Bionic hand control method, device, electronic device and storage medium

Abstract

The present disclosure provides a bionic hand control method, device, electronic device and storage medium, wherein an inertial measurement unit and an electromyographic sensor are provided in the bionic hand. The bionic hand control method of the present disclosure embodiment comprises: obtaining the motion data of the bionic hand measured in real time by the inertial measurement unit; obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data of the bionic hand; when the jitter value exceeds a predetermined jitter threshold, entering a jitter protection mode, in which the current finger posture of the bionic hand is locked. The present disclosure can effectively avoid erroneous operations caused by jitter of the bionic hand.

Description

Technical Field

[0001] The present disclosure relates to the field of robotics technology, and in particular to a bionic hand control method, device, electronic device and storage medium. Background Art

[0002] Bionic hands are hand-assistive devices that mimic the structure and function of biological hands. They usually contain multiple degrees of freedom, can perform a variety of grasping and manipulation tasks, and are designed to simulate the look and feel of real hands as much as possible, and can mimic the weight and movements of real hands. Bionic hands can not only improve the quality of life of amputees, but also show great application potential in many fields such as industry, medicine, and services.

[0003] At present, the control of the bionic hand is mainly achieved by building myoelectric sensors into the bionic hand. After the user wears the bionic hand, the myoelectric sensors built into the bionic hand come into contact with the user's skin to collect the myoelectric signals of the user's skin, and the movements of the fingers of the bionic hand are controlled by analyzing the myoelectric signals. However, when the bionic hand is in an unstable state such as shaking, the contact between the myoelectric sensors and the user's skin is not sufficient, and the collected myoelectric signals are of poor quality and disorder, causing the bionic hand fingers to make wrong movements and even misoperation, affecting the user experience. Summary of the invention

[0004] In view of this, the present disclosure provides a bionic hand control method, device, electronic device and storage medium.

[0005] According to a first aspect of the present disclosure, a bionic hand control method is provided, wherein an inertial measurement unit and an electromyographic sensor are provided in the bionic hand, and the method comprises:

[0006] Acquiring motion data of the bionic hand measured in real time by the inertial measurement unit;

[0007] Obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data of the bionic hand;

[0008] When the jitter value exceeds a predetermined jitter threshold, a jitter protection mode is entered, in which the current finger posture of the bionic hand is locked.

[0009] In some implementations of the first aspect of the present disclosure, the method further includes: after entering the jitter protection mode, controlling the electromyographic sensor to stop collecting electromyographic signals.

[0010] In some embodiments of the first aspect of the present disclosure, the method further includes: when the jitter value does not exceed the predetermined jitter threshold, entering a normal mode, in which the finger posture of the bionic hand is unlocked and the electromyographic sensor is controlled to collect electromyographic signals in real time.

[0011] In some embodiments of the first aspect of the present disclosure, the inertial measurement unit includes an accelerometer, a gyroscope and a magnetometer, and the motion data includes linear acceleration, angular velocity and magnetic field strength; obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data includes: using a pre-trained jitter model to process the motion data of the bionic hand to obtain the jitter value; wherein the jitter model is trained by pre-collected bionic hand motion data marked with jitter values.

[0012] In some embodiments of the first aspect of the present disclosure, the method also includes: after entering the shake protection mode, determining whether the current finger posture is a preset posture; if the current finger posture is the preset posture, adjusting the input signal of the drive motor in the bionic hand to enhance the finger gripping force of the bionic hand, the drive motor being arranged inside the bionic hand and connected to the finger joints of the bionic hand.

[0013] In some embodiments of the first aspect of the present disclosure, if the current finger posture is a preset posture, the input signal of the drive motor in the bionic hand is adjusted to enhance the finger gripping force of the bionic hand, including: determining the target gripping force of the bionic hand according to the current gripping force of the bionic hand and / or the jitter value, and adjusting the input signal of the drive motor to increase the torque output of the drive motor so that the gripping force of the bionic hand reaches the target gripping force; wherein the current gripping force of the bionic hand is determined according to the electromyographic signal from the electromyographic sensor.

[0014] In some embodiments of the first aspect of the present disclosure, the method also includes: in response to a first operation of a user on a physical key and / or in response to a first instruction input by a user, exiting the shake protection mode, controlling the electromyographic sensor to collect electromyographic signals and unlocking the finger posture of the bionic hand.

