Wireless myoelectricity sensing device, sensor falling-off detection method, equipment and medium

Abstract

The invention discloses a wireless myoelectricity sensing device, method and equipment and a storage medium. The device comprises a measuring electrode, an analog front-end unit and a micro-processing unit. Wherein the measuring electrode and the micro-processing unit are connected with the analog front-end unit; the measuring electrode is used for receiving the direct current source and generating a first voltage when the electrode leaves the muscle of the human body, or is used for receiving the alternating current source and generating a second voltage when the electrode leaves the muscle of the human body; the analog front-end unit is used for collecting the first voltage or the second voltage and sending the first voltage or the second voltage to the micro-processing unit; the micro-processing unit is used for generating an alarm signal according to the first voltage or the second voltage. The invention can be widely applied to the technical field of myoelectricity sensors.

Description

Technical Field

[0001] The present application relates to the technical field of myoelectric sensors, and in particular to a wireless myoelectric sensing device, method, equipment and storage medium. Background Art

[0002] In the related art, after the patient wears the electrodes of the electromyography sensor for a long time, the contact between the electrodes of the electromyography sensor and the skin cannot be detected in real time, resulting in excessive impedance between the electrodes, which in turn reduces the quality of the electromyography signal. Moreover, when the electrodes of the electromyography sensor fall off or partially fall off, the sensor cannot detect in real time, resulting in deviations in the measurement results and insufficient measurement accuracy. Therefore, there are still technical problems that need to be solved in the related art. Summary of the invention

[0003] The purpose of this application is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0004] To this end, an object of an embodiment of the present application is to provide a wireless electromyographic sensing device, a sensor detachment detection method, a device and a storage medium, which can detect electrode detachment in a timely manner and improve detection accuracy.

[0005] In order to achieve the above-mentioned technical objectives, the technical solution adopted in the embodiments of the present application includes: a wireless electromyography sensing device, comprising: a measuring electrode, an analog front-end unit and a microprocessing unit; wherein the measuring electrode and the microprocessing unit are connected to the analog front-end unit; the measuring electrode is used to receive a DC current source, and when the electrode leaves the human muscle, it generates a first voltage, or is used to receive an AC current source, and when the electrode leaves the human muscle, it generates a second voltage; the analog front-end unit is used to collect the first voltage or the second voltage, and send the first voltage or the second voltage to the microprocessing unit; the microprocessing unit is used to generate an alarm signal according to the first voltage or the second voltage.

[0006] In addition, a wireless electromyography sensing device according to the above embodiment of the present invention may also have the following additional technical features:

[0007] Furthermore, in an embodiment of the present application, the circuit also includes a right leg drive unit; the right leg drive unit includes a reference electrode and an amplifier circuit; the amplifier circuit is connected to the analog front-end unit; the reference electrode is connected to the amplifier circuit; the reference electrode is connected to the ground terminal of the measuring electrode; the right leg drive unit is used to output an inverting voltage with a direction opposite to the power frequency interference voltage and the same voltage value to offset the power frequency interference voltage.

[0008] Furthermore, in an embodiment of the present application, the analog front end unit includes a programmable gain amplifier and an analog-to-digital converter; the programmable gain amplifier is connected to the analog-to-digital converter.

[0009] Furthermore, in an embodiment of the present application, the gain of the programmable gain amplifier is 12 times; and the sampling frequency of the analog-to-digital converter is greater than 2 kHz.

[0010] Furthermore, in an embodiment of the present application, the microprocessor unit includes a radio frequency module and an MCU; the radio frequency module is connected to the MCU; and the radio frequency module is used to realize a wireless communication connection between the MCU and a host computer.

[0011] On the other hand, the present application provides a method for detecting the fall-off of a wireless electromyographic sensor, which is implemented by the wireless electromyographic sensor device described in any of the above items, and the method comprises:

[0012] When the measuring electrode leaves the human body muscle, a direct current source acts on the measuring electrode and adjusts the voltage at both ends of the measuring electrode to a first voltage; the analog front-end unit collects the first voltage and sends the first voltage to the microprocessing unit;

[0013] The microprocessing unit determines that the first voltage is greater than a first preset threshold value and generates an alarm signal;

[0014] Alternatively, when the measuring electrode leaves the human body muscle, an alternating current source acts on the measuring electrode and adjusts the voltage across the measuring electrode to a second voltage; the analog front-end unit collects the second voltage and sends the second voltage to the microprocessing unit;

[0015] The microprocessing unit determines that the second voltage is greater than a second preset threshold and generates an alarm signal.

