Multi-lead myoelectricity detection system and method, electronic equipment and storage medium

Abstract

The invention provides a multi-lead myoelectricity detection system and method, electronic equipment and a storage medium. The system comprises a multi-channel myoelectricity acquisition node, a local area network, a synchronous signal broadcast and an upper computer, wherein the myoelectricity acquisition node is used for acquiring a myoelectricity signal; the local area network is used for realizing synchronous transmission of the multi-channel myoelectricity acquisition nodes; the synchronization signal broadcast is used for enabling the multichannel myoelectricity acquisition nodes to receive synchronization signals at the same time and then send the synchronization signals to the upper computer; the upper computer is used for displaying and storing the electromyographic signals of different channels in real time and processing and analyzing the electromyographic signals. The electromyographic signal synchronous monitoring system can break space limitation to achieve long-distance electromyographic signal transmission, break channel number limitation to achieve multi-node electromyographic signal synchronous monitoring, and can be used for diagnosis of different diseases and judgment of rehabilitation treatment effects through feature analysis of the electromyographic signals.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-node myoelectric signal detection, and in particular to a multi-lead myoelectric detection system and method, electronic equipment and storage medium. Background Art

[0002] Electromyography is an important physiological electrical signal for clinical diagnosis of various diseases and evaluation of rehabilitation methods, such as stroke, paralysis, Parkinson's disease, etc. Wired electromyography acquisition system is the most commonly used method. However, the wired electromyography acquisition system uses wired transmission to limit the range of human movement, has deficiencies in the detection range of movement, and has channel limitation problems.

[0003] Therefore, there is an urgent need for an electromyography detection system that can realize remote and simultaneous monitoring of electromyography signals in different parts and multi-channel detection. Summary of the invention

[0004] In order to achieve the above-mentioned purpose and other advantages according to the present invention, the first purpose of the present invention is to provide a multi-lead electromyography detection system, including a multi-channel electromyography acquisition node, a local area network, a synchronous signal broadcast, and a host computer; wherein, The electromyography acquisition node is used to collect electromyography signals; The local area network is used to realize the synchronous transmission of multi-channel electromyography acquisition nodes; The synchronization signal broadcast is used to enable the multi-channel electromyography acquisition nodes to simultaneously receive the synchronization signal and then send it to the host computer; The host computer is used to display and store the electromyographic signals of different channels in real time, and to process and analyze the electromyographic signals.

[0005] Furthermore, the electromyography acquisition node adopts differential electrodes.

[0006] Furthermore, the electromyography acquisition node includes an operational amplifier chip, a passive RC filter circuit, a main controller, a wireless communication module, a universal serial bus interface, and a synchronization signal receiving module. The operational amplifier chip uses DC coupling to collect the electromyography signal, and amplifies the electromyography signal through resistance matching of the peripheral circuit of the operational amplifier chip. The passive RC filter circuit is used for analog circuit filtering of the electromyography signal. The main controller performs digital-to-analog conversion through its built-in ADC module to digitize the electromyography signal. The wireless communication module is used to connect to the local area network and transmit the electromyography signal. The universal serial bus interface is used for other data transmission except electromyography signals, as well as network configuration and charging. The synchronization signal receiving module is used to receive the synchronization signal.

[0007] Furthermore, the electromyography acquisition node also reserves a bottom soldering pad and a top wire soldering point, the reserved bottom soldering pad is used for soldering the sensor, and the reserved top wire soldering point is used for soldering the wire of the sensor.

[0008] Furthermore, the local area network adopts a TCP network, and the synchronization signal broadcast adopts a Bluetooth broadcast synchronization signal.

[0009] Furthermore, the wireless communication module adopts a WIFI module.

[0010] Furthermore, the host computer includes an algorithm analysis model, which is used to extract features of the electromyographic signal, classify the extracted feature values ​​and evaluate the performance of the model, and finally realize the analysis of the electromyographic signal.

[0011] The second object of the present invention is to provide a multi-lead electromyography detection method, based on the above system, comprising the following steps: Broadcast synchronization signals so that multi-channel electromyography acquisition nodes simultaneously receive the synchronization signals and then send the collected electromyography signals to the host computer through the local area network; The electromyographic signals of different channels are displayed and stored in real time, and the electromyographic signals are processed and analyzed.

[0012] A third object of the present invention is to provide a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above method when executing the computer program.