[0015] According to a second aspect of the present disclosure, there is provided a bionic hand control device, comprising:

[0016] A data acquisition unit, used to acquire motion data of the bionic hand measured in real time by the inertial measurement unit;

[0017] A jitter evaluation unit, used for obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data of the bionic hand;

[0018] The jitter protection unit is used to enter a jitter protection mode when the jitter value exceeds a predetermined jitter threshold value, in which the current finger posture of the bionic hand is locked.

[0019] According to a third aspect of the present disclosure, an electronic device is provided, comprising: one or more processors and a memory storing a program, wherein the program comprises instructions, and when the instructions are executed by the processor, the processor executes the above method.

[0020] According to a fourth aspect of the present disclosure, a computer-readable storage medium storing a program is provided, wherein the program includes instructions, which, when executed by one or more processors of a computing device, cause the computing device to execute the above method.

[0021] It can be seen from the above technical scheme that, through the embodiment of the present disclosure, the motion data of the bionic hand is detected in real time through the inertial measurement unit, the shaking degree of the bionic hand is evaluated according to the motion data, and the shaking protection mode is entered when the shaking degree of the bionic hand is higher than the preset degree. In the shaking protection mode, the finger posture of the bionic hand is locked and the electromyographic sensor is controlled to stop collecting electromyographic signals, which can effectively avoid misoperation caused by shaking of the bionic hand, and significantly improve the user experience of the bionic hand while meeting the actual application needs of users. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 A schematic diagram of the structure of a bionic hand control system provided in an embodiment of the present disclosure;

[0024] Figure 2 A flow chart of a bionic hand control method provided by an embodiment of the present disclosure;

[0025] Figure 3 Another flow chart of the bionic hand control method provided by the embodiment of the present disclosure;

[0026] Figure 4 A schematic diagram of the structure of a bionic hand control device provided in an embodiment of the present disclosure;

[0027] Figure 5 A schematic structural block diagram of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0029] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure. The singular forms "a", "said" and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0030] As used herein, the words "if," "if," and the like may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0031] As described in the background technology, when the bionic hand is in an unstable state such as shaking, the contact between the electromyographic sensor and the user's skin is insufficient, and the collected electromyographic signals are of poor quality and disordered, causing the bionic hand fingers to make wrong movements or even misoperation, affecting the user experience. For example, when controlling the bionic hand to grasp a heavy object, if misoperation occurs due to the above problems, the object may slip due to insufficient gripping force, random finger movements, and other problems.

[0032] In view of this, the embodiments of the present disclosure provide the following bionic hand control method, device, electronic device and storage medium, which detects the motion data of the bionic hand in real time through an inertial measurement unit, evaluates the degree of jitter of the bionic hand based on the motion data, and enters a jitter protection mode when the jitter degree of the bionic hand is higher than a preset degree. In the jitter protection mode, the finger posture of the bionic hand is locked and the electromyographic sensor is controlled to stop collecting electromyographic signals, which can effectively avoid misoperation caused by shaking of the bionic hand, and significantly improve the user experience of the bionic hand while meeting the actual application needs of users.

[0033] To facilitate understanding, the bionic hand control system provided in the embodiment of the present disclosure is first exemplarily described below.

[0034] Figure 1 FIG. 2 shows a schematic diagram of the structure of a bionic hand control system provided by an embodiment of the present disclosure. Figure 1The bionic hand control system provided by the embodiment of the present disclosure includes: an electromyographic sensor 110, an inertial measurement unit (IMU) 120 and an electronic device 130. The electromyographic sensor 110 and the inertial measurement unit 120 are both arranged in a bionic hand 140. When worn, the electromyographic sensor 110 in the bionic hand 140 can contact the wearer's skin. The electromyographic sensor 110 and the inertial measurement unit 120 can communicate with the electronic device 130 respectively. The electronic device 130 can be used to control the bionic hand to make movements through the bionic hand control method described below.

[0035] Figure 1 An example of a bionic hand is also shown. Figure 1 In the example of , the bionic hand 140 includes five fingers 141, a palm 142, a wrist 143, and a receiving cavity 144. In a specific application, the IMU 120 can be arranged in the palm 142, the wrist 143, or the receiving cavity 144 of the bionic hand, and the myoelectric sensor 110 can be arranged in the receiving cavity 144 so that the myoelectric sensor can fully contact the user's skin to collect myoelectric signals.

