Portable hand rehabilitation system based on sEMG

Abstract

The application discloses a portable hand rehabilitation system based on sEMG, which comprises an electromyographic sensor, an electric stimulation module, a processor module and a pneumatic glove module; the electromyographic sensor is connected with an electrode patch and is used for detecting the surface electromyographic signal of the patient's hand; the electric stimulation module is connected with an electrode used for electrically stimulating the arm, the electric stimulation module is in communication connection with the electromyographic sensor, is used for receiving the surface electromyographic signal and forwarding the surface electromyographic signal to the processor module; the processor module is wirelessly connected with the electric stimulation module, is used for judging the motion intention based on the Willision amplitude and the local phase difference value of the surface electromyographic signal, and is used for sending the inflation / air extraction instruction to the pneumatic glove module based on the motion intention; the pneumatic glove module comprises a solenoid valve, an air pump and a pneumatic glove, the solenoid valve is wirelessly connected with the processor module and controls the air pump to inflate / extract the pneumatic glove based on the received inflation / air extraction instruction.

Description

Technical Field

[0001] This invention relates to the field of medical rehabilitation equipment technology, and in particular to a portable hand rehabilitation system based on sEMG. Background Technology

[0002] Surface electromyography (sEMG) is an electrical signal that accompanies muscle contraction and can directly reflect the movement of human muscles.

[0003] Currently, clinical treatment modalities for hand function are mainly divided into two types: therapist-assisted mode and rehabilitation instrument-assisted mode. Therapist-assisted mode involves the patient completing a series of rehabilitation exercises with the assistance of a therapist, without the aid of the instrument. This mode has relatively good results, and the patient can control the movement independently during treatment. However, it requires the therapist's intervention, and due to the limited number of therapists, patients can only receive treatment for a short period. Furthermore, patients need to go to the hospital for treatment, which is inconvenient for some. Rehabilitation instrument-assisted mode involves the patient completing fixed therapeutic movements with the assistance of relevant instruments. However, in this mode, the patient passively receives treatment and cannot control the movement independently. The treatment process is relatively monotonous, and the patient's enthusiasm for treatment is low, resulting in limited therapeutic effects. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a portable hand rehabilitation system based on sEMG, which allows patients to participate in the treatment process independently, thereby improving their enthusiasm for treatment and thus enhancing the treatment effect. Moreover, patients can use the device at home or in other scenarios to treat themselves without having to go to the hospital for specific treatment. The treatment is highly efficient and convenient, thus improving both the efficiency and convenience of treatment while ensuring the treatment effect.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0006] A portable hand rehabilitation system based on sEMG includes an electromyography (sEMG) sensor, an electrical stimulation module, a processor module, and a pneumatic glove module. The sEMG sensor is connected to electrode pads for detecting surface electromyography signals of the patient's hand. The electrical stimulation module is connected to electrodes for applying electrical stimulation to the arm. The electrical stimulation module is communicatively connected to the sEMG sensor to receive the surface electromyography signals and forward them to the processor module. The processor module is wirelessly connected to the electrical stimulation module to determine the movement intention based on the Willisson amplitude and local phase difference of the surface electromyography signals, and sends inflation / deflation commands to the pneumatic glove module based on the movement intention. The pneumatic glove module includes a solenoid valve, an air pump, and a pneumatic glove. The solenoid valve is wirelessly connected to the processor module and controls the air pump to inflate / deflate the pneumatic glove based on the received inflation / deflation commands.

[0007] Preferably, the determination of movement intention based on the Willisson amplitude and local phase difference value of the surface electromyography (EMG) signal includes the following steps: S11, acquiring the surface EMG signal; S12, determining whether the Willisson amplitude of the surface EMG signal is greater than a first threshold; if yes, proceed to step S13; if no, return to step S11; S13, determining whether the absolute value of the local phase difference value of the surface EMG signal is greater than a second threshold; if yes, proceed to step S14; if no, return to step S11; S14, determining whether the local phase difference value of the surface EMG signal is greater than 0; if yes, determine the movement intention as clenching a fist; if no, determine the movement intention as opening the palm.

[0008] Preferably, the Willisson amplitude of the surface electromyography signal is calculated using the following formula:

[0009]

[0010]

[0011] Where WAMP represents the Willision amplitude of the surface electromyography signal, x i Let be the amplitude of the surface electromyography (EMG) signal at time i, and L be the number of surface EMG signal samples acquired.

