A prosthetic hand withdrawal reflex control system and method

Abstract

The present invention discloses a prosthetic hand withdrawal reflex control system and method, including a temperature sensor, a sensor wire, a digital processor module, an electrical stimulation waveform generation module, a peripheral stimulation pathway module and a prosthetic hand control module. The method includes the steps of obtaining the temperature of the object contacted by the prosthetic hand, transmitting an electrical signal to a temperature acquisition prediction and warning module, fitting and predicting to obtain a temperature prediction result, sending a temperature warning signal to a reflex pathway module, sending an instruction to control the prosthetic hand to complete the hand release action, transmitting tingling electrical stimulation waveform information to the peripheral stimulation pathway module, generating tingling electrical stimulation to act on the amputee, etc. The present invention can predict the temperature of the contacted object in a very short time, greatly shortening the time required for sensor measurement. The present invention uses a biologically realistic Izhikevich model to construct a reflex loop in a digital signal processor, so that the prosthetic hand of the amputee quickly releases after touching a high-temperature object, and reminds the amputee to identify external risk factors.

Description

Technical Field

[0001] The present invention relates to the field of perception feedback and control of prosthetic hands, and in particular to a prosthetic hand withdrawal reflex control system and method. Background Art

[0002] In real life, when a normal person touches a hot object, the withdrawal reflex (subconsciously retracting the hand) is triggered. The retraction action is completed before the high temperature information is transmitted to the brain, thus avoiding damage to the skin and nerves caused by the high temperature. Compared with normal people, when amputees operate prosthetic hands, they lack skin receptors, nerves and corresponding muscles on their prosthetic hands, and cannot sense high temperatures in time. They may misjudge the temperature of objects and affect their normal life. Existing industrial or commercial temperature sensors require a long time to stabilize before they can complete temperature measurement, which is different from the extremely short-time temperature judgment mechanism of the human body's withdrawal reflex.

[0003] In response to the problem of amputees' functional loss, previous patents have used sensors and external stimuli to help amputees sense temperature (patent name: Myoelectric prosthesis system and environmental perception method guided by multimodal information, inventors: Song Aiguo and Hu Xuhui, publication number: CN112587285A; 2021.04). After the sensor receives the temperature information, it uses a vibration signal force feedback of a specific frequency to vibrate on the amputee, representing different temperatures, and applies it to the amputee to make him sense the temperature. If the temperature exceeds the set threshold, voice or sound effects are used to remind the user to pay attention to the high temperature. The amputee receives this information and makes corresponding autonomous control based on his own judgment. There is also a patent that detects the temperature of the object through an infrared sensor when the prosthetic hand approaches the object to be grasped, and displays the result in real time on the display screen (patent name: A multi-sensor fusion prosthetic hand grasping force feedback control method, inventors: Jiang Haiyan and Huang Shuping, publication number: CN113952091A; 2022.01), and feeds it back to the user. The vibration unit installed on the arm can emit different vibration intensities corresponding to a specific temperature range to alert the user.

[0004] In response to the temperature prediction problem, past patents established the correlation between temperature data and electrical characteristic data through neural network training (invention patent name: training method, prediction method, device, equipment and medium of temperature prediction model, inventor: Deng Yangdong, publication number: CN114066090A, 2022.02), and used basic data and measured data to train the temperature prediction model, which effectively solved the problems of difficult data analysis and poor temperature prediction accuracy. Other patents draw Bezier curves based on the current temperature value of the boiler and the historical temperature values ​​of the set time (invention patent name: a boiler temperature prediction method and system, inventors: Zhou Guodong and He Yanfeng, publication number: CN114110550A, 2021.11), thereby predicting the temperature value of the boiler starting from the current moment and continuing for the set time. These methods improve the temperature prediction accuracy of industrial devices.