[0016] Furthermore, in an embodiment of the present application, the frequency of the alternating current is 1 / 4 of the sampling rate of the analog-to-digital converter of the analog front-end unit.

[0017] Furthermore, in the embodiment of the present application, the first preset threshold is 95% of the supply voltage of the DC current source.

[0018] On the other hand, the present application also provides a wireless electromyography sensor fall-off detection device, comprising:

[0019] at least one processor;

[0020] at least one memory for storing at least one program;

[0021] When the at least one program is executed by the at least one processor, the at least one processor implements a wireless electromyographic sensing device as described in any one of the invention contents.

[0022] In addition, the present application also provides a computer-readable storage medium, which stores processor-executable instructions. When the processor-executable instructions are executed by the processor, they are used to execute a wireless electromyography sensing device as described in any of the above items.

[0023] The advantages and benefits of the present application will be partially given in the following description, and partially become apparent from the following description, or be understood through the practice of the present application:

[0024] The present application can realize electrode detachment detection through interconnected measuring electrodes, analog front-end units and microprocessing units. The measuring electrodes receive DC voltage or AC voltage and generate a potential difference when the electrodes leave the human body muscle; the analog front-end unit collects the potential difference and sends the potential difference to the microprocessing unit; the microprocessing unit is used to generate an alarm signal according to the potential difference. The present application can detect electrode detachment in time and improve detection accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of a human motion circuit in the prior art;

[0026] Figure 2 A schematic diagram of a module of a wireless electromyography sensor device in a specific embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the steps of a method for detecting the fall-off of a wireless electromyographic sensor in a specific embodiment of the present invention;

[0028] Figure 4 A schematic diagram of the steps of a method for detecting the fall-off of a wireless electromyographic sensor in another specific embodiment of the present invention;

[0029] Figure 5 A schematic diagram of the circuit structure of a patient protection circuit in a specific embodiment of the present invention;

[0030] Figure 6 A schematic diagram of the circuit structure of an analog front-end chip in a specific embodiment of the present invention;

[0031] Figure 7 A schematic diagram of the circuit structure of a microcontroller unit in a specific embodiment of the present invention;

[0032] Figure 8 It is a schematic diagram of the circuit structure of a radio frequency module in a specific embodiment of the present invention;

[0033] Fig. 9It is a structural schematic diagram of a DC lead-off detection mode circuit in a specific embodiment of the present invention;

[0034] Fig.10 It is a structural schematic diagram of an AC lead-off detection mode circuit in a specific embodiment of the present invention;

[0035] Fig.11 A schematic diagram of signal transmission of a wireless electromyographic sensing device in another specific embodiment of the present invention;

[0036] Fig.12 A schematic diagram of the frequency spectrum of three electromyographic signals in a specific embodiment of the present invention;

[0037] Fig.13 It is a schematic diagram of a module of a wireless electromyography sensing device in another specific embodiment of the present invention;

[0038] Fig.14 is an equivalent circuit diagram of a right leg driving circuit in a specific embodiment of the present invention;

[0039] Fig.15 It is a structural schematic diagram of a wireless electromyographic sensor fall-off detection device in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0040] The embodiments of the present invention are described in detail below with reference to the accompanying drawings to explain the principles and processes of the wireless myoelectric sensing device, method, equipment and storage medium in the embodiments of the present invention.

[0041] First, let's explain the physiological basis of electromyographic signals.

[0042] Human motor circuits Figure 1 As shown in the figure. After the cerebral cortex generates the intention to move, the stimulus is transmitted to the motor neurons in the corresponding position through the brainstem and spinal cord to control the contraction of skeletal muscles. At the same time, the sensory neurons feedback the current muscle state to the dorsal ganglion, and then to the cerebral cortex through the spinal cord. The motor nerves and sensory nerves are responsible for the transmission of control signals and feedback signals respectively, enhancing the stability of human movement.