[0013] A fourth object of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a multi-lead electromyography detection system and method, an electronic device and a storage medium, which can break the space limitation to realize long-distance electromyography signal transmission, break the channel number limitation to realize multi-node electromyography signal synchronous monitoring, and can be used for diagnosis of different diseases and judgment of rehabilitation treatment effect through characteristic analysis of electromyography signals.

[0015] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. The specific implementation of the present invention is given in detail by the following embodiments and their accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 Schematic diagram of a multi-lead electromyography detection system provided in an embodiment; Figure 2 A schematic diagram of the design of the electromyography acquisition node provided in the embodiment; Figure 3 A schematic diagram of an electromyographic signal acquisition node provided in an embodiment; Figure 4 It is a flow chart of the multi-lead electromyography detection method provided in the embodiment; Figure 5 A schematic diagram of a computer device provided in an embodiment; Figure 6 A schematic diagram of a computer-readable storage medium provided in an embodiment. DETAILED DESCRIPTION

[0017] The present invention is further described below in conjunction with the accompanying drawings and specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. It should be noted that, under the premise of no conflict, the embodiments or technical features described below can be arbitrarily combined to form a new embodiment.

[0018] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0019] The figure numbers in this application are only used to distinguish the various steps in the scheme, and are not used to limit the execution order of the various steps. The specific execution order is subject to the description in the specification.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0021] Example 1 A multi-lead electromyography detection system, such as Figure 1 As shown, it includes a multi-channel electromyography acquisition node (such as Figure 1 Node 1, node 2, ···, node n), local area network, synchronous signal broadcast, host computer; among them, The electromyography acquisition node is used to collect electromyography signals; The local area network is used to realize the synchronous transmission of multi-channel electromyography acquisition nodes; The synchronization signal broadcast is used to enable the multi-channel electromyography acquisition nodes to simultaneously receive the synchronization signal and then send it to the host computer; The host computer is used to display and store the electromyographic signals of different channels in real time, and to process and analyze the electromyographic signals.

[0022] In some embodiments, the electromyography acquisition node uses differential electrodes. Figure 2 As shown, the electromyographic acquisition node includes an operational amplifier chip, a passive RC filter circuit, a main controller, a wireless communication module, a universal serial bus interface, and a synchronization signal receiving module. The operational amplifier chip uses DC coupling to collect the electromyographic signal, and the electromyographic signal is amplified by the resistance matching of the peripheral circuit of the operational amplifier chip. The passive RC filter circuit is used for analog circuit filtering of the electromyographic signal. The main controller performs digital-to-analog conversion through its built-in ADC module to realize the digitization of the electromyographic signal. The wireless communication module is used to connect to the local area network and transmit the electromyographic signal. The universal serial bus interface is used for other data transmission (for example, power display, circuit board initialization status, system SRAM occupancy status, working mode, etc.) in addition to the electromyographic signal, as well as network configuration and charging. The synchronization signal receiving module is used to receive the synchronization signal. Preferably, the wireless communication module uses a WIFI module, for example, an ESP8266 WIFI module.

[0023] For example, STM32L442KCU6 is used as the main controller, and its internal ADC chip is used for digital-to-analog conversion to realize signal digitization, and the electromyography acquisition frequency is 500Hz. DC coupling is used to collect sEMG, and the INA332 chip amplifies sEMG by 96 times through resistor matching, followed by a 159.2Hz passive RC filter to complete the analog circuit filtering of sEMG; it has been verified that this amplification factor can achieve the amplification of electromyographic signals without exceeding the threshold due to the electromyographic signals being too large.

[0024] In some embodiments, Figure 2 As shown in FIG. 1 , the electromyography acquisition node also reserves a bottom pad and a top wire welding point. The reserved bottom pad is used to weld the sensor, and the reserved top wire welding point is used to weld the sensor wire. The reserved bottom pad can be used to weld the sensor, and the reserved top wire welding point is used to weld the sensor wire. Figure 2 shown.

[0025] Sometimes the traditional electrode stickers cannot meet the signal collection requirements, so a sensor connection area is reserved to allow the node to have more sensor options. In this embodiment, the two signal collection methods are as follows: Figure 3 shown.

[0026] In some embodiments, one of the keys to multi-channel electromyographic signal acquisition is the synchronization of different channels, so that the electromyographic characteristics of different parts at the same time can be reflected, and the electromyographic analysis can be completed when the electromyographic signal is real and effective. In order to realize the synchronous transmission of multi-channel electromyographic acquisition nodes, the local area network is constructed using a TCP network, and the synchronization of different nodes is guaranteed. For this reason, the synchronization signal broadcast uses a Bluetooth broadcast synchronization signal, so that different electromyographic acquisition nodes receive the synchronization signal at the same time and send it to the host computer, realizing long-distance multi-node electromyographic signal acquisition.

