Wavelet transform based EMG feature extraction and evaluation using scatter graphs

In the hand movement recognition system the most important step is feature extraction. Nowadays, the analysis of Electromyograhy signal using wavelet transform becoming the most powerful method. In this paper we have typically used the mathematical diagram tool i.e. scatter graph technique to evalua...

Full description

Saved in:
Bibliographic Details
Main Authors: Lolure, Amol, Thool, V. R.
Format: Conference Proceeding
Language:English
Subjects:
Bandwidth
Discrete wavelet transforms
Electromyograph
Electromyography
feature extraction
scatter graph
Thumb
wavelet transform
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In the hand movement recognition system the most important step is feature extraction. Nowadays, the analysis of Electromyograhy signal using wavelet transform becoming the most powerful method. In this paper we have typically used the mathematical diagram tool i.e. scatter graph technique to evaluate the performance of EMG features. The EMG signal corresponding to the different hand movements and finger movements are considered. Various features that are widely used