[0036] In a specific application, a driving motor is provided inside the bionic hand 140, and the driving motor is connected to the finger joints of the bionic hand 140. The driving motor drives the fingers 141 of the bionic hand 140 to move under the control of an input signal. The driving motor is electrically connected to the electronic device 130, and the input signal of the driving motor can be provided by the electronic device 130.

[0037] It should be noted that Figure 1 The structure of the bionic hand 140 is only used as an example. Those skilled in the art should understand that the structure of the bionic hand is different in different application scenarios. For example, in other examples, the bionic hand may have fewer or more than five fingers, and the wrist may be designed as a hollow structure to be used as a receiving cavity at the same time. The embodiments of the present disclosure are applicable to bionic hands of any structure.

[0038] The myoelectric sensor 110 generates an electromyographic signal by sensing muscle contraction. In some examples, the myoelectric sensor 110 may be, but is not limited to, a surface electromyographic sensor, and the electromyographic signal may be, but is not limited to, a surface electromyography (sEMG).

[0039] The inertial measurement unit 120 can measure the motion data of the bionic hand 140 in real time. In specific applications, the inertial measurement unit 120 may include but is not limited to a gyroscope, an accelerometer, a magnetometer, etc., and the motion data collected by the inertial measurement unit 120 may include but is not limited to angular velocity, linear acceleration, magnetic field strength, etc.

[0040] See also Figure 1The electronic device 130 may include a controller 131 and a communication module 132. The communication module 132 is electrically connected to the controller 131. The communication module 132 may communicate with the myoelectric sensor 110 to obtain myoelectric signals generated by the contraction of muscles (e.g., arms, wrists, or hands) of a user wearing a bionic hand 140. The communication module 132 may communicate with the inertial measurement unit 120 to obtain motion data of the bionic hand 140. The controller 131 may be used to execute the bionic hand control method described below.

[0041] In a specific application, the electronic device 130 can be implemented as a microcontroller or other control device that can be built into the bionic hand. Alternatively, the electronic device 130 can be implemented as a device such as a computer or a server that is arranged outside the bionic hand.

[0042] In specific applications, the communication module 132 can be implemented as but not limited to a Bluetooth module, a short-range communication module, an Ethernet communication interface or other similar modules to communicate wirelessly. In addition, the communication module 132 can also be implemented as a communication data serial port or other electrical connection interface to communicate by wire.

[0043] The above system architecture of the embodiment of the present disclosure is only an example. Those skilled in the art should understand that in specific applications, the bionic hand control system may also adopt any other applicable architecture, and the embodiment of the present disclosure does not limit this.

[0044] The bionic hand control method provided by the embodiment of the present disclosure is described in detail below.

[0045] Figure 2 FIG. 1 is a flow chart of a bionic hand control method provided by an embodiment of the present disclosure. The bionic hand control method provided by an embodiment of the present disclosure can be executed by the aforementioned electronic device 130. Figure 2 , the method of the embodiment of the present disclosure may include:

[0046] Step 201, obtaining motion data of the bionic hand measured in real time by an inertial measurement unit;

[0047] Step 202, obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data of the bionic hand;

[0048] Step 203: When the jitter value exceeds a predetermined jitter threshold, a jitter protection mode is entered, in which the current finger posture of the bionic hand is locked.

[0049] In step 201 or before step 201, the bionic hand control method may further include: acquiring an electromyographic signal collected in real time by an electromyographic sensor, the electromyographic signal being generated due to skin contraction of the wearer; and determining a current finger posture of the bionic hand according to the electromyographic signal.

[0050] In specific applications, a gesture recognition model of a bionic hand can be pre-trained, and the gesture recognition model can be run to process the real-time collected electromyographic signals to identify the finger gestures of the bionic hand. While identifying the finger gestures, gesture data indicating the finger gestures can be further obtained. The gesture data may include but is not limited to gesture type, joint angle, finger position, finger direction (such as flexion / extension, adduction / abduction, rotation, etc.), etc.

[0051] When the inertial measurement unit includes an accelerometer, a gyroscope, and a magnetometer, the motion data acquired in step 201 may include linear acceleration, angular velocity, magnetic field strength, and the like.

