an urgent problem to be solved. Summary of the Invention

[0004] The purpose of this invention is to provide a closed-loop control system and feedback method for prostheses based on vibration coding feedback. This system converts the gripping force signal into different activation modes of multiple vibration motors, intuitively conveying the gripping force level to the prosthesis user. This helps improve the ability of disabled people to perceive the object being grasped and lays the foundation for achieving fine operation of the prosthesis.

[0005] The above objectives are achieved through the following technical solutions:

[0006] A closed-loop control system for prostheses based on vibration-encoded feedback is disclosed. The system includes a prosthetic hand with grip force sensing capability, an electromyography (EMG) sensor module, a wearable vibration feedback device, and a data processor. The prosthetic hand with grip force sensing capability is used for force and tactile perception. This prosthetic hand is worn on the user's residual limb through a prosthetic socket. The EMG sensor module is integrated into the inner surface of the prosthetic socket where it fits against the residual limb. The wearable vibration feedback device is used to enable the user to perceive force and tactile information. The data processor is used for decoding the user's EMG intent, controlling the prosthetic hand, controlling the vibration feedback device, and executing key programs within the system.

[0007] The aforementioned closed-loop control system for a prosthesis based on vibration coding feedback includes a force sensor in the prosthetic hand with grip force sensing capability, and a signal acquisition board is provided on the prosthetic hand for connecting the data line of the force sensor.

[0008] The aforementioned closed-loop control system for a prosthesis based on vibration coding feedback includes a wearable vibration feedback device comprising a vibration unit array for the wearer to perceive vibration. The vibration unit array consists of four vibration motors that surround the upper arm and are evenly distributed on the front, back, outer, and inner sides of the upper arm.

[0009] The aforementioned closed-loop control system for a prosthesis based on vibration-coded feedback includes a vibration coding strategy for the wearable vibration feedback device as follows: Based on the range of the force sensor, the acquired continuous gripping force data is divided into five discrete force levels—Level 1, Level 2, Level 3, Level 4, and Level 5—from low to high. Different discrete force levels are mapped to specific activation states of four vibration motors. When the gripping force data is at Level 1, only the right vibration motor is activated; when the gripping force data is at Level 2, only the lower vibration motor is activated; when the gripping force data is at Level 3, only the left vibration motor is activated; when the gripping force data is at Level 4, only the upper vibration motor is activated; and when the gripping force data is at Level 5, all four vibration motors—upper, lower, left, and right—are activated simultaneously.

[0010] A closed-loop feedback method for prostheses based on vibration-coded feedback, the method comprising the following steps:

[0011] S1. First, the user makes a grasping intention. The electromyography (EMG) sensor module reads the EMG signals on the surface of the residual limb in real time. Then, the data processor decodes the EMG signals and outputs speed control commands, thereby driving the prosthetic hand end effector to grasp the target object.

[0012] S2. During the process of the prosthetic hand grasping an object, the force sensor captures the grasping force data of the contact surface in real time. Then, the data processor converts the grasping force data into a combination activation command of four directional vibration motors according to the preset vibration coding strategy, and transmits the control signal to the wearable vibration feedback device.

[0013] S3. The wearable vibration feedback device generates corresponding vibration stimulation at different positions on the front, back, left, and right of the user's arm. The user can intuitively obtain the actual grip strength level of the current prosthetic hand by sensing the vibration direction and the number of vibration sources through the skin. S4. Based on the perceived current grip strength feedback, the user dynamically adjusts the intensity of their own muscle contraction to correct the input electromyographic signal. By adjusting the opening and closing of the prosthetic hand, the user adjusts the magnitude of the grip strength, realizing closed-loop regulation of human-computer interaction. If the task is not completed, the user returns to step S1 in real time.