[0043] like Figure 1As shown in the figure, motor neurons can be connected to multiple muscle fibers. At this time, the motor neuron, axon, muscle fiber connected to the motor neuron and its motor end plate constitute a motor unit (MU). MU is the smallest unit that generates electromyographic signals. After the brain motor stimulus is transmitted to the corresponding position of the spinal cord, the motor neuron begins to be excited, and the motor signal is transmitted to the motor end plate through the nerve endings, and a potential is generated at the position of the motor end plate and propagates along the muscle fiber to the tendon. The muscle fiber begins to contract under the stimulation of the action potential. When the skeletal muscle begins to contract under the control of the motor neuron, the potential generated by the superficial muscle MU is superimposed to form a corresponding potential difference on the muscle surface. The above potential difference is collected by the electromyographic sensor and becomes an electromyographic signal. When the electromyographic signal is generated, its activity and amplitude reflect the current degree of muscle recruitment and are closely related to the state of muscle activity. Therefore, by decoding the electromyographic signal, the current muscle force value can be obtained, and then the joint torque can be obtained. Since the electromyographic signal is generated by the MU, it has the following characteristics:

[0044] 1) Low signal amplitude. The amplitude of the electromyographic signal of healthy people ranges from 0 to 5 mV, and that of people with lower limb motor impairment ranges from 0 to 0.35 mV.

[0045] 2) Signal bandwidth. The effective frequency range of electromyographic signals is 20-450Hz. A bandpass filter must be used to filter the signals before use.

[0046] 3) The signal is susceptible to interference. Since the amplitude of the electromyographic signal is low, it is easily affected by electromagnetic interference from the external environment. In addition, since the electromyographic signal is generated inside the muscle and needs to be transmitted to the muscle surface through the muscle tissue before it can be collected by the electromyographic sensor, the subject's physiological state will affect the waveform of the electromyographic signal.

[0047] 4) The signal is random. Since the electromyographic signal has a zero mean characteristic, many electromyographic control systems regard the original electromyographic signal as a zero mean Gaussian process, whose instantaneous value does not contain effective information.

[0048] Secondly, the defects in the relevant technology are explained:

[0049] In the related art, the electromyogram (EMG) signal provides information related to the muscle activation state. It is the sum of the activation potentials associated with muscle contraction. EMG is widely used in various applications, including muscle activation assessment, neuromuscular health diagnosis, gait analysis, human-computer interaction, and pattern recognition. Although many researchers have studied EMG signals, the high cost of commercial EMG equipment still limits the promotion of EMG-based systems. In addition, commercial EMG equipment generally does not provide an interface for human-computer interaction detection. This makes it difficult to apply to real-time human-computer collaborative control.

[0050] In order to solve the above problems, researchers in related fields have developed low-cost wireless EMG systems. Traditional wireless EMG systems are able to measure muscle activity during human movement. And various denoising methods have been explored to obtain output signals. However, most analog-to-digital conversion chips (ADCs) used in traditional wireless EMG systems are built-in analog-to-digital converters of the controller. In addition, traditional wireless EMG systems lack circuit structures to compensate for 50Hz power line noise. In addition, due to the lack of lead-off detection circuits, traditional wireless EMG systems cannot detect the contact between electrodes and the human body in real time when collecting data, which leads to certain deviations in the test and reduces accuracy. Therefore, there are still problems in related technologies that need to be solved.

[0051] In view of the above-mentioned defects of the prior art, Figure 2 , Figure 2 A wireless electromyography sensor device is provided in an embodiment of the present application. Figure 2 In the embodiment, the wireless electromyography sensing device may include a measuring electrode 1, an analog front end unit 2 and a microprocessing unit 3. The measuring electrode 1 and the microprocessing unit 3 are connected to the analog front end unit 2;

[0052] The measuring electrode 1 can receive a DC current source and generate a voltage when the electrode leaves the human muscle, or can receive an AC current source and generate another voltage when the electrode leaves the human muscle. It can be understood that the DC current source can be a DC current source obtained by inputting an external voltage to a DC-DC converter. The AC current source can be an AC current source obtained by inputting an external voltage to an inverter. The analog front-end unit 2 can collect two voltages and send the two voltages to the microprocessor unit 3. The microprocessor unit 3 can generate different alarm signals based on the two voltages. The alarm signal can be transmitted to the host computer through the radio frequency module.

