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A walking pattern recognition method for exoskeleton based on electromyographic signals

A technology of electromyographic signals and walking patterns, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of increasing the difficulty of information collection, not mentioning common road condition information recognition, and being unfavorable for technology promotion and application, etc., to achieve The method is reliable and practical, the recognition time is short, the effect of real-time and safety assurance

Active Publication Date: 2017-03-29
HEBEI UNIV OF TECH
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Problems solved by technology

[0004] The Chinese patent No. CN201210214871.4 discloses a lower limb movement trajectory prediction method based on the fusion of EMG signals and joint angle information. Using EMG signals and knee joint angle information, four types of lower limbs can be identified: walking, standing up, squatting and knee extension The motion mode is used to control lower limb prostheses. The disadvantage is that the Vicon 3D motion capture system is used to calculate the knee joint angle, which increases the difficulty of information collection and limits the subject's activity area to a specific laboratory, which is not conducive to the promotion of technology. application, and did not mention the identification of common road conditions such as up and down stairs and up and down slopes

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  • A walking pattern recognition method for exoskeleton based on electromyographic signals
  • A walking pattern recognition method for exoskeleton based on electromyographic signals
  • A walking pattern recognition method for exoskeleton based on electromyographic signals

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Embodiment

[0085] The model of the EMG signal sensor used in this embodiment is MyoScan, and the EMG electrode used is a one-time-use three-point differential input EMG electrode with non-drying conductive gel. It is matched with the MyoScan EMG signal sensor. The model is MSP430F2274. One end of the electromyography signal sensor is connected to the electromyography electrode through the electrode button, and the other end is connected to the single-chip microcomputer fixed on the exoskeleton through a wire.

[0086] In the present invention, the value of M is determined to be 50ms, and the value of N is determined to be 4. The selection of the confidence threshold α is greatly affected by different individuals and varies from person to person. In this embodiment, the confidence threshold is determined by conducting multiple experiments on the data of the tested person α=0.65. Among them, the KNN classification algorithm mainly relies on the surrounding limited nearby samples when making ...

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Abstract

The invention relates to an exoskeleton walking mode identification method based on electromyographic signals. The exoskeleton walking mode identification method based on the electromyographic signal comprises the steps of (1) electromyographic signal collection, wherein an electromyographic electrode is attached to the muscle belly along the selected muscle group muscle fibers, an electromyographic signal sensor is connected with the electromyographic electrode through an electrode buckle, and a single-chip microcomputer fixed to the exoskeleton is connected with the electromyographic signal sensor through a wire and used for collecting the electromyographic signals; (2) electromyographic signal conditioning, wherein after the step (1), surface electromyographic signals collected by the electromyographic electrode are input to the electromyographic signal sensor for signal conditioning; (3) exoskeleton walking mode identification through an SVM-KNN classification algorithm based on threshold segmentation, wherein the surface electromyographic signals processed in the step (2) are input to the single-chip microcomputer for A / D conversion, preprocessing for elimination of zero drift, detection feature extraction initial time, feature extraction and classification through the SVM-KNN classification algorithm based on threshold segmentation, and finally the exoskeleton walking mode is identified.

Description

Technical field [0001] The invention relates to a human walking pattern recognition method applied to an exoskeleton, in particular to an exoskeleton walking pattern recognition method based on electromyographic signals. Background technique [0002] With the aging problem of modern society becoming more and more serious, the health problems of the elderly have received extensive attention from the whole society. Among them, the inflexible legs and feet are very headache problems in the lives of the elderly. Many elderly people will suffer from Feeling of weakness in his legs and feet, seriously affecting his normal life. Exoskeleton can provide external assistance to the elderly or people with walking disabilities in the process of walking on flat ground, up and down stairs, and uphill and downhill, helping them maintain appropriate activities, which is of great significance for improving the quality of life of the elderly and reducing the burden on the family and society. [000...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06K9/66
Inventor 陈玲玲杨鹏温倩李亚英任海男
Owner HEBEI UNIV OF TECH
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