[0014] In the closed-loop feedback method for prostheses, the specific process of step S1 is as follows:

[0015] S11. The electromyography (EMG) sensing module acquires raw EMG signals from the surface muscle groups of the user's residual limb in real time at a sampling frequency of 200Hz. The data processor calculates the root mean square value of the raw EMG signal using a sliding window with a length of 200ms and an overlap rate of 80%, and extracts the EMG envelope. Subsequently, a second-order Butterworth low-pass filter with a cutoff frequency of 2.5Hz is used to smooth and filter the envelope signal to remove high-frequency interference and obtain smooth EMG characteristic signals.

[0016] S12. The data processor normalizes the smoothed electromyographic feature signal, specifically by normalizing it to the set ratio of the user's maximum voluntary muscle contraction, in order to prevent the user from experiencing muscle fatigue due to excessive muscle contraction required to the extreme. At the same time, the data processor has a fixed action dead zone threshold set to filter out unconscious electromyographic fluctuations or environmental baseline noise below the threshold, so as to avoid the prosthetic hand from producing unexpected erroneous movements.

[0017] S13. The data processor uses a proportional speed control strategy to perform closed-loop motion control on the prosthetic hand; when the normalized electromyography intensity in step S12 exceeds the set motion dead zone threshold, the data processor establishes a linear mapping relationship between the electromyography intensity and the driving speed of the prosthetic hand end effector, and calculates the desired motion speed; the data processor combines the user's muscle contraction pattern (such as flexor contraction corresponding to closure, extensor contraction corresponding to opening) to generate speed control commands, thereby driving the prosthetic hand end effector to accurately grasp the target object.

[0018] The specific process of step S3 is as follows:

[0019] S31. The force sensor on the prosthetic hand end effector monitors the contact force data between the prosthetic hand and the target object in real time and transmits the data to the data processor. The data processor discretizes the continuously changing gripping force data according to the effective range of the sensor and divides it into five discrete force levels from low to high: Level 1, Level 2, Level 3, Level 4, and Level 5.

[0020] S32. The data processor, based on the current discrete force level, calls the preset vibration coding strategy to generate the corresponding vibration drive command; from the first level to the fourth level, the data processor sequentially generates commands to activate only the right vibration motor, the lower vibration motor, the left vibration motor, or the upper vibration motor respectively; after receiving the command, the wearable vibration feedback device generates vibration stimulation in a single specific direction.

[0021] S33. When the gripping force data increases to level 5, the data processor generates an instruction to simultaneously activate four vibration motors: front, back, left, and right. After receiving this instruction, the wearable vibration feedback device uses a significantly increased number of vibration sources and stronger tactile stimulation to convey to the user that the gripping force is greater at this time.

[0022] Compared with the prior art, the advantages of the present invention are as follows:

[0023] 1. Reconstructing tactile sensory pathways and reducing visual dependence. This invention addresses the common problem in current mainstream commercial myoelectric prostheses of lacking feedback reconstruction of force-tactile perception during prosthesis-environment interaction, enabling amputees to quickly and accurately perceive gripping force when controlling their prostheses to grasp objects, thus reconstructing the missing force-tactile sensory pathways.

[0024] 2. The vibration coding strategy is intuitive and effectively reduces cognitive load. This invention makes full use of the high recognition of the human skin for tactile stimulation locations, converting continuous gripping force signals into activation modes of vibration motors in different directions (front, back, left, and right). This allows users to intuitively and accurately know the actual gripping force level of the prosthetic hand simply by sensing the spatial location and number of vibration sources through their skin.

[0025] 3. Stable and reliable human-machine closed-loop control. This invention constructs a human-machine closed-loop control mechanism, which allows the user to compare the current gripping force perceived by the skin with the target gripping force, spontaneously adjust the intensity of their own muscle contraction to correct the electromyographic control input, and adjust the magnitude of the gripping force by adjusting the opening and closing of the prosthetic hand, thereby achieving stable and reliable closed-loop control of the gripping force. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the closed-loop prosthesis system of the present invention;

[0027] Figure 2 This is a schematic diagram of a wearable vibration feedback device;

[0028] Figure 3 This is a diagram of the vibration coding strategy;

[0029] Figure 4 This is a block diagram of the closed-loop prosthetic system of the present invention;

[0030] Figure 5 This is a system flowchart of the present invention. Detailed Implementation

[0031] To enhance understanding of the present invention, the embodiments will be described in detail below with reference to the accompanying drawings.

