A self-adaptive electrode registration method for robust myoelectric control

An electromyographic control and self-adaptive technology, applied in the field of robust electromyographic control of self-adaptive electrode registration, can solve problems such as differences and achieve high-accuracy results

Active Publication Date: 2019-04-09
UNIV OF SCI & TECH OF CHINA
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  • Abstract
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Problems solved by technology

However, these works only use high-density data to simulate electrode displacement and give quantitative analysis, and the electrodes are not re-worn in the experiment, which is still significantly different from the actual application.

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  • A self-adaptive electrode registration method for robust myoelectric control
  • A self-adaptive electrode registration method for robust myoelectric control
  • A self-adaptive electrode registration method for robust myoelectric control

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Embodiment Construction

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0018] An embodiment of the present invention provides an adaptive electrode registration method for robust myoelectric control, such as figure 1 As shown, it includes the following steps:

[0019] 1. Use the myoelectric signals collected by the currently worn electrode equipment to construct training data.

[0020] 1) The electrode device selects a flexible high-density electrode array with the number of row channels p, the number of column chann...

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Abstract

The invention discloses a self-adaptive electrode registration method for robust myoelectric control, and the method comprises the steps: completing the matching of a local region between training data (before electrode offset) and test data (after electrode offset) based on a convolutional neural network structure, and achieving the self-alignment or self-calibration of an electrode array; A completely unsupervised learning mode is used, no extra calibration data is needed, and the electrode self-calibration process is directly completed in the test stage. On the basis, the data of the overlapped recording areas before and after the array offset is identified, so that the high accuracy of the motion pattern identification can be ensured.

Description

technical field [0001] The invention relates to the field of biological signal processing, in particular to an adaptive electrode registration method for robust myoelectric control. Background technique [0002] Myoelectric signal is the bioelectric signal accompanying muscle contraction, which contains a wealth of motion control information, which can be used to capture motion or motion intention and interpret it as a control command in the human-machine interface. Surface EMG signals are collected from the skin surface and are widely used in EMG control due to the advantages of non-invasive measurement. Specifically, myoelectric control technology can be applied to devices such as prosthetics and exoskeleton robots. Surface EMG pattern recognition is a milestone technology in the field of EMG control. It can realize the control of multiple degrees of freedom by training classifiers to recognize various muscle movement patterns. Although this technology has a high action ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08G06F3/01
CPCG06F3/015G06N3/08G06N3/045G06F2218/08G06F2218/12G06F18/24
Inventor 张旭吴乐陈勋陈香喻斌丛松宇
Owner UNIV OF SCI & TECH OF CHINA
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