[0005] The present invention first develops a temperature prediction algorithm that responds to human bionics, quickly predicts the temperature range of the external environment based on the temperature change rate imitating the human body mechanism, and applies it to the rapid prediction and early warning of the temperature of objects touched by the prosthetic hand, and connects and matches it with a biologically real reflex circuit, so that after the prosthetic hand contacts the overheated object, it will quickly withdraw and release the hand through the circuit to avoid damage to the prosthetic hand; at the same time, the present invention will also naturally and quickly feedback high temperature warning information in the amputee's finger-sensing area through electrical stimulation, notify the prosthetic user to avoid damage due to high temperature, thereby effectively improving the withdrawal protection of the prosthetic hand temperature warning, and also reminding the user of the prosthetic hand of environmental hazards. Summary of the invention

[0006] In view of the above-mentioned defects of the prior art, the present invention provides a prosthetic hand withdrawal reflex control system and method; the technical problem to be solved by the present invention is how to make the prosthetic hand quickly withdraw and release the hand after it contacts an overheated object to avoid damage to the prosthetic hand, and at the same time, notify the prosthetic user to avoid injury due to high temperature.

[0007] To achieve the above objectives, the present invention provides a prosthetic hand withdrawal reflex control system, characterized in that it includes a temperature sensor, a sensor wire, a digital processor module, an electrical stimulation waveform generation module, a peripheral transcutaneous electrical stimulation pathway module and a prosthetic hand control module; the digital processor module includes a temperature acquisition prediction and early warning module and a reflex pathway module; the temperature sensor is placed at the fingertip of the prosthetic hand, the temperature sensor is connected to the digital processor module through the sensor wire, and the voltage signal of the temperature sensor is input to the temperature acquisition prediction and early warning module through the sensor wire; the temperature acquisition prediction and early warning module receives the voltage signal of the temperature sensor and performs analog-to-digital conversion, converts it into a digital signal, and performs temperature change fitting prediction, and the result plus the room temperature during use is the temperature prediction result, Then, the temperature prediction result is converted into a current signal in proportion. The higher the predicted temperature, the larger the corresponding current. The current signal is the temperature warning signal. The temperature warning signal is input into the reflex pathway module. One path of the temperature warning signal sends a motion instruction through the motor neuron model of the reflex pathway module to control the muscle model in the prosthetic hand, so that the prosthetic hand can complete the release action to protect the prosthetic hand. The other path of the temperature warning signal is transmitted to the electrical stimulation waveform generation module, which starts to encode and generate a tingling electrical stimulation waveform, and transmits the tingling electrical stimulation waveform information to the peripheral transcutaneous electrical stimulation pathway module. After receiving the tingling electrical stimulation waveform information, the peripheral transcutaneous electrical stimulation pathway module generates a tingling electrical stimulation to act on the amputee, so that the amputee receives the temperature warning signal.

[0008] The present invention also provides a prosthetic hand withdrawal reflex control method, which is characterized by comprising the following steps:

[0009] Step 1: obtaining the temperature of the object touched by the prosthetic hand through a temperature sensor placed at the fingertips of the prosthetic hand;

[0010] Step 2: The temperature sensor converts the acquired object temperature into an electrical signal and transmits it to the temperature acquisition, prediction and early warning module;

[0011] Step 3: the temperature acquisition prediction and early warning module receives the voltage signal of the temperature sensor, performs analog-to-digital conversion, converts the signal into a digital signal, and performs fitting prediction of the temperature change. The fitting prediction result plus the room temperature during use is the temperature prediction result;

[0012] Step 4: the temperature acquisition prediction and warning module compares the temperature prediction result with a preset threshold value, and sends the temperature warning signal to the reflection path module if the temperature is higher than the threshold value;

[0013] Step 5: The temperature warning signal sends a motion instruction through the motor neuron model of the reflex pathway module to control the muscle model in the prosthetic hand, so that the prosthetic hand completes the release action to protect the prosthetic hand;

[0014] Step 6: another channel of the temperature warning signal is transmitted to the electrical stimulation waveform generation module, which starts encoding and generating a tingling electrical stimulation waveform, and transmits the tingling electrical stimulation waveform information to the peripheral stimulation pathway module;

[0015] Step 7, after receiving the tingling electrical stimulation waveform information, the peripheral transcutaneous electrical stimulation pathway module generates tingling electrical stimulation to act on the amputee, so that the amputee receives the temperature warning signal;

[0016] Step 8: After receiving the temperature warning signal, the amputee handles subsequent corresponding matters.

[0017] Further, in step one, the temperature sensor is used as a part of an integrated sensor.

[0018] Furthermore, in step three, the temperature change fitting prediction is performed by performing polynomial fitting on the digital signal to obtain its first-order derivative (slope) signal, and the first-order derivative (slope) signal is input into the slope-temperature change fitting prediction module. The fitting prediction result plus the room temperature during use can obtain the temperature prediction result.