[0052] The jitter value may be obtained through the jitter model in step 202. Two specific implementations of step 202 are described in detail below.

[0053] In some implementations, step 202 may include: analyzing the motion data of the bionic hand to obtain fluctuation data of the bionic hand, and using a predetermined jitter model to statistically analyze the fluctuation data of the bionic hand to obtain a jitter value. The fluctuation data may be used to indicate changes in the motion state of the bionic hand.

[0054] Specifically, the fluctuation data may include the fluctuation direction, fluctuation range and fluctuation frequency. In some implementations, the fluctuation data may be obtained in the following ways: the movement direction of the bionic hand may be determined by analyzing the angular velocity data in the motion data, and the movement direction is the fluctuation direction; the movement amplitude of the bionic hand may be determined by analyzing the magnitude of the acceleration and angular velocity in the motion data, and the movement amplitude is the fluctuation range; the frequency component of the motion may be obtained by extracting the frequency information from the time series information of the motion data using Fourier transform or other spectrum analysis methods, and the frequency component is the fluctuation frequency.

[0055] In addition, the fluctuation direction and fluctuation range in the fluctuation data can also be obtained in the following ways: using methods such as Kalman filtering, particle filtering or deep learning to estimate the posture of the bionic hand through motion data to obtain the posture data of the bionic hand (such as Euler angles or quaternions, etc.), extracting the motion parameters of the bionic hand from the posture data, the motion parameters including speed and displacement, and determining the fluctuation direction and fluctuation range by combining the motion parameters and motion data.

[0056] The jitter model may be, but is not limited to, an analysis model based on Gaussian distribution or an analysis model based on Fourier transform. In this example, the standard deviation or jitter peak indicating the degree of jitter can be obtained by using the jitter model to perform statistical analysis on the fluctuation data. The standard deviation or jitter peak is the jitter value. The larger the value of the standard deviation or jitter peak, the stronger the jitter of the bionic hand.

[0057] In some implementations, step 202 may include: using a pre-trained jitter model to process motion data of the bionic hand to obtain a jitter value of the bionic hand. The jitter model may be trained using pre-collected bionic hand motion data labeled with jitter values.

[0058] In specific applications, a machine learning model such as a convolutional neural network, a recurrent neural network, a variational encoder, etc. can be used to construct a jitter model, collect bionic hand motion data marked with jitter values ​​as samples, use a large number of collected samples to form a training set, a test set, and a validation set, use the training set to train the jitter model, and evaluate the performance of the jitter model through the validation set and the test set until the performance of the jitter model meets the requirements. In step 202, the bionic hand motion data is input into the jitter model for processing to obtain a jitter value indicating the degree of jitter of the bionic hand.

[0059] Furthermore, the jitter model can also be trained as a model for extracting jitter characteristics of bionic hand fingers, and the training method is the same as the above method. The jitter value obtained using the jitter model can more accurately reflect the degree of finger jitter of the bionic hand.

[0060] Furthermore, before step 202 or during step 202, the motion data may be pre-processed to remove noise, thereby improving the data quality of the motion data and further improving the accuracy of the jitter value.

[0061] In step 203, the predetermined jitter threshold can be an empirical value or a dynamic value. In specific applications, the predetermined jitter threshold can be flexibly set according to the needs of the actual application and the situation of the finger posture of the bionic hand. For example, in the scenario of using a bionic hand to grasp fragile objects, the predetermined jitter threshold can be set to a smaller value, in the scenario of using a bionic hand to operate a scalpel, the predetermined jitter threshold can be set to a smaller value, and in the scenario of using a bionic hand to grasp anti-fall objects, the predetermined jitter threshold can be set to a larger value. The configuration method, specific value, value range, etc. of the predetermined jitter threshold are not limited in the embodiments of the present disclosure.

[0062] Furthermore, in step 203 or after step 203, the bionic hand control method of the disclosed embodiment may further include: after entering the shaking protection mode, determining whether the current finger posture is a preset posture; if the current finger posture is a preset posture, adjusting the input signal of the driving motor in the bionic hand to enhance the finger gripping force of the bionic hand, the driving motor being arranged inside the bionic hand and connected to the finger joints of the bionic hand. Thus, the finger gripping force can be enhanced as needed to prevent the occurrence of, for example, objects slipping when the bionic hand shakes.