[0012] Preferably, the local phase difference value LD of the surface electromyography signal is defined using the following formula:

[0013] LD = X i +X i-1 +X i-2 -X i-3 -X i-4 -X i-5

[0014] Among them, X iThe value of the surface electromyography signal at time i.

[0015] Preferably, sending an inflation / deflation command to the pneumatic glove module based on the movement intention includes the following steps: if the movement intention is to clench a fist, an inflation command is sent to the pneumatic glove module; if the movement intention is to open the palm, a deflation command is sent to the pneumatic glove module.

[0016] Preferably, the processor module is further configured to acquire the current state of the pneumatic glove, and determine whether the movement intention is correct based on the current state of the pneumatic glove. If correct, it sends an inflation / deflation command to the pneumatic glove module based on the movement intention; if incorrect, it sends an electrical stimulation command to the electrical stimulation module.

[0017] Preferably, the electromyography sensor is used to detect the surface electromyography signal of the patient's superficial flexor digitorum muscles.

[0018] Preferably, the electrical stimulation module is connected to the processor module via Bluetooth; and / or, the solenoid valve is equipped with a WiFi module, and the solenoid valve is wirelessly connected to the processor module via the WiFi module.

[0019] Preferably, the processor module is a smartphone.

[0020] Preferably, the electrical stimulation module is an LGT-233 electrical stimulation therapy device. The electrical stimulation module is also used to preprocess the surface electromyography (EMG) signal and send the preprocessed EMG signal to the processor module.

[0021] The beneficial technical effects of this invention are as follows: The aforementioned portable hand rehabilitation system based on sEMG determines the patient's movement intention based on surface electromyography signals and controls the pneumatic glove based on the patient's movement intention, allowing the patient to participate autonomously in the treatment process. This frees the patient from the previously monotonous passive treatment mode, thereby increasing the patient's treatment enthusiasm and promoting the recovery of functions such as nerve function, thus improving the treatment effect. Moreover, the patient can use the device for treatment at home or in other scenarios without having to go to the hospital for specific treatment, resulting in high treatment efficiency and convenience. This ensures both treatment effectiveness and improved efficiency and convenience. The processor module is wirelessly connected to the electrical stimulation module and the pneumatic glove module. On the one hand, the patient does not need to wear the bulky processor module during treatment, reducing the patient's burden. On the other hand, it promotes the modularity of the device and increases its portability. This invention determines movement intention by combining Willision amplitude and local phase difference values. Combining the advantages of low computational load of Willision amplitude and accurate judgment of local phase difference values, the determination of movement intention is more accurate while ensuring real-time performance. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the structure of the portable hand rehabilitation system based on sEMG of the present invention;

[0023] Figure 2 This is a schematic diagram of the motion intent determination process of the present invention;

[0024] Figure 3 This is a schematic diagram of the control process for the pneumatic glove of the present invention;

[0025] Figure 4 This is a schematic diagram of the workflow of the portable hand rehabilitation system based on sEMG of the present invention in active training mode. Detailed Implementation

[0026] To enable those skilled in the art to more clearly understand the purpose, technical solution, and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0027] like Figure 1 As shown, in one embodiment of the present invention, the portable hand rehabilitation system based on sEMG includes an electromyography sensor, an electrical stimulation module, a processor module, and a pneumatic glove module.

[0028] The electromyography sensor is connected to electrode pads for detecting surface electromyography signals in the wearer's hand.

[0029] As shown in Table 1, there is a significant difference in the amplitude of electromyographic (EMG) signals when the fist is clenched and relaxed. The amplitude of the EMG signal when clenching the fist is approximately 500-600 ohms higher than that when relaxed. This invention uses clinically available EMG sensors to collect surface EMG signal data from patients with hand dysfunction in both relaxed and clenched states. This provides a data basis for subsequent analysis of the patient's movement intentions. Based on the surface EMG signal data, it is possible to determine whether the corresponding muscles are in an active or inactive state, and thus determine whether the patient is in a clenched fist or relaxed state.

[0030]

[0031] Table 1. Similarities and differences between electromyographic signals in normal individuals and those in patients.

[0032] In the practical application of this invention, the user is a patient with limited finger mobility. Therefore, we chose to measure only the electromyographic signals of the superficial flexor digitorum muscles, which reduces the number of electrode pads, thereby improving portability and lowering costs.