[0032] Example 1: As Figure 1As shown, the present invention discloses a closed-loop control system for prostheses based on vibration-encoded feedback, comprising a prosthetic hand 1 with force and tactile sensing capabilities, an electromyography (EMG) sensing module 2, a wearable vibration feedback device 3, and a data processor 4. The prosthetic hand 1 with grasping force sensing capabilities is worn on the user's residual limb through a prosthetic socket. The EMG sensing module 2 is integrated into the inner surface of the prosthetic socket that fits against the residual limb, and the data processor 4 is integrated within the prosthetic socket. The wearable vibration feedback device 3 enables the user to perceive force and tactile information from the prosthesis. The data processor is used for decoding the user's EMG intent, controlling the prosthetic hand, controlling the vibration feedback device, and executing key programs within the system. This system assists amputees in perceiving force information during the interaction between the prosthesis and the environment, thereby constructing a human-machine closed-loop control loop to improve the prosthesis's grasping ability and stability.

[0033] like Figure 2 As shown, the wearable vibration feedback device of this invention uses a vibration unit array 5 to allow the wearer to perceive vibrations. The vibration unit array consists of four vibration motors that encircle the upper arm, evenly distributed on the front, back, outer, and inner sides of the upper arm. The wearable vibration feedback device has a ring-shaped structure with adjustable fasteners at both ends to accommodate different user arm sizes and provide appropriate pre-tightening force to ensure a close fit between the internal vibration unit array and the user's skin. The vibration unit array consists of four independent vibration motors arranged in a cross-shaped array within the device. When the user wears the device, these four vibration motors are evenly distributed on the front, back, outer, and inner sides of the arm, respectively defined in this embodiment as the upper vibration motor, lower vibration motor, left vibration motor, and right vibration motor. The data processor 4 is connected and communicates with each of the four vibration motors and independently controls the start and stop states of each motor. This device, through the cross-shaped spatial arrangement of the four vibration motors, utilizes the high recognition of tactile stimulation locations by human skin, providing a hardware foundation for implementing vibration coding strategies.

[0034] like Figure 3As shown in the diagram, the vibration coding strategy of this invention details the mapping logic between the grip strength level of the prosthetic hand and the activation state of each vibration motor in the vibration feedback device. The data processor receives grip strength data from the force sensor at the end of the prosthetic hand. Based on the effective range of the force sensor, the data processor divides the continuous pressure signal into five discrete force levels—level one, level two, level three, level four, and level five—in increments from low to high. After acquiring the current force level, the data processor generates control commands to drive the four vibration motors arranged in a cross shape. At levels one through four, the system uses a single vibration mode. Specifically, when the pressure is at level one, the feedback command only activates the right vibration motor; when the pressure rises to level two, only the lower vibration motor is activated; at level three, only the left vibration motor is activated; and at level four, only the upper vibration motor is activated. When the pressure reaches level five, the data processor simultaneously activates all four vibration motors—upper, lower, left, and right. By changing the position of the vibration source on the user's upper arm, the user can determine the current grip strength level simply by the vibration direction and the number of vibration sources.