[0053] Furthermore, the device also includes a right leg driving unit. The right leg driving unit includes a reference electrode and an amplifier circuit; the amplifier circuit is connected to the analog front end unit. The reference electrode can be connected to the amplifier circuit. The reference electrode is connected to the ground terminal of the measuring electrode. The right leg driving unit is used to output an inverted voltage with a direction opposite to the power frequency interference voltage and the same voltage value to offset the power frequency interference voltage.

[0054] Furthermore, in some feasible embodiments of the present application, the analog front end unit includes a programmable gain amplifier and an analog-to-digital converter; the programmable gain amplifier is connected to the analog-to-digital converter.

[0055] Furthermore, in some feasible embodiments of the present application, the gain of the programmable gain amplifier is 12 times; and the sampling frequency of the analog-to-digital converter is greater than 2 kHz.

[0056] Furthermore, in some feasible embodiments of the present application, the microprocessor unit includes a radio frequency module and an MCU; the radio frequency module is connected to the MCU. The radio frequency module is used to realize wireless communication connection between the MCU and the analog front end unit.

[0057] In addition, refer to Figure 3 as well as Figure 4 The present application also provides a wireless electromyographic sensor drop-off detection method, which is implemented by any of the wireless electromyographic sensor devices described above. The wireless electromyographic sensor drop-off detection method includes steps S101, S102, and S103, or steps S111, S112, and S113.

[0058] S101. When the measuring electrode leaves the human body muscle, a direct current source acts on the measuring electrode to adjust the voltage across the measuring electrode to a first voltage.

[0059] S102: The analog front end unit collects a first voltage and sends the first voltage to the microprocessing unit.

[0060] S103: The microprocessing unit determines that the first voltage is greater than a first preset threshold and generates an alarm signal.

[0061] or,

[0062] S111. When the measuring electrode leaves the human body muscle, the alternating current source acts on the measuring electrode to adjust the voltage across the measuring electrode to a second voltage.

[0063] S112, the analog front end unit collects the second voltage and sends the second voltage to the microprocessing unit.

[0064] S113: The microprocessing unit determines that the second voltage is greater than a second preset threshold and generates an alarm signal.

[0065] Further, in some feasible embodiments of the present application, the frequency of the AC voltage may be 1 / 4 of the sampling rate of the analog-to-digital converter of the analog front-end unit.

[0066] Further, in some feasible embodiments of the present application, the first preset threshold may be 95% of the supply voltage of the DC current source, and the second preset threshold may be 1 / √2 times of the supply voltage of the AC current source.

[0067] The specific implementation principle of this application is described below with reference to the accompanying drawings:

[0068] The electromyogram (EMG) signal provides information about the activation state of a muscle. It is the sum of the activation potentials associated with muscle contraction. EMG is used in a wide variety of applications, including muscle activation assessment, neuromuscular health diagnosis, gait analysis, human-computer interaction, and pattern recognition.

[0069] Reference Figure 5 as well as Figure 6 The wireless electromyography (EMG) system of this embodiment includes analog and digital circuits. The analog circuit includes an analog front end (AFE) chip ( Figure 6 )、Patient Protection Circuit( Figure 5 ) and interface jacks. The digital circuitry includes a microcontroller unit (MCU) ( Figure 7 ) and radio frequency (RF) modules ( Figure 8 ). The raw EMG signal is first conducted through the electrodes attached to the surface of the target muscle, amplified by the built-in amplifier of the AFE, and then converted into a digital signal by the ADC and transmitted to the MCU. The MCU performs bandpass and notch filtering on the raw EMG signal to eliminate motion artifact noise, power line noise, and high-frequency noise. The radio frequency module (RF) sends the pre-processed signal to the computer.

[0070] Reference Figure 5 as well as Figure 6 , the analog circuit of the wireless EMG sensor of this embodiment includes a programmable gain amplifier (PGA) and an ADC integrated in an AFE chip. The gain of the PGA is set to 12. The sampling rate of the ADC is set to 8kHz. In addition to the preamplifier (PGA) and the ADC, the sensor also includes an integrated right leg drive unit (RLD circuit). The right leg drive unit (RLD circuit) is used to reduce the power line noise of the EMG signal. The entire analog circuit is powered by a 3.3V power chip. The patient protection circuit can reduce the current conduction effect of the wireless EMG sensor on the patient.

