NDLI: Forearm Controller Based on BP Network and Sub-band Waves

Content Provider	IEEE Xplore Digital Library
Author	Xu Wang Xueqin Jia Jinghong Li Lihong Zhao
Copyright Year	2006
Description	Author affiliation: Coll. of Inf. Sci. & Eng., Northeastern Univ. in China, Shenyang (Xu Wang; Xueqin Jia; Jinghong Li; Lihong Zhao)
Abstract	In order to make the artificial forearm controller easier be trained and have higher robust, an adaptive controller for myoelectric signal (MES) is proposed. The control signal, MES, is derived from natural contraction patterns, which can be produced reliably with no subject training. To find features of MES, twenty-five filters with different center frequency and same bandwidth are designed and the feature curves of MES are shown in this paper. Based on the wavelet transform (WT) and the proposed feature curves, an ensemble of gate crossings based representations of MES is proposed. The gate for counting the gate crossings can change along with contractions, and this makes feature extraction adaptive to dissimilar contraction levels. Two-layer perceptron neural networks are used to classify a single site MES based on two features, specifically the gate crossings between 0 and 31.25Hz and the gate crossings between 31.25 and 62.5Hz. Based on the proposed controller scheme, the simulation result displays high accuracy rate
Starting Page	9367
Ending Page	9370
File Size	175232
Page Count	4
File Format	PDF
ISBN	1424403324
DOI	10.1109/WCICA.2006.1713814
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robust control Programmable control Adaptive control Filters Frequency Bandwidth Wavelet transforms Feature extraction Multilayer perceptrons Neural networks myoelectric signal neural networks wavelet transform feature extraction
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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