[0035] The block diagram of a prosthetic closed-loop control system module based on vibration coding feedback described in this invention is as follows: Figure 4 As shown, this system reconstructs the force-tactile sensory pathways lost in amputees, reshaping the closed-loop interaction between the user and the external environment. The user engages in real-time, two-way interaction with the control system: on one hand, the system reads and decodes electromyographic signals from the surface of the residual limb in real time through an electromyographic sensing module, translating the user's grasping intentions into driving commands for the prosthetic hand's end effector; on the other hand, the system acquires real-time contact force information during the interaction between the prosthetic hand and the target object through a force sensor integrated into the prosthetic hand's end effector. This continuous grasping force information is processed by a vibration encoding strategy of the data processor and transformed into control commands for a wearable vibration feedback device, ultimately conveyed to the user in the form of intuitive vibration stimulation. When the user feels vibration feedback in a specific location or a specific number of locations on the upper arm, they can immediately and intuitively understand the actual grasping force level of the prosthetic hand and the force interaction state between the prosthetic limb and the object. At this point, the user can spontaneously and dynamically adjust their muscle contraction intensity to correct the electromyographic input based on the difference between the perceived gripping force feedback and the expected target task. Throughout the entire process of dynamically grasping and holding an object, the force sensing module at the end of the prosthetic hand and the wearable vibration feedback device continue to provide the user with information on changes in contact force in real time, enabling the user to correct output deviations in a timely manner and to conduct continuous, stable and reliable closed-loop force control interaction with the external environment.

[0036] The flowchart of the prosthetic closed-loop feedback system described in this invention is as follows: Figure 5As shown. First, the user intends to grasp the target object, and the muscles of the residual limb contract accordingly, generating corresponding surface electromyographic (EMG) signals. Then, the system collects these signals in real time through the EMG sensor module, decodes them through a data processor, and maps them into motion commands, thereby driving the prosthetic hand end effector to perform a physical grasp of the target object. During the contact between the prosthetic hand and the object, the system acquires the grasping force data of the contact surface in real time through a force sensor, and converts this data into activation commands for a specific location according to a vibration coding strategy. These commands are then applied to the user's upper arm via a wearable vibration feedback device. The user can intuitively understand the current actual grasping force level based on the perceived vibration location and the number of vibration sources, and dynamically adjust their muscle contraction intensity accordingly to correct the initial EMG control input, thus completing the closed-loop force regulation process of human-computer interaction. The specific method includes the following steps:

[0037] S1. First, the user makes a grasping intention. The electromyography (EMG) sensor module reads the EMG signals on the surface of the residual limb in real time. Then, the data processor decodes the EMG signals and outputs speed control commands, thereby driving the prosthetic hand end effector to grasp the target object.

[0038] S2. During the process of the prosthetic hand grasping an object, the force sensor captures the grasping force data of the contact surface in real time. Then, the data processor converts the grasping force data into a combination activation command of four directional vibration motors according to the preset vibration coding strategy, and transmits the control signal to the wearable vibration feedback device.

[0039] S3. The wearable vibration feedback device generates corresponding vibration stimulation at different positions on the front, back, left, and right of the user's arm. The user can intuitively obtain the actual grip strength level of the current prosthetic hand by sensing the vibration direction and the number of vibration sources through the skin. S4. Based on the perceived current grip strength feedback, the user dynamically adjusts the intensity of their own muscle contraction to correct the input electromyographic signal. By adjusting the opening and closing of the prosthetic hand, the user adjusts the magnitude of the grip strength, realizing closed-loop regulation of human-computer interaction. If the task is not completed, the user returns to step S1 in real time.

[0040] The specific process of step S1 in the aforementioned prosthetic closed-loop feedback method is as follows:

[0041] S11. The electromyography (EMG) sensing module acquires raw EMG signals from the surface muscle groups of the user's residual limb in real time at a sampling frequency of 200Hz. The data processor calculates the root mean square value of the raw EMG signal using a sliding window with a length of 200ms and an overlap rate of 80%, and extracts the EMG envelope. Subsequently, a second-order Butterworth low-pass filter with a cutoff frequency of 2.5Hz is used to smooth and filter the envelope signal to remove high-frequency interference and obtain smooth EMG characteristic signals.

[0042] S12. The data processor normalizes the smoothed electromyographic feature signal, specifically by normalizing it to the set ratio of the user's maximum voluntary muscle contraction, in order to prevent the user from experiencing muscle fatigue due to excessive muscle contraction required to the extreme. At the same time, the data processor has a fixed action dead zone threshold set to filter out unconscious electromyographic fluctuations or environmental baseline noise below the threshold, so as to avoid the prosthetic hand from producing unexpected erroneous movements.