[0071] Reference Figure 7 as well as Figure 8 , the digital circuit of the wireless EMG sensor of this embodiment uses STM32F103C8T6 as the central controller and an ESP32C3 as a radio frequency (RF) module. The EMG signal sampled by ADS1292 is sent to STM32 via a serial peripheral interface (SPI) bus. In the central controller, the EMG signal is averaged every 8 samples to eliminate high-frequency noise and improve the resolution of the EMG data. The EMG signal is then digitally filtered through an IIR bandpass filter and a notch filter to eliminate motion artifact noise and power line noise. The filtered EMG signal is sent to the RF module via a universal asynchronous receiver / transmitter (UART) bus. The wireless EMG sensor is also equipped with a controller area network (CAN) bus, and the controller area network (CAN) bus can be used for human-machine interaction. The robot can obtain muscle activation status to perform human-machine collaborative control.

[0072] The wireless EMG system of this embodiment also provides an electrode off detection circuit. The impedance of the patient's electrodes decays over time. Therefore, it is necessary to continuously monitor these electrode connections to verify that the electrodes are properly connected. The electrode off detection circuit provides users with great flexibility to choose from a variety of lead off detection strategies. The electrode off detection circuit is as follows Fig. 9 As shown. The basic principle is to inject an excitation signal and measure the response to determine whether the electrode has fallen off. The circuit provides two different methods to determine the status of the patient's electrode. These methods differ in the frequency content of the excitation signal. The electrode off detection circuit is designed with two lead off detection modes. They are the DC lead off detection mode and the AC lead off detection mode.

[0073] ① DC lead-off detection mode. In this method, the sensor connects the electrode lead wires to the output ports of the DC current source and the DC current sink, such as Fig. 9 As shown. The power supply voltage of the DC current source and the current sink is 3.3V. The electrode detachment detection current of the DC current source and the DC current sink can be controlled by the MCU and is generally set to 10uA. When the electrode connection is normal, the electrical impedance between the bipolar electrode and the skin is about 10kΩ. The current source and the current sink can control the current of the current source-electrode-skin-current sink loop to be equal to 10uA. At this time, the partial voltage of the current on the bipolar electrode and the skin is about 100mV. When the electrode falls off, the electrical impedance between the bipolar electrode and the skin tends to infinity, and the partial voltage of the electrode detachment detection current on the bipolar electrode and the skin approaches the power supply voltage of 3.3V.

[0074] During use, the detection threshold set in the MCU is 95% of the power supply voltage, that is, 3.135 V. When the voltage drop between the bipolar electrode and the skin exceeds 3.135 V, the sensor will send an alarm signal to remind the user that the electrode has fallen off.

[0075] ② AC lead-off detection mode. In this method, the system will connect the electrode lead wires to the output ports of the AC current source and AC current sink. Fig.10As shown. A high-frequency AC signal with a frequency higher than the effective frequency of EMG is used for excitation. The frequency of the AC signal is 4 times the sampling frequency, which can minimize the impact of the AC excitation current on EMG sampling. By measuring the amplitude of the excitation signal in the output spectrum, the lead-off status can be calculated. Specifically, the power supply voltage of the AC current source and the AC current sink is DC 3.3V. The AC current source and the AC current sink generate AC current by periodically changing the direction of current flow. The AC signal output by the AC current source and the AC current sink will be transmitted to the current source-electrode-skin-current sink loop. The frequency of the AC current output by the AC current source and the AC current sink is set to 1 / 4 of the current sampling rate. Assuming that the current sampling rate of the EMG signal is set to 8kHz, the AC current signal frequency of the AC current source and the AC current sink is 2kHz in the AC lead-off detection mode. The root mean square value of the AC current can be controlled by the MCU, with a maximum of 10uA. In the AC lead-off detection mode, the signal path is as follows Fig.11 As shown in the figure, after the AC signal is superimposed, the EMG signal is amplified by the PGA, and then sampled by the ADC before entering the MCU.