[0019] Furthermore, in step 4, the reflex pathway module constructs a “receptor neuron-interneuron-motor neuron” in a digital signal processor using a biologically realistic Izhikevich model. The Izhikevich model simulates the process of biological neurons emitting pulses, and its model equation is:

[0020] v'=0.04v 2 +5v+140-u+I

[0021] u'=a(bv-u)

[0022] If v ≥ 30mV,

[0023] Wherein v represents the neuron membrane potential, u represents the neuron recovery variable, the units of u and v are both millivolts, I is the current input to the neuron, the unit is milliampere, a, b, c, d are unitless parameters that change with the type of neuron, and when v ≥ 30mV, it is considered that the neuron emits a pulse. The temperature warning signal is converted into input current I in this model and input into the receptor neuron model. When the upper-level neuron emits a pulse, the loop model converts the pulse signal into a current signal and inputs it into the next-level neuron, thereby completing the transmission of information in the loop.

[0024] Furthermore, in step five, the muscle model includes an extensor model and a flexor model, and a finger is controlled by the cooperation between the extensor model and the flexor model.

[0025] Furthermore, in step five, after receiving the motion instruction issued by the motor neuron model, the muscle model calculates the force output by the motor and controls the motor to achieve finger control.

[0026] Furthermore, in step six, the encoded content includes the amplitude and frequency of the electrical stimulation, and a specific combination of amplitude and frequency is used to generate the tingling electrical stimulation waveform.

[0027] Furthermore, in step six, the peripheral transcutaneous electrical stimulation pathway module includes a plurality of electrical stimulation modules, which act on the finger-sensing area or the alternative area of ​​the non-finger-sensing area of ​​the amputee to apply electrical stimulation corresponding to the temperature prediction result.

[0028] Furthermore, in step seven, the tingling electrical stimulation acts on the user's skin.

[0029] The present invention has the following technical features and advantages:

[0030] (1) The present invention provides a prediction algorithm for predicting the final temperature range based on the temperature change rate. The algorithm is consistent with the human body's temperature judgment mechanism and is suitable for application to artificial hands to simulate the human hand's perception of temperature.

[0031] (2) The present invention uses an FPGA chip to construct a biologically realistic muscle model, and uses the model to drive the motors at the prosthetic fingers, so that the movement of the prosthetic hand can be more consistent with physiological characteristics.

[0032] (3) The present invention uses Izhikevich to construct a neuron model in a digital processor. After receiving stimulation, the model can simulate real neurons to generate pulse signals and has biological authenticity.

[0033] (4) The present invention constructs a reflex circuit in the digital signal processor, which can simulate the reflex behavior of the human hand and protect the prosthetic hand. The circuit uses neurons constructed by the Izhikevich model.

[0034] (5) The present invention can use a wire-pulling method to control the retraction protection action of the prosthetic hand, so that the movement of the prosthetic hand is more consistent with the movement and biological characteristics of a healthy human hand.

[0035] (6) The present invention can use an underactuated prosthetic hand to control the retraction protection action of the prosthetic hand, so that the movement of the prosthetic hand is more consistent with the movement and biological real characteristics of a healthy human hand.

[0036] (7) The present invention can use a commercial motor drive to control the retraction protection action of the prosthetic hand, so that the movement of the prosthetic hand is more consistent with the movement of a healthy hand and the real biological characteristics.

[0037] (8) While constructing the reflex pathway, the present invention retains the function of the amputee's autonomous movement control of the prosthesis. If the amputee applies a high-threshold movement command when touching a high-temperature object, the reflex can be suppressed and the prosthetic hand will no longer be released. This is consistent with the control characteristics of normal people's reflexes.

[0038] (9) The present invention uses a polynomial fitting method to fit the temperature-time curve measured by the temperature sensor, and then calculates the first-order derivative of the polynomial curve to obtain the rate of change of temperature during the period of time.

[0039] (10) The present invention utilizes a digital processor to implement a temperature acquisition prediction and warning module and a reflection circuit, which has a fast operation speed and a stable state, and is suitable for a prosthetic hand.

[0040] (11) The temperature judgment interval selected by the present invention refers to the mechanism of human body temperature receptors. The human body's judgment of temperature is rough. According to the recognition interval of human body temperature receptors, there are six intervals: below 17°C, 17°C-27°C, 27°C-33°C, 33°C-44°C, 44°C-52°C, and above 52°C [3]. This patent establishes a similar temperature judgment interval with reference to the recognition mechanism of human body temperature receptors.