[0043] S13. The data processor uses a proportional speed control strategy to perform closed-loop motion control on the prosthetic hand; when the normalized electromyography intensity in step S12 exceeds the set motion dead zone threshold, the data processor establishes a linear mapping relationship between the electromyography intensity and the driving speed of the prosthetic hand end effector, and calculates the desired motion speed; the data processor combines the user's muscle contraction pattern (such as flexor contraction corresponding to closure, extensor contraction corresponding to opening) to generate speed control commands, thereby driving the prosthetic hand end effector to accurately grasp the target object.

[0044] The specific process of step S3 in the aforementioned prosthetic closed-loop feedback method is as follows:

[0045] S31. The force sensor on the prosthetic hand end effector monitors the contact force data between the prosthetic hand and the target object in real time and transmits the data to the data processor. The data processor discretizes the continuously changing gripping force data according to the effective range of the sensor and divides it into five discrete force levels from low to high: Level 1, Level 2, Level 3, Level 4, and Level 5.

[0046] S32. The data processor, based on the current discrete force level, calls the preset vibration coding strategy to generate the corresponding vibration drive command; from the first level to the fourth level, the data processor sequentially generates commands to activate only the right vibration motor, the lower vibration motor, the left vibration motor, or the upper vibration motor respectively; after receiving the command, the wearable vibration feedback device generates vibration stimulation in a single specific direction.

[0047] S33. When the gripping force data increases to level 5, the data processor generates an instruction to simultaneously activate four vibration motors: front, back, left, and right. After receiving this instruction, the wearable vibration feedback device uses a significantly increased number of vibration sources and stronger tactile stimulation to convey to the user that the gripping force is greater at this time.

[0048] It should be noted that the above embodiments are not intended to limit the scope of protection of the present invention. Equivalent transformations or substitutions made based on the above technical solutions all fall within the scope of protection of the claims of the present invention.

Claims

1. A closed-loop control system for a prosthesis based on vibration-coded feedback, characterized in that, The system includes a prosthetic hand with grip force sensing capability, an electromyography (EMG) sensor module, a wearable vibration feedback device, and a data processor. The prosthetic hand with grip force sensing capability is used for force and tactile perception. The prosthetic hand is worn on the user's residual limb through a prosthetic socket. The EMG sensor module is integrated into the inner surface of the prosthetic socket that fits against the residual limb. The wearable vibration feedback device is used to enable the user to perceive force and tactile information. The data processor is used for decoding the user's EMG intent, controlling the prosthetic hand, controlling the vibration feedback device, and executing key programs within the system.

2. The prosthetic closed-loop control system based on vibration coding feedback according to claim 1, characterized in that, The prosthetic hand with grip force sensing capability includes a force sensor, and a signal acquisition board is installed on the prosthetic hand for connecting the data cable of the force sensor.

3. The prosthetic closed-loop control system based on vibration coding feedback according to claim 2, characterized in that, The wearable vibration feedback device includes a vibration unit array for the wearer to perceive vibration. The vibration unit array consists of four vibration motors that surround the upper arm and are evenly distributed on the front, back, outer and inner sides of the upper arm.

4. The prosthetic closed-loop control system based on vibration coding feedback according to claim 3, characterized in that, The vibration coding strategy of the wearable vibration feedback device is as follows: based on the range of the force sensor, the acquired continuous gripping force data is divided into five discrete force levels from low to high: the first level, the second level, the third level, the fourth level, and the fifth level; different discrete force levels are mapped to specific activation states of four vibration motors; when the gripping force data is at the first level, only the right vibration motor is activated. When the grip strength data is at level two, only the lower vibration motor is activated; When the grip strength data is at level three, only the left vibration motor is activated; When the grip strength data is at level four, only the upper vibration motor is activated; When the grip strength data is at level 5, the upper vibration motor, lower vibration motor, left vibration motor, and right vibration motor are activated simultaneously.