[0033] The electrostimulation module is connected to electrodes. By sending commands to the electrodes, it can transmit electrostimulation signals and apply electrical stimulation to the arm, thus achieving electrostimulation therapy. Furthermore, the electrostimulation module is communicatively connected to the electromyography (EMG) sensor to receive surface EMG signals collected by the sensor. It preprocesses the surface EMG signals to remove interference such as power frequency noise and peak amplitude in the original signals, and finally wirelessly transmits the preprocessed surface EMG signals to the processor module.

[0034] In this embodiment, the electrostimulation module is an LGT-233 electrostimulation therapy device; of course, in other embodiments, the electrostimulation module can also be other models of electrostimulation therapy devices available on the market. The LGT-233 electrostimulation therapy device connects to the electromyography (EMG) sensor via an internal AD adapter cable to receive the surface EMG signals collected by the EMG sensor. The LGT-233 then connects to the processor module via its internal Bluetooth module, sending the pre-processed surface EMG signals to the processor module. The LGT-233 electrostimulation therapy device features stable Bluetooth connectivity and fast output speed; its Bluetooth module transmits data at a frequency of 10Hz, meeting the real-time requirements of EMG signal transmission.

[0035] The pneumatic glove module includes a solenoid valve, an air pump, and a pneumatic glove. The solenoid valve drives and controls the air pump, which is powered by an independent battery. The solenoid valve is wirelessly connected to the processor module, controlling the air pump to inflate / de-inflate the pneumatic glove according to inflation / de-inflation commands sent by the processor module. Because the pneumatic glove module is wirelessly connected to the processor module, the patient does not need to wear the bulky processor module during treatment, reducing the patient's burden and increasing the portability of the device.

[0036] Wireless connection methods include Bluetooth and WiFi. However, since electromyography (EMG) signals are transmitted via Bluetooth, one-to-many transmission is difficult, and simultaneous transmission of different data can easily lead to data confusion. Therefore, in this embodiment, we use WiFi to control the air pump. The solenoid valve of this invention has a WiFi module, which serves as a WiFi hotspot. The processor module connects to this hotspot to form a local area network and controls the air pump's operating state by sending commands. The solenoid valve maintains its original state until the WiFi module receives a new command.

[0037] In this invention, the processor module serves as a data processor for a portable hand rehabilitation system, primarily used to acquire and analyze surface electromyography (EMG) signals and to control the electrical stimulation module and the pneumatic glove module accordingly. In this embodiment, the processor module is a smartphone, and by embedding a processing program into the smartphone, the phone can control the electrical stimulation module and the pneumatic glove module; of course, in other embodiments, the processor module can also be a computer device such as a tablet computer or a laptop computer.

[0038] The portable hand rehabilitation system based on sEMG of the present invention has two working modes: an assisted treatment mode and an active training mode. The working modes of the portable hand rehabilitation system based on sEMG can be switched by operating the processor module.

[0039] In the auxiliary treatment mode, the processor module determines the movement intention based on the Willision amplitude and local phase difference value of the surface electromyography signal, and sends inflation / deflation commands to the pneumatic glove module based on the movement intention, thereby realizing the control of the pneumatic glove.

[0040] like Figure 2 As shown, the determination of movement intention based on the Willisson amplitude and local phase difference value of surface electromyography signals includes the following steps:

[0041] S11. Acquire surface electromyographic signals.

[0042] S12. Determine whether the Willision amplitude of the surface electromyography signal is greater than the first threshold. If yes, proceed to step S13; otherwise, return to step S11.

[0043] S13. Determine whether the absolute value of the local phase difference LD of the surface electromyography signal is greater than the second threshold. If yes, proceed to step S14; otherwise, return to step S11.

[0044] S14. Determine whether the local phase difference value LD of the surface electromyography signal is greater than 0. If yes, determine that the movement intention is to clench the fist; if no, determine that the movement intention is to open the palm.

[0045] Willision amplitude refers to the number of times the difference in amplitude of surface electromyography (EMG) signals exceeds a threshold within a certain period of time. The Willision amplitude is calculated using the following formula:

[0046]

[0047]

[0048] Where WAMP represents the Willision amplitude of the surface electromyography signal, x iLet be the amplitude of the surface electromyography (EMG) signal at time i, and L be the number of surface EMG signal samples acquired.

[0049] Since the Willisson amplitude, a temporal characteristic, indicates the motor potential of active motor units and can be used to assess muscle contraction levels, the higher the muscle activity level over the same time period, the higher the Willisson amplitude. Therefore, the Willisson amplitude is selected to indicate the activity level of the patient's corresponding muscles. When the Willisson amplitude of the patient's corresponding muscle is less than a specified value (first threshold), the corresponding muscle is considered to be inactive; when the Willisson amplitude of the patient's corresponding muscle is greater than the specified value (first threshold), the corresponding muscle is considered to be active.