[0063] In some examples, it is possible to determine whether the finger posture is a preset posture by the type of posture. Specifically, a preset posture list can be pre-set, and the preset posture list contains type information of the preset posture. The preset posture can be, but is not limited to, grasping, grabbing, pinching, pinching, and other postures that are sensitive to misoperation. After determining the posture type of the current finger of the bionic hand using the electromyographic signal collected by the electromyographic sensor, it is determined whether the type of the current finger posture of the bionic hand is included in the preset posture list. If so, it is determined that the current finger posture of the bionic hand is the preset posture, otherwise, the current finger posture of the bionic hand is not the preset posture.

[0064] In some examples, it is possible to determine whether the finger posture of the bionic hand is a preset posture by using posture parameters. Specifically, a preset posture list can be preconfigured, and the preset posture list includes parameter values ​​of one or more preset postures and their difference thresholds. The parameters of the posture include but are not limited to joint angles, finger positions, and finger directions, and the difference thresholds include but are not limited to joint angle thresholds, finger position thresholds, and finger direction thresholds. After determining the parameter values ​​of the current finger posture of the bionic hand using the electromyographic signal collected by the electromyographic sensor, the difference between each parameter value of the current finger posture of the bionic hand and the corresponding parameter value of the preset posture is calculated (for example, absolute difference, variance, relative difference rate, percentage difference rate, etc.). If the difference of all parameters is not greater than the difference threshold of the corresponding parameter, the current finger posture of the bionic hand is the preset posture. After the difference between the current finger posture of the bionic hand and each preset posture in the preset posture list is determined, if none of the preset postures meets the condition of "the difference is not greater than the corresponding threshold", the current finger posture of the bionic hand is not the preset posture.

[0065] Of course, the specific implementation methods for determining whether the current finger posture of the bionic hand is the preset posture are not limited to the above two. Those skilled in the art should understand that any applicable method can be used in specific applications to determine whether the current finger posture of the bionic hand is the preset posture. This disclosure embodiment does not limit this.

[0066] Furthermore, adjusting the input signal of the driving motor in the bionic hand to enhance the gripping force of the fingers of the bionic hand may include: determining the target gripping force of the bionic hand based on the current gripping force and / or jitter value of the bionic hand, and adjusting the input signal of the driving motor to increase the torque output of the driving motor so that the gripping force of the bionic hand reaches the target gripping force; wherein the current gripping force of the bionic hand is determined based on the electromyographic signal collected by the electromyographic sensor.

[0067] In some examples, the input signal of the drive motor in the bionic hand can be adjusted in the following manner to enhance the gripping force of the fingers of the bionic hand: determine the current gripping force, calculate the target gripping force based on the current gripping force and a predetermined ratio, and adjust the input signal of the drive motor according to the target gripping force to increase the torque of the drive motor until the current gripping force detected by the force sensor is close to or equal to the target gripping force or until the gripping force corresponding to the torque of the drive motor is close to or equal to the target gripping force. Among them, the current gripping force can be detected by a force sensor, or calculated by the torque of the drive motor and the transmission ratio. For example, if it is necessary to increase the current gripping force by 50%, the target gripping force can be equal to the product of the current gripping force and 150%. Thus, during the shaking process, when the bionic hand is still locked in the gripping state, the required ratio can be increased on the basis of the current gripping force by adjusting the input signal of the drive motor to avoid the occurrence of situations such as objects slipping during shaking.

[0068] In some examples, the input signal of the drive motor in the bionic hand can be adjusted in the following manner to enhance the gripping force of the fingers of the bionic hand: calculate the difference between the current jitter value and the predetermined jitter threshold value, determine the gripping force increase ratio based on the difference, determine the current gripping force, calculate the target gripping force based on the current gripping force and the gripping force increase ratio, and adjust the input signal of the drive motor according to the target gripping force to increase the torque of the drive motor until the current gripping force detected by the force sensor is close to or equal to the target gripping force or until the gripping force corresponding to the torque of the drive motor is close to or equal to the target gripping force. Among them, the current gripping force can be detected by a force sensor, and can also be calculated by the torque of the drive motor and the transmission ratio. Thus, the gripping force can be increased according to the degree of jitter. The greater the degree of jitter, the more the gripping force increases, thereby better avoiding the occurrence of situations such as objects slipping.