[0076] Fig.12 Figure (a) shows the EMG signal. Fig.12 Figure (b) shows the EMG signal with the AC signal superimposed. Fig.12 Figure (c) shows the spectrum of the EMG signal after the AC signal is superimposed. It can be seen that the power of the superimposed AC signal is outside the effective power range of the EMG signal. During the use of the sensor, the signal sampled by the ADC is the sum of the original electromyographic signal and the AC signal generated by the AC current on the skin. After the ADC sampling signal is input into the MCU, the MCU can extract the RMS value of the AC signal through the fast Fourier transform algorithm.

[0077] When the electrode is in good contact with the skin, the electrical impedance between the skin and the electrode is about 10kΩ, and the RMS value of the voltage generated by the AC current on the skin and the electrode is about 100mV.

[0078] When the electrode loses contact with the skin, the electrical impedance between the skin and the electrode tends to infinity. Since the power supply voltage of the AC current source and the AC current sink is 3.3V, after the electrode loses contact with the skin, the peak value of the voltage generated by the AC current on the skin and the electrode will not be higher than the power supply voltage. That is, when the contact is broken, the peak-to-peak value of the voltage generated by the AC current on the electrode and the skin is 3.3V of the power supply voltage. Through the calculation relationship between the root mean square value and the peak-to-peak value, it can be seen that the root mean square value of the voltage generated on the skin and the electrode is 3.3V / √2=2.334V. In actual use, when the root mean square amplitude of the AC signal exceeds 95% of 2.334V, that is, 2.216V, the sensor will send an alarm signal to prompt the user that the electrode has fallen off.

[0079] It should be noted that since the effective frequency range of the EMG signal is 20-450Hz, in the AC lead-off detection mode, the ADC sampling rate needs to be greater than 2kHz. This can ensure that the AC signal frequency generated by the AC current source and AC current sink is not in the effective frequency range of the EMG signal to prevent interference with the collection of the EMG signal.

[0080] The wireless EMG system of this embodiment also provides a right leg drive (RLD) circuit. The structure block diagram of the RLD circuit in the wireless EMG system is shown in FIG. Fig.13 When the EMG signal is input into the PGA through the bipolar electromyography electrode, the RLD amplifier is connected to the common-mode signal output terminal of the PGA, amplifies the common-mode signal of the PGA, inverts it, and then outputs it to the reference electrode.

[0081] When the muscle is not exerting force, there will be no EMG signal on the muscle surface. At this time, the equivalent circuit diagram of bipolar EMG electrode + EMG lead wire + PGA + RLD amplifier is as follows: Fig.14 As shown. The power frequency interference is equivalent to the existence of a voltage source with an amplitude of 220Vrms and a frequency of 50Hz in the circuit. V1 and V2 are the voltage values ​​of the two output ports of the bipolar electromyographic electrode respectively. The power frequency interference of the power grid is equivalent to adding an AC signal with a frequency of 50Hz and an amplitude affected by Cp, Cb, Z1 and Z2 at points V1 and V2. That is, the voltage value of points V1 and V2 to the circuit GND changes continuously with a period of 50Hz. Under normal circumstances, the voltage amplitude and phase of points V1 and V2 are approximately the same. Therefore, we design an RLD circuit to eliminate the above interference.

[0082] The RLD equivalent circuit is as follows Fig.14 The input of the RLD amplifier obtains the common-mode voltage from the common-mode output of the PGA, and the common-mode voltage amplitude is After inversion, the output is sent to the reference electrode. The output voltage of the RLD amplifier is V o =-V cmThe existence of the RLD amplifier is equivalent to adding a new voltage source with an antiphase to the voltage source that generates the power frequency interference to the ground terminal. At this time, the voltage value of the circuit GND at points V1 and V2 can be effectively reduced, reducing the amplitude of the power frequency interference signal.

[0083] and Figure 3 Corresponding to the method, the embodiment of the present application also provides a wireless electromyographic sensor fall-off detection device, and its specific structure can be referred to Fig.15 ,include:

[0084] at least one processor 1011;

[0085] At least one memory 1012, used to store at least one program;

[0086] When the at least one program is executed by the at least one processor, the at least one processor implements the wireless electromyography sensor fall-off detection method.

[0087] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0088] and Figure 3 Corresponding to the method, an embodiment of the present application further provides a computer-readable storage medium, which stores processor-executable instructions, and the processor-executable instructions are used to execute the wireless electromyography sensor detachment detection method when executed by the processor.