[0050] Analysis revealed that determining a patient's motor intention primarily depends not on identifying the moments of relaxation and fist clenching, but on identifying the boundary between these two states. While the Willisson amplitude can assess muscle activity over a given time period, it falls short in analyzing the boundary between fist clenching and relaxation. Firstly, during sustained fist clenching, the electromyographic (EMG) signal remains at a relatively high level for an extended period. As calculated by formulas (1) and (2), this leads to a lower Willisson amplitude and potential misjudgment. Secondly, clinical testing of patients' EMG signals revealed occasional slow declines in EMG signal during the transition from contraction to relaxation. Specifically, the decrease in EMG signal between adjacent time points is relatively small and persists for a considerable period. If the Willisson amplitude threshold is set too high, the muscle may be classified as inactive during this time. Conversely, a lower threshold may misjudge normal fluctuations in EMG signal as an active state. Therefore, an additional parameter is needed to assess the patient's motor intention in addition to the Willisson amplitude.

[0051] Define a new parameter named Local Difference (LD) as follows:

[0052] LD = X i +X i-1 +X i-2 -X i-3 -X i-4 -X i-5

[0053] Among them, X i The value of the surface electromyography signal at time i.

[0054] When the absolute value of the parameter LD is greater than a specified value (second threshold), the muscle is considered to be in an active state. Furthermore, if the parameter LD is positive, it is considered to be on the boundary between a relaxed and active state, and the intention to move should be determined as the patient clenching their fist. If the parameter LD is negative while its absolute value is greater than the specified value (second threshold), it is considered to be on the boundary between an active and relaxed state, and the intention to move should be determined as the patient opening their palm.

[0055] The advantages of using local phase difference (LD) for motor intention determination are as follows: First, LD can avoid abnormal increases in some electromyographic signals, which could lead to misjudgment of motor intention by Willisson amplitude; second, when patients wear gloves, the amplitude of electromyographic signals is relatively small, and LD can obtain the amplitude of each segment, and the motor intention can be determined by the sum of the amplitudes of each segment, so as to minimize the misjudgment of motor intention.

[0056] The portable hand rehabilitation system based on sEMG in this embodiment judges the movement intention by combining the Willision amplitude and the local phase difference value. Combining the advantages of the low computational cost of the Willision amplitude and the accuracy of the local phase difference value, the judgment of the movement intention is more accurate while ensuring real-time performance.

[0057] like Figure 3 As shown, sending inflation / deflation commands to the pneumatic glove module based on movement intention includes the following steps: If the movement intention is to clench a fist, an inflation command is sent to the WiFi module of the solenoid valve. The solenoid valve controls the air pump to inflate the pneumatic glove according to the inflation command so that the fingers bend, and after waiting for 4 seconds, a stop working command is sent to the solenoid valve to close the solenoid valve; If the movement intention is to open the palm, a deflation command is sent to the WiFi module of the solenoid valve. The solenoid valve controls the air pump to deflate the pneumatic glove according to the deflation command so that the fingers straighten, and after waiting for 2 seconds, a stop working command is sent to the solenoid valve to close the solenoid valve.

[0058] Analysis and observation of finger movements in daily life revealed that opening the palm generally doesn't require forcibly opening it into a flat plane; in contrast, clenching a fist, typically used for grasping objects, requires stronger gripping force. Based on this judgment, we controlled the air pump to inflate the pneumatic glove for 4 seconds before closing the solenoid valve, allowing the glove to fully contract; conversely, we controlled the air pump to de-inflate the glove for 2 seconds before closing the solenoid valve, allowing the user to slightly bend their fingers, increasing electromyographic signals and thus indicating an intention to clench a fist.

[0059] like Figure 4As shown, in active training mode, the processor module acquires the current state of the pneumatic glove and determines whether the movement intention is correct based on the current state of the pneumatic glove. If correct, it sends an inflation / deflation command to the pneumatic glove module based on the movement intention, switches the state of the pneumatic glove, and continues periodic training. If incorrect, it sends an electrical stimulation command to the electrical stimulation module. The LGT-233 electrical stimulation module provides electrical stimulation to the arm muscles through electrodes (the intensity can be adjusted) to promote the recovery of the patient's nerve function, etc., so that the patient can receive more effective treatment.