[0069] In specific applications, any other applicable methods may be used to enhance the gripping force of the fingers of the bionic hand, and the embodiments of the present disclosure do not limit this.

[0070] In step 203, the finger posture of the bionic hand can be locked by sending a control signal to the drive motor in the bionic hand. Specifically, after entering the shake protection mode, the locking mechanism is automatically triggered, and the first control signal instructing the drive motor to control the bionic hand fingers to maintain the current posture is sent to the drive motor in the bionic hand to lock the finger posture of the bionic hand. In specific applications, the first control signal can be calculated by, for example, a PID (i.e., proportional integral differential) control algorithm, an adaptive control algorithm, or any other applicable control algorithm.

[0071] In step 203, if the current mode is already in the shake protection mode, there is no need to switch the mode, and the shake protection mode can be maintained. If the current mode is not in the shake protection mode, the current mode can be switched to the shake protection mode, and the locking mechanism can be triggered to lock the finger posture of the bionic hand.

[0072] Furthermore, step 203 may also include: after entering the shaking protection mode, controlling the myoelectric sensor to stop collecting myoelectric signals, thereby avoiding misoperation or shaking due to disordered myoelectric signals during shaking.

[0073] In some examples, a status flag can be set for the electromyographic sensor. When the value of the status flag is "stop", the electromyographic sensor interrupts the collection of electromyographic signals. If the status flag is "start", the electromyographic sensor will work in the state of real-time collection of electromyographic signals. In this example, after entering the jitter protection mode, the status flag of the electromyographic sensor can be automatically updated to "stop" to control the electromyographic sensor to stop collecting electromyographic signals.

[0074] In some examples, a first event can be set to trigger the electromyographic sensor to stop collecting data, and the trigger condition of the first event is set to "entering shake protection mode". In this way, once the bionic hand enters the shake protection mode, the first event is triggered and the electromyographic sensor will automatically stop collecting electromyographic signals.

[0075] Figure 3 Another schematic flow chart of the bionic hand control method provided by an embodiment of the present disclosure is shown.

[0076] Further, see Figure 3 The bionic hand control method provided by the embodiment of the present disclosure may further include:

[0077] Step 204, when the jitter value does not exceed the predetermined jitter threshold, enter the normal mode, in which the finger postures of the bionic hand are unlocked and the electromyographic sensor is controlled to collect electromyographic signals in real time. Specifically, if it is currently in the jitter protection mode, it can exit the jitter protection mode and return to the normal mode; if it is currently in the normal mode, it can maintain the normal mode. Thus, when it is detected that the jitter of the bionic hand is small or disappears, the jitter protection mode can be exited, and the electromyographic signals can continue to be collected and identified to control the fingers of the bionic hand.

[0078] In some examples, by updating the status flag of the electromyographic sensor to "start", the electromyographic sensor will switch to the working state of "real-time collection of electromyographic signals" and continue to collect electromyographic signals.

[0079] In some examples, a second event is automatically triggered after entering the normal mode, and the second event is used to trigger the electromyographic sensor to start collecting data. In response to the second event, the electromyographic sensor will automatically start real-time collection of electromyographic signals.

[0080] In some examples, the posture of the bionic hand can be unlocked by sending a control signal to the drive motor. For example, after entering the normal mode, the unlocking mechanism is triggered, and a second control signal instructing the drive motor to unlock is sent to the drive motor in the bionic hand to unlock the posture of the bionic hand.

[0081] Further, see Figure 3 The bionic hand control method provided by the embodiment of the present disclosure may further include:

[0082] Step 205: In response to the user's first operation on the physical button and / or in response to the user's first instruction input, the shake protection mode is exited, the bionic hand is unlocked, and the myoelectric sensor is controlled to collect myoelectric signals in real time. Thus, when unlocking is required or the user actively wants to make a specific action, the bionic hand can be controlled to change the finger posture by pressing the physical button, inputting instructions, etc.

[0083] The first operation on the physical key may be, but is not limited to, pressing, long pressing, tapping, or other operation forms. The first instruction may be a voice instruction, an action instruction, a gesture instruction, or other forms. The embodiments of the present disclosure do not limit the specific forms of the first operation and the first instruction.