[0041] Compared with the traditional method and device, the present invention has the following beneficial effects:

[0042] (1) The present invention has developed a temperature prediction algorithm that conforms to the human body temperature judgment mechanism and predicts the final temperature range based on the temperature change rate. This algorithm can predict the temperature range of the contacted object in a very short time (within a few sampling points) after receiving the sensor signal, greatly shortening the time required for sensor measurement.

[0043] (2) The present invention makes up for the deficiency of the existing prosthetic hand that lacks the retraction reflex when it touches a high-temperature object. The reflex loop is constructed in the digital signal processor using the biologically realistic Izhikevich model. When the amputee touches the high-temperature object, the prosthetic hand quickly releases the hand, thereby protecting the prosthetic hand. At the same time, the electrical stimulator can produce a pinprick sensation and send an early warning message to the amputee. After receiving the information, the amputee can make a judgment and autonomously control the prosthesis through electromyography, reminding the amputee to identify external risk factors.

[0044] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A schematic diagram of a usage scenario of a preferred embodiment of the present invention;

[0046] Figure 2 The figure is a schematic diagram of a signal processing flow chart of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following describes several preferred embodiments of the present invention with reference to the drawings in the specification, so that the technical content is clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the protection scope of the present invention is not limited to the embodiments mentioned in the text.

[0048] In the drawings, components with the same structure are indicated by the same numerical reference numerals, and components with similar structures or functions are indicated by similar numerical reference numerals. The size and thickness of each component shown in the drawings are arbitrarily shown, and the present invention does not limit the size and thickness of each component. In order to make the illustration clearer, the thickness of the components is appropriately exaggerated in some places in the drawings.

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] The specific implementation of the present invention is as follows:

[0051] like Figure 1 and Figure 2 As shown, one embodiment consists of a temperature sensor, a digital processor, a prosthetic hand, an electrical stimulation waveform generation module, an electrical stimulator, an electrical stimulation electrode, an electromyography collector, an electromyography collection electrode, an electromyography collection electrode, a neuromorphic chip (a biologically realistic model chip built using FPGA), electrode wires, and sensor wires.

[0052] As part of the integrated sensor, the temperature sensor is placed at the fingertip of the prosthetic limb. The temperature sensor is connected to the digital processor through a sensor wire, and the voltage signal of the temperature sensor is input into the temperature warning prediction module of the digital processor through the wire. The temperature warning prediction module receives the voltage signal of the temperature sensor, performs analog-to-digital conversion, and then inputs it into a digital signal and inputs it into the polynomial fitting slope module. The module calculates the temperature change rate (slope) and then inputs it into the slope-temperature change fitting prediction module to predict the temperature change. The result plus the room temperature during use is the temperature prediction result. The module compares the prediction result with the set threshold. If it is higher than the threshold, a warning signal is sent to the reflection path.

[0053] The reflex pathway is composed of receptor neurons, interneurons, and motor neurons constructed by the Izhikevich model. The warning signal is first input to the receptor neuron, causing the neuron to generate pulses of a specific frequency and excite the interneuron. Similarly, the interneuron stimulates the next-order motor neuron to generate pulses after the pulse is excited, thus completing the conduction of the warning signal in the reflex pathway. The motor neuron converts one warning signal into a reflex movement command and transmits it to the neuromorphic chip of the prosthetic hand. The other warning signal is transmitted to the electrical stimulation waveform generation module through a wire to transmit the electrical stimulation control command.

[0054] The myoelectric collector collects the amputee's electromyographic signals. The electromyographic collection electrodes are attached to the amputee's ulnar wrist flexor and ulnar wrist extensor muscles, and connected to the electromyographic collector. The electromyographic collector sends the electromyographic information to the neuromorphic chip through wires, so that it can solve the movement instructions and control the motor. The amputee controls the prosthetic hand through the electromyography of the above two muscles to move autonomously.