[0060] It should be noted that in active training mode, the exercise intention is determined based on surface electromyography signals, and the determination process is similar to... Figure 2 The steps for determining the movement intention in the illustrated embodiment are the same and will not be repeated here. After determining the patient's movement intention, the correctness of the movement intention is then determined based on the current state of the pneumatic glove. When the current state of the pneumatic glove is contracted, the movement intention must be an open palm for the movement intention to be considered correct; when the current state of the pneumatic glove is extended, the movement intention must be a clenched fist for the movement intention to be considered correct. The process of sending inflation / deflation commands to the pneumatic glove module based on the movement intention is the same as... Figure 3 The steps for sending inflation / deflation commands to the pneumatic glove module based on motion intention in the illustrated embodiment are the same and will not be repeated here.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any way. Those skilled in the art can make various equivalent changes and improvements based on the above embodiments, and all equivalent variations or modifications made within the scope of the claims should fall within the protection scope of the present invention.

Claims

1. A portable hand rehabilitation system based on sEMG, characterized in that, The portable hand rehabilitation system based on sEMG includes an electromyography (sEMG) sensor, an electrical stimulation module, a processor module, and a pneumatic glove module. The sEMG sensor is connected to electrode pads for detecting surface electromyography (EMG) signals on the patient's hand. The electrical stimulation module is connected to electrodes for applying electrical stimulation to the arm. The electrical stimulation module is communicatively connected to the sEMG sensor to receive the surface EMG signals and forward them to the processor module. The processor module is wirelessly connected to the electrical stimulation module and is used to determine the movement intention based on the Willisson amplitude and local phase difference value of the surface electromyography signal, and send inflation / deflation commands to the pneumatic glove module based on the movement intention; the pneumatic glove module includes a solenoid valve, an air pump and a pneumatic glove, the solenoid valve is wirelessly connected to the processor module and controls the air pump to inflate / deflate the pneumatic glove based on the received inflation / deflation commands; The method of determining movement intention based on the Willisson amplitude and local phase difference value of surface electromyography signals includes the following steps: S11. Acquire surface electromyographic signals; S12. Determine whether the Willision amplitude of the surface electromyography signal is greater than the first threshold. If yes, proceed to step S13. If no, return to step S11. S13. Determine whether the absolute value of the local phase difference of the surface electromyography signal is greater than the second threshold. If yes, proceed to step S14; otherwise, return to step S11. S14. Determine whether the local phase difference value of the surface electromyography signal is greater than 0. If yes, determine that the movement intention is to clench the fist; if no, determine that the movement intention is to open the palm. The Willisson amplitude of the surface electromyography signal is calculated using the following formula: in, The Willisian amplitude represents the surface electromyography signal. For time The amplitude of the surface electromyography (EMG) signal at that time, where L is the number of surface EMG signal samples acquired; The local phase difference (LD) of surface electromyography (EMG) signals is defined using the following formula: Among them, The value of the surface electromyography signal at time i.

2. The portable hand rehabilitation system based on sEMG as described in claim 1, characterized in that, Sending inflation / deflation commands to the pneumatic glove module based on movement intention includes the following steps: if the movement intention is to clench a fist, an inflation command is sent to the pneumatic glove module; if the movement intention is to open the palm, a deflation command is sent to the pneumatic glove module.

3. The portable hand rehabilitation system based on sEMG as described in any one of claims 1-2, characterized in that, The processor module is also used to acquire the current state of the pneumatic glove and determine whether the movement intention is correct based on the current state of the pneumatic glove. If correct, it sends an inflation / deflation command to the pneumatic glove module based on the movement intention; otherwise, it sends an electrical stimulation command to the electrical stimulation module.

4. The portable hand rehabilitation system based on sEMG as described in claim 1, characterized in that, The electromyography sensor is used to detect the surface electromyographic signals of the patient's superficial flexor digitorum muscles.

5. The portable hand rehabilitation system based on sEMG as described in claim 1, characterized in that, The electrical stimulation module is connected to the processor module via Bluetooth; and / or, the solenoid valve is equipped with a WiFi module, and the solenoid valve is wirelessly connected to the processor module via the WiFi module.

6. The portable hand rehabilitation system based on sEMG as described in claim 1, characterized in that, The processor module is a smartphone.

7. The portable hand rehabilitation system based on sEMG as described in claim 6, characterized in that, The electrical stimulation module is an LGT-233 electrical stimulation therapy device. The electrical stimulation module is also used to preprocess the surface electromyography (EMG) signal and send the preprocessed EMG signal to the processor module.

Images