5. A closed-loop feedback method for prostheses based on vibration-coded feedback, characterized in that, The method of using the vibration-encoded feedback-based prosthetic closed-loop control system according to any one of claims 1-4 includes the following steps: S1. First, the user makes a grasping intention. The electromyography (EMG) sensor module reads the EMG signals on the surface of the residual limb in real time. Then, the data processor decodes the EMG signals and outputs speed control commands, thereby driving the prosthetic hand end effector to grasp the target object. S2. During the process of the prosthetic hand grasping an object, the force sensor captures the grasping force data of the contact surface in real time. Then, the data processor converts the grasping force data into a combination activation command of four directional vibration motors according to the preset vibration coding strategy, and transmits the control signal to the wearable vibration feedback device. S3. The wearable vibration feedback device generates corresponding vibration stimulation at different positions in front, back, left and right of the user's arm. The user can intuitively obtain the actual grip strength level of the current prosthetic hand by the vibration direction and number of vibration sources perceived by the skin. S4. Based on the perceived current gripping force feedback, the user dynamically adjusts the intensity of their own muscle contraction to correct the input electromyographic signal. By adjusting the opening and closing of the prosthetic hand, the user adjusts the gripping force to achieve closed-loop regulation of human-computer interaction. If the task is not completed, the user returns to step S1 in real time.

6. The closed-loop feedback method for prostheses based on vibration coding feedback according to claim 5, characterized in that, The specific process of step S1 in the aforementioned prosthetic closed-loop feedback method is as follows: S11. The electromyography (EMG) sensing module acquires raw EMG signals from the surface muscle groups of the user's residual limb in real time at a sampling frequency of 200Hz. The data processor calculates the root mean square value of the raw EMG signal using a sliding window with a length of 200ms and an overlap rate of 80%, and extracts the EMG envelope. Subsequently, a second-order Butterworth low-pass filter with a cutoff frequency of 2.5Hz is used to smooth and filter the envelope signal, removing high-frequency interference and obtaining smooth EMG characteristic signals. S12. The data processor normalizes the smoothed electromyographic (EMG) signal, specifically by normalizing it to a set ratio of the user's maximum voluntary muscle contraction. This prevents muscle fatigue caused by excessive, extreme muscle contraction. Simultaneously, the data processor has a fixed dead zone threshold to filter out unconscious EMG fluctuations or environmental baseline noise below this threshold, preventing the prosthetic hand from producing unexpected erroneous movements. S13. The data processor uses a proportional speed control strategy to perform closed-loop motion control on the prosthetic hand; when the normalized electromyography intensity in step S12 exceeds the set motion dead zone threshold, the data processor establishes a linear mapping relationship between the electromyography intensity and the driving speed of the prosthetic hand end effector, and calculates the desired motion speed; the data processor combines the user's muscle contraction pattern to generate speed control commands, thereby driving the prosthetic hand end effector to accurately grasp the target object.

7. A closed-loop feedback method for prostheses based on vibration coding feedback according to claim 6, characterized in that, The specific process of step S3 is as follows: S31. The force sensor on the prosthetic hand end effector monitors the contact force data between the prosthetic hand and the target object in real time and transmits the data to the data processor; The data processor discretizes the continuously changing gripping force data according to the effective range of the sensor, and divides it into five discrete force levels from low to high: Level 1, Level 2, Level 3, Level 4, and Level 5. S32. The data processor generates corresponding vibration drive commands by calling the preset vibration coding strategy according to the current discrete force level. In the first to fourth levels, the data processor sequentially generates instructions to activate only the right vibration motor, the lower vibration motor, the left vibration motor, or the upper vibration motor, respectively. After receiving a command, the wearable vibration feedback device generates vibration stimulation in a single specific location; S33. When the gripping force data increases to the fifth level, the data processor generates an instruction to simultaneously activate the four vibration motors in the front, back, left, and right directions; After receiving the instruction, the wearable vibration feedback device uses a significantly increased number of vibration sources and stronger tactile stimulation to convey to the user that the gripping force is greater at this time.

Images