[0089] The contents of the above-mentioned wireless electromyographic sensor detachment detection method embodiment are all applicable to the present storage medium embodiment. The functions specifically implemented by the present storage medium embodiment are the same as those of the above-mentioned wireless electromyographic sensor detachment detection method embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned wireless electromyographic sensor detachment detection method embodiment.

[0090] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are expected, wherein the order of various operations is changed and the sub-operation described as a part of a larger operation is performed independently.

[0091] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0092] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several programs to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0093] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable programs for implementing the logical functions, and may be embodied in any computer-readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch and execute a program from a program execution system, device or apparatus), or in conjunction with such program execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by a program execution system, device or apparatus, or in conjunction with such program execution systems, devices or apparatuses.

[0094] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0095] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0096] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0097] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0098] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the described embodiments. Technical personnel familiar with the field may make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A wireless electromyography sensing device, characterized in that: include: Measuring electrodes, analog front end unit and microprocessing unit; Wherein, the measuring electrode and the microprocessing unit are connected to the analog front-end unit; The measuring electrode is used to receive a direct current source and generate a first voltage when the electrode leaves the human muscle, or to receive an alternating current source and generate a second voltage when the electrode leaves the human muscle; the analog front-end unit is used to collect the first voltage or the second voltage and send the first voltage or the second voltage to the microprocessing unit; the microprocessing unit is used to generate an alarm signal according to the first voltage or the second voltage.

2. The wireless electromyography sensing device according to claim 1, characterized in that: The device further comprises a right leg driving unit; the right leg driving unit comprises a reference electrode and an amplifier circuit; the amplifier circuit is connected to the analog front end unit; the reference electrode is connected to the amplifier circuit; The reference electrode is connected to the ground terminal of the measuring electrode; the right leg driving unit is used to output an anti-phase voltage with a direction opposite to the power frequency interference voltage and a voltage value the same as that of the power frequency interference voltage to offset the power frequency interference voltage.

3. The wireless electromyography sensing device according to claim 1, characterized in that: The analog front end unit includes a programmable gain amplifier and an analog-to-digital converter; the programmable gain amplifier is connected to the analog-to-digital converter.

4. The wireless electromyography sensing device according to claim 3, characterized in that: The gain of the programmable gain amplifier is 12 times; the sampling frequency of the analog-to-digital converter is greater than 2kHz.

5. The wireless electromyography sensing device according to claim 1, characterized in that: The microprocessing unit includes a radio frequency module and an MCU; the radio frequency module is connected to the MCU; and the radio frequency module is used to realize a wireless communication connection between the MCU and a host computer.

6. A method for detecting the fall-off of a wireless electromyography sensor, characterized in that: The method is implemented by the wireless electromyography sensing device according to any one of claims 1 to 5, and includes: When the measuring electrode leaves the human body muscle, a direct current source acts on the measuring electrode and adjusts the voltage at both ends of the measuring electrode to a first voltage; The analog front end unit collects the first voltage and sends the first voltage to the microprocessing unit; The microprocessing unit determines that the first voltage is greater than a first preset threshold value and generates an alarm signal; Alternatively, when the measuring electrode leaves the human body muscle, an alternating current source acts on the measuring electrode to adjust the voltage across the measuring electrode to a second voltage; The analog front end unit collects the second voltage and sends the second voltage to the microprocessing unit; The microprocessing unit determines that the second voltage is greater than a second preset threshold and generates an alarm signal.

7. A wireless electromyography sensor fall-off detection method according to claim 6, characterized in that: The frequency of the AC voltage is 1 / 4 of the sampling rate of the analog-to-digital converter of the analog front-end unit.

8. A wireless electromyographic sensor fall-off detection method according to claim 6, characterized in that: The first preset threshold is 95% of the supply voltage of the direct current source.

9. A wireless electromyography sensor fall-off detection device, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the wireless electromyography sensor fall-off detection method as described in any one of claims 6 to 8.

10. A computer-readable storage medium storing instructions executable by a processor, characterized in that: The processor-executable instructions are used to execute the wireless electromyography sensor fall-off detection method as described in any one of claims 6 to 8 when executed by the processor.

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