[0055] The neuromorphic chip of the prosthetic hand receives the reflex movement instructions transmitted by the motor neurons, solves them, generates the corresponding prosthetic hand control information, and transmits it to the commercial prosthetic hand through wires. Each prosthetic hand is controlled by a pair of motors, which simulate the opening and grasping of the hand, respectively, so that it can release the high-temperature object and complete the reflex. If it is a wire-driven or under-driven prosthetic hand, it is transmitted to a pair of drive motors on the hand through wires. This pair of motors receives the tension and speed information, and controls the prosthetic hand through the cooperation of a pair of drive motors, so that it can release the high-temperature object and complete the reflex.

[0056] The electrical stimulation waveform generation module receives the electrical stimulation control instruction through the wire and starts encoding. The encoding content includes the amplitude and frequency of the electrical stimulation. It uses a specific amplitude and frequency combination to generate a tingling electrical stimulation waveform and transmits the waveform information to the peripheral electrical stimulator through the wire.

[0057] The peripheral electrical stimulator has five electrical stimulation modules, each of which is connected to an electrode patch through an electrode wire. The electrode patch is fixed to the induced finger sense area or alternative sense area at the end of the amputee's residual limb. The electrical stimulator converts the transmitted waveform information into electrical stimulation, which is applied to the amputee through the stimulation electrode, so that the amputee receives a temperature warning signal.

[0058] It should be noted that the present invention adopts a temperature prediction and early warning algorithm based on the temperature change rate, and can also choose to use neural network training for temperature-time data, or use curve fitting and other methods to predict temperature, which can also play a predictive effect. The peripheral stimulation pathway of the present invention acts on the finger-inducing sense area of ​​the amputee through electrical stimulation, and feeds back the temperature warning signal to the amputee. It can also use general electrical stimulation in the non-inducing finger-inducing sense area to complete the feedback of the temperature warning information, such as electrical stimulation of the upper arm, upper arm or other areas of the amputee, but not the finger-inducing sense area of ​​the amputee. The reflection loop can also be constructed using a general filter, rather than using a biologically real neuron model, and the transmission of the warning information in the loop can also be completed. Although other schemes can realize the feedback of the warning signal, the sound and light vibration feedback is slower, and the electrical stimulation is also slower if it is on the non-specific finger-inducing sense area. The present invention adopts the electrical stimulation feedback warning signal based on the induced finger sense, and can also select the electrical stimulation coding scheme of different frequencies and pulse widths, such as the electrical stimulation coding scheme that makes the amputee feel the sensations of humming, vibration, numbness, etc., which can also realize the function of early warning information feedback. The reflex pathway of the present invention is composed of neurons constructed from a biologically realistic Izhikevich model. It is also possible to use a filter to process the warning signal or directly use a threshold switch to transmit the warning signal to the prosthetic hand to achieve reflex. This alternative lacks biological authenticity, but can also achieve reflex function.

[0059] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A prosthetic hand withdrawal reflex control system, characterized in that: It includes a temperature sensor, a sensor wire, a digital processor module, an electrical stimulation waveform generation module, a peripheral transcutaneous electrical stimulation pathway module and a prosthetic hand control module; the digital processor module includes a temperature acquisition prediction and warning module and a reflex pathway module; the temperature sensor is placed at the fingertip of the prosthetic limb, the temperature sensor is connected to the digital processor module through the sensor wire, and the voltage signal of the temperature sensor is input to the temperature acquisition prediction and warning module through the sensor wire; the temperature acquisition prediction and warning module receives the voltage signal of the temperature sensor and performs analog-to-digital conversion, converts it into a digital signal and performs temperature change fitting prediction, the result plus the room temperature during use is the temperature prediction result, and then the temperature prediction result is converted into a current signal in proportion, the higher the predicted temperature, the larger the corresponding current, and the current signal is the temperature warning signal, wherein the temperature change fitting The combined prediction is achieved by fitting a polynomial to the digital signal to obtain its first-order derivative signal, and the first-order derivative signal is input into the slope-temperature change fitting prediction module, and the result of the fitting prediction plus the room temperature during use can obtain the temperature prediction result; the temperature warning signal is input into the reflex pathway module, and one path of the temperature warning signal sends a motion instruction through the motor neuron model of the reflex pathway module to control the muscle model in the prosthetic hand, so that the prosthetic hand completes the release action to protect the prosthetic hand; the other path of the temperature warning signal is transmitted to the electrical stimulation waveform generation module, and encoding and generating a tingling electrical stimulation waveform are started, and the tingling electrical stimulation waveform information is transmitted to the peripheral transcutaneous electrical stimulation pathway module; after receiving the tingling electrical stimulation waveform information, the peripheral transcutaneous electrical stimulation pathway module generates a tingling electrical stimulation to act on the amputee, so that the amputee receives the temperature warning signal.