[0084] Through the bionic hand control method of the disclosed embodiment, it can be detected that the bionic hand automatically enters the shake protection mode when the shake is relatively strong, locks the finger posture of the bionic hand and controls the electromyographic sensor to stop collecting electromyographic signals, effectively avoiding misoperation of the bionic hand due to shaking, reducing the occurrence of situations such as objects slipping, and also avoiding erroneous actions caused by disordered electromyographic signals, thereby significantly improving the user experience while meeting the actual application needs of users.

[0085] Figure 4 FIG. 2 shows a schematic diagram of the structure of a bionic hand control device provided by an embodiment of the present disclosure. Figure 4 , the bionic hand control device 400 may include:

[0086] A data acquisition unit 401 is used to acquire the motion data of the bionic hand measured in real time by the inertial measurement unit;

[0087] A jitter evaluation unit 402, configured to obtain a jitter value indicating a jitter degree of the bionic hand according to the motion data of the bionic hand;

[0088] The jitter protection unit 403 is used to enter a jitter protection mode when the jitter value exceeds a predetermined jitter threshold, in which the current finger posture of the bionic hand is locked.

[0089] Furthermore, the jitter protection unit 403 may also be used to: after entering the jitter protection mode, control the electromyographic sensor to stop collecting electromyographic signals.

[0090] Furthermore, the bionic hand control device 400 may also include: a normal operation unit 404, which is used to enter a normal mode when the jitter value does not exceed a predetermined jitter threshold. In the normal mode, the finger postures of the bionic hand are unlocked and the electromyographic sensor is controlled to collect electromyographic signals in real time.

[0091] Furthermore, the jitter evaluation unit 402 can be specifically used to: use a pre-trained jitter model to process the motion data of the bionic hand to obtain a jitter value; wherein the jitter model is trained by pre-collected bionic hand motion data labeled with jitter values.

[0092] Furthermore, the bionic hand control device 400 may also include: an adjustment unit 405, which is used to determine whether the current finger posture is a preset posture after entering the shake protection mode; if the current finger posture is the preset posture, adjust the input signal of the drive motor in the bionic hand to enhance the finger gripping force of the bionic hand, and the drive motor is arranged inside the bionic hand and connected to the finger joints of the bionic hand.

[0093] Furthermore, the bionic hand control device 400 may also include: an active unlocking unit 406, which is used to exit the shake protection mode in response to the user's first operation on the physical button and / or in response to the first instruction input by the user, control the electromyographic sensor to collect electromyographic signals in real time and unlock the finger posture of the bionic hand.

[0094] For other technical details about the bionic hand control device 400 , please refer to the above-mentioned part of the bionic hand control method, which will not be repeated here.

[0095] In addition, an embodiment of the present disclosure further provides a computer-readable storage medium on which a computer program is stored. The program includes instructions, and when the instructions are executed by one or more processors of a computing device, the steps of the aforementioned bionic hand control method are executed.

[0096] Figure 5 FIG. 1 is a schematic diagram showing the structure of an electronic device provided by an embodiment of the present disclosure. Figure 5 The electronic device 500 may include: one or more processors 501, and a memory 502 storing one or more programs, which are executed by the one or more processors 501 to implement the method flow shown in the above embodiments of the present disclosure and / or program units corresponding to each unit in the device.

[0097] The various components are interconnected using different buses and can be mounted on a common motherboard or in other ways as needed. The processor 501 can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the user interface on an external input / output device (such as a display device coupled to the interface). In other embodiments, if necessary, multiple processors and / or multiple buses can be used with multiple memories and multiple memories.

[0098] The processor 501 may include one or more single-core processors or multi-core processors. The processor 501 may include any combination of general-purpose processors or dedicated processors (such as image processors, application processors, baseband processors, etc.).

[0099] The memory 502 is a computer-readable storage medium provided by the present disclosure, which can be used to store non-transient software programs, non-transient computer executable programs and units, such as the following in the embodiments of the present disclosure: Figure 2 The processor 501 executes the non-transient software programs, instructions and units stored in the memory 502 to perform the above method embodiments. Figure 2 The programs, instructions and units corresponding to the bionic hand control method shown.

[0100] The electronic device 500 may further include: an input device 503 and an output device 504. The processor 501, the memory 502, the input device 503 and the output device 504 may be connected via a bus or other means. Figure 5 The example of connecting through bus is taken in the following.