[0027] In order to analyze sEMG characteristics, a host computer is required to cooperate with real-time display and data storage. The host computer in this embodiment can display and store electromyographic signals of different channels in real time. Specifically, the host computer has functions such as filtering, packet loss information, signal multiple amplification, sEMG real-time display speed adjustment, and data storage.

[0028] In some embodiments, the host computer includes an algorithm analysis model, which is used to extract the features of the electromyographic signal. In order to fully analyze the electromyographic signal, the electromyographic features extracted include peak value fz, mean value jz, average amplitude pjfz, root mean square jfg, root amplitude fgfz, degree qd, margin index ydz, waveform index bxz, pulse index mcz, peak index ffz, kurtosis index qdz, and absolute power feature AP; then the extracted eigenvalues ​​are classified and the performance of the model is evaluated, and finally the analysis of the electromyographic signal is realized. For example, the extracted eigenvalues ​​use 7 classification algorithms including 'AdaBoost', 'Bagging', 'ExtraTrees', 'SVC', 'RF', 'DF', and 'GBDT'. The model evaluates the performance of the model by calculating the accuracy, precision, recall rate, F1 score, Roc curve, and confusion matrix, and finally the analysis of the electromyographic signal is realized.

[0029] In order to solve the technical problems existing in the wired EMG acquisition system, this embodiment provides a multi-lead EMG detection system to achieve remote and simultaneous monitoring of EMG signals in different parts, making detection of dozens of channels possible through the TCP network, and providing a new method for multi-channel EMG detection.

[0030] Example 2 A multi-lead electromyography detection method is based on the multi-lead electromyography detection system provided in Example 1. For a detailed description of the system, reference can be made to the corresponding description in the above system embodiment, which will not be repeated here. Figure 4 As shown, the method comprises the following steps: S1, broadcast synchronization signal, so that the multi-channel electromyography acquisition node simultaneously receives the synchronization signal and sends the collected electromyography signal to the host computer through the local area network; In some embodiments, one of the keys to multi-channel electromyographic signal acquisition is the synchronization of different channels, so that the electromyographic characteristics of different parts at the same time can be reflected, and the electromyographic analysis can be completed when the electromyographic signal is real and effective. In order to realize the synchronous transmission of multi-channel electromyographic acquisition nodes, the local area network is constructed using a TCP network, and the synchronization of different nodes is guaranteed. For this reason, the synchronization signal broadcast uses a Bluetooth broadcast synchronization signal, so that different electromyographic acquisition nodes receive the synchronization signal at the same time and send it to the host computer, realizing long-distance multi-node electromyographic signal acquisition.

[0031] S2. Display and store the electromyographic signals of different channels in real time, and process and analyze the electromyographic signals.

[0032] In order to analyze sEMG characteristics, a host computer is required to cooperate with real-time display and data storage. The host computer in this embodiment can display and store electromyographic signals of different channels in real time. Specifically, the host computer has functions such as filtering, packet loss information, signal multiple amplification, sEMG real-time display speed adjustment, and data storage.

[0033] In some embodiments, the host computer includes an algorithm analysis model, which is used to extract the features of the electromyographic signal. In order to fully analyze the electromyographic signal, the electromyographic features extracted include peak value fz, mean value jz, average amplitude pjfz, root mean square jfg, root amplitude fgfz, degree qd, margin index ydz, waveform index bxz, pulse index mcz, peak index ffz, kurtosis index qdz, and absolute power feature AP; then the extracted eigenvalues ​​are classified and the performance of the model is evaluated, and finally the analysis of the electromyographic signal is realized. For example, the extracted eigenvalues ​​use 7 classification algorithms including 'AdaBoost', 'Bagging', 'ExtraTrees', 'SVC', 'RF', 'DF', and 'GBDT'. The model evaluates the performance of the model by calculating the accuracy, precision, recall rate, F1 score, Roc curve, and confusion matrix, and finally the analysis of the electromyographic signal is realized.

[0034] This embodiment provides a multi-lead electromyography detection method, which can realize multi-node electromyography signal detection, adopt TCP network and WIFI signal to transmit electromyography signals synchronously to the host computer, and the host computer displays the electromyography signals in real time and completes storage, and realizes subsequent electromyography evaluation.