2. A method for controlling a prosthetic hand withdrawal reflex, characterized in that: The following steps are involved: Step 1: obtaining the temperature of the object touched by the prosthetic hand through a temperature sensor placed at the fingertips of the prosthetic hand; Step 2: The temperature sensor converts the acquired object temperature into an electrical signal and transmits it to the temperature acquisition, prediction and early warning module; Step 3: The temperature acquisition prediction and early warning module receives the voltage signal of the temperature sensor and performs analog-to-digital conversion, converts it into a digital signal, and performs temperature change fitting prediction. The result of the fitting prediction plus the room temperature during use is the temperature prediction result; wherein, the temperature change fitting prediction is performed by performing polynomial fitting on the digital signal to obtain its first-order derivative signal, and the first-order derivative signal is input into the slope-temperature change fitting prediction module. The temperature prediction result can be obtained by adding the result of the fitting prediction to the room temperature during use; Step 4: the temperature acquisition prediction and warning module compares the temperature prediction result with a preset threshold value, and sends the temperature warning signal to the reflection path module if the temperature is higher than the threshold value; Step 5: The temperature warning signal sends a motion instruction through the motor neuron model of the reflex pathway module to control the muscle model in the prosthetic hand, so that the prosthetic hand completes the release action to protect the prosthetic hand; Step 6: another channel of the temperature warning signal is transmitted to the electrical stimulation waveform generation module, which starts encoding and generating the tingling electrical stimulation waveform, and transmits the tingling electrical stimulation waveform information to the peripheral stimulation pathway module; Step 7, after receiving the tingling electrical stimulation waveform information, the peripheral transcutaneous electrical stimulation pathway module generates tingling electrical stimulation to act on the amputee, so that the amputee receives the temperature warning signal; Step 8: After receiving the temperature warning signal, the amputee handles subsequent corresponding matters.

3. The prosthetic hand withdrawal reflex control method according to claim 2, characterized in that: In step one, the temperature sensor is used as part of an integrated sensor.

4. The method for controlling the prosthetic hand withdrawal reflex according to claim 2, characterized in that: In step 4, the reflex pathway module constructs a "receptor neuron-interneuron-motor neuron" in a digital signal processor using a biologically realistic Izhikevich model. The Izhikevich model simulates the process of biological neurons emitting pulses, and its model equation is: v'=0.04v 2 +5v+140-u+I u'=a(bv-u) If v≥30mV Wherein v represents the neuron membrane potential, u represents the neuron recovery variable, the units of u and v are both millivolts, I is the current input to the neuron, the unit is milliampere, a, b, c, d are unitless parameters that change with the type of neuron, and when v ≥ 30mV, it is considered that the neuron emits a pulse. The temperature warning signal is converted into input current I in this model and input into the receptor neuron model. When the upper-level neuron emits a pulse, the loop model converts the pulse signal into a current signal and inputs it into the next-level neuron, thereby completing the transmission of information in the loop.

5. The method for controlling the prosthetic hand withdrawal reflex according to claim 2, characterized in that: In step five, the muscle model includes an extensor model and a flexor model, and a finger is controlled by the cooperation between the extensor model and the flexor model.

6. The method for controlling the prosthetic hand withdrawal reflex according to claim 2, characterized in that: In step five, after receiving the motion command issued by the motor neuron model, the muscle model calculates the force output by the motor and controls the motor to achieve finger control.

7. The method for controlling the prosthetic hand withdrawal reflex according to claim 2, characterized in that: In step six, the encoded content includes the amplitude and frequency of the electrical stimulation, and a specific combination of amplitude and frequency is used to generate the tingling electrical stimulation waveform.

8. The method for controlling the prosthetic hand withdrawal reflex according to claim 2, characterized in that: In step six, the peripheral transcutaneous electrical stimulation pathway module includes a plurality of electrical stimulation modules, which act on the finger-sensing area or the alternative area of ​​the non-finger-sensing area of ​​the amputee to apply electrical stimulation corresponding to the temperature prediction result.

9. The method for controlling the prosthetic hand withdrawal reflex according to claim 2, characterized in that: In step seven, the tingling electrical stimulation acts on the user's skin.

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