[0101] The input device 503 can receive input digital or character information, and generate signal input related to user settings and function control, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator rod, one or more mouse buttons, a trackball, a joystick and other input devices. The output device 505 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration drive motor), etc. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display and a plasma display. In some embodiments, the display device may be a touch screen.

[0102] The above-mentioned programs (also referred to as software, software applications, or codes) include machine instructions for programmable processors, and these computer programs may be implemented using object-oriented programming languages, assembly or machine languages.

[0103] With the development of time and technology, the meaning of medium is becoming more and more extensive, and the dissemination path of computer programs is no longer limited to tangible media, but can also be downloaded directly from the Internet. Any combination of one or more computer-readable storage media can be used. Computer-readable storage media can be used, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media (a non-exhaustive list) include: portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, device or device.

[0104] The technical solution provided by the present disclosure is described in detail above. The principles and implementation methods of the present disclosure are described in detail using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present disclosure. At the same time, for those skilled in the art, according to the idea of ​​the present disclosure, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present disclosure.

[0105] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A bionic hand control method, characterized in that: The bionic hand is provided with an inertial measurement unit and an electromyographic sensor, and the method comprises: Acquiring motion data of the bionic hand measured in real time by the inertial measurement unit; Obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data of the bionic hand; When the jitter value exceeds a predetermined jitter threshold, entering a jitter protection mode, in which the current finger posture of the bionic hand is locked; Wherein, obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data includes: using a pre-trained jitter model to process the motion data of the bionic hand to obtain the jitter value; wherein, the jitter model is trained by pre-collected bionic hand motion data marked with jitter values.

2. The method according to claim 1, characterized in that The method further comprises: After entering the jitter protection mode, the electromyographic sensor is controlled to stop collecting electromyographic signals.

3. The method according to claim 1, characterized in that The method further includes: when the jitter value does not exceed the predetermined jitter threshold, entering a normal mode, in which the finger postures of the bionic hand are unlocked and the myoelectric sensor is controlled to collect myoelectric signals in real time.

4. The method according to claim 1, characterized in that The inertial measurement unit includes an accelerometer, a gyroscope and a magnetometer, and the motion data includes linear acceleration, angular velocity and magnetic field strength.

5. The method according to claim 1, characterized in that The method further comprises: After entering the shake protection mode, determining whether the current finger posture is a preset posture; If the current finger posture is a preset posture, the input signal of the drive motor in the bionic hand is adjusted to enhance the finger gripping force of the bionic hand. The drive motor is arranged inside the bionic hand and connected to the finger joints of the bionic hand.

6. The method according to claim 4, characterized in that If the current finger posture is a preset posture, adjusting the input signal of the driving motor in the bionic hand to enhance the finger gripping force of the bionic hand includes: Determining a target gripping force of the bionic hand according to the current gripping force of the bionic hand and / or the jitter value, and adjusting an input signal of the drive motor to increase the torque output of the drive motor so that the gripping force of the bionic hand reaches the target gripping force; The current gripping force of the bionic hand is determined according to the electromyographic signal from the electromyographic sensor.

7. The method according to claim 1, characterized in that The method further comprises: In response to a first operation of a user on a physical key and / or in response to a first instruction input by a user, the jitter protection mode is exited, the myoelectric sensor is controlled to collect myoelectric signals and the finger postures of the bionic hand are unlocked.

8. A bionic hand control device, characterized in that: include: A data acquisition unit, used to acquire motion data of the bionic hand measured in real time by an inertial measurement unit; A jitter evaluation unit, used for obtaining a jitter value indicating the degree of jitter of the bionic hand according to the motion data of the bionic hand; A jitter protection unit, used for entering a jitter protection mode when the jitter value exceeds a predetermined jitter threshold, in which the current finger posture of the bionic hand is locked; The jitter evaluation unit is used to process the motion data of the bionic hand using a pre-trained jitter model to obtain the jitter value; wherein the jitter model is trained by pre-collected bionic hand motion data marked with jitter values.

9. An electronic device, characterized in that: include: One or more processors and a memory storing a program, wherein the program includes instructions, and when the instructions are executed by the processor, the processor executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a program, wherein the program comprises instructions, and when the instructions are executed by one or more processors of a computing device, the instructions cause the computing device to execute the method according to any one of claims 1 to 7.

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