[0035] Example 3 A computer device such as Figure 5 As shown, it includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements a multi-lead electromyography detection method when executing the computer program. For a detailed description of the method, reference may be made to the corresponding description in the above method embodiment, and no further description is given here.

[0036] Example 4 A computer readable storage medium such as Figure 6 As shown, the computer readable storage medium stores a computer program, and when the computer program is executed by the processor, a multi-lead electromyography detection method is implemented. For a detailed description of the method, reference may be made to the corresponding description in the above method embodiment, and no further description is given here.

[0037] The number of devices and processing scales described here are used to simplify the description of the present invention. Applications, modifications and variations of the present invention will be obvious to those skilled in the art.

[0038] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and implementation modes. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and the illustrations shown and described herein.

[0039] The apparatus, electronic device, non-volatile computer storage medium and method provided in the embodiments of this specification correspond to each other, and therefore, the apparatus, electronic device and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, electronic device and non-volatile computer storage medium will not be repeated here.

[0040] Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, the controller can be made to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered as a hardware component, and the devices for implementing various functions included therein can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software units for implementing the method and structures within the hardware component.

[0041] The systems, devices or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described separately by functions in various units. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in the same or more software and / or hardware.

[0042] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0043] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0044] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0045] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0046] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0047] The specification may be described in the general context of computer-executable instructions executed by a computer, such as program units. Generally, program units include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communications network. In a distributed computing environment, program units may be located in local and remote computer storage media, including storage devices.

[0048] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0049] The above description is only an embodiment of this specification and is not intended to limit one or more embodiments of this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of one or more embodiments of this specification.

Claims

1. A multi-lead electromyography detection system, characterized in that: It includes multi-channel electromyography acquisition nodes, local area network, synchronous signal broadcasting, and host computer; among them, The electromyography acquisition node is used to collect electromyography signals; The local area network is used to realize the synchronous transmission of multi-channel electromyography acquisition nodes; The synchronization signal broadcast is used to enable the multi-channel electromyography acquisition nodes to simultaneously receive the synchronization signal and then send it to the host computer; The host computer is used to display and store the electromyographic signals of different channels in real time, and to process and analyze the electromyographic signals.

2. A multi-lead electromyography detection system as claimed in claim 1, characterized in that: The electromyography acquisition node adopts differential electrodes.

3. A multi-lead electromyography detection system as claimed in claim 2, characterized in that: The electromyography acquisition node includes an operational amplifier chip, a passive RC filter circuit, a main controller, a wireless communication module, a universal serial bus interface, and a synchronization signal receiving module. The operational amplifier chip uses DC coupling to collect the electromyography signal, and amplifies the electromyography signal through resistance matching of the peripheral circuit of the operational amplifier chip. The passive RC filter circuit is used for analog circuit filtering of the electromyography signal. The main controller performs digital-to-analog conversion through its built-in ADC module to realize the digitization of the electromyography signal. The wireless communication module is used to connect to the local area network and transmit the electromyography signal. The universal serial bus interface is used for other data transmission except electromyography signals, as well as network configuration and charging. The synchronization signal receiving module is used to receive the synchronization signal.

4. A multi-lead electromyography detection system as claimed in claim 3, characterized in that: The electromyography acquisition node also reserves a bottom soldering pad and a top wire soldering point. The reserved bottom soldering pad is used for soldering the sensor, and the reserved top wire soldering point is used for soldering the wire of the sensor.

5. A multi-lead electromyography detection system as claimed in claim 1, characterized in that: The local area network adopts a TCP network, and the synchronization signal broadcast adopts a Bluetooth broadcast synchronization signal.

6. A multi-lead electromyography detection system as claimed in claim 3, characterized in that: The wireless communication module adopts a WIFI module.

7. A multi-lead electromyography detection system as claimed in claim 1, characterized in that: The host computer includes an algorithm analysis model, which is used to extract the features of the electromyographic signal, classify the extracted feature values ​​and evaluate the performance of the model, and finally realize the analysis of the electromyographic signal.

8. A multi-lead electromyography detection method, based on the system according to any one of claims 1 to 7, characterized in that: The following steps are involved: Broadcast synchronization signals so that multi-channel electromyography acquisition nodes simultaneously receive the synchronization signals and then send the collected electromyography signals to the host computer through the local area network; The electromyographic signals of different channels are displayed and stored in real time, and the electromyographic signals are processed and analyzed.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to claim 8 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to claim 8 is implemented.

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