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Design of a Simulation System for Cross-Eye Dynamic Jamming Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Pattern Recognition of Artificial Legs Based on WPT and LVQ

Authors : Lei Liu, Yinmao Song, Peng Yang, Zuo Jun Liu

Published in: Proceedings of 2017 Chinese Intelligent Automation Conference

Publisher: Springer Singapore

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Abstract

Aiming at (SEMG) of gait recognition, multi-channel SEMG presents a adopts the wavelet packet transform (WPT) and learning vector quantization (LVQ) algorithm of neural network classifier. The SEMG signal based on the entropy criterion of optimal wavelet BaoJi decomposed each node decomposition coefficients, calculate the coefficient of each node corresponding sub band signal energy, after normalization processing characteristic vector input, LVQ neural network to achieve the gait recognition based on SEMG. Experimental results show that take two SEMG signals, the classifier can effectively identify upstairs, downstairs, uphill and downhill four action pattern, the recognition rate of 96%, can be reliably applied to the control of the prosthetic.

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Metadata
Title
Pattern Recognition of Artificial Legs Based on WPT and LVQ
Authors
Lei Liu
Yinmao Song
Peng Yang
Zuo Jun Liu
Copyright Year
2018
Publisher
Springer Singapore
Book
Proceedings of 2017 Chinese Intelligent Automation Conference

Print ISBN: 978-981-10-6444-9

Electronic ISBN: 978-981-10-6445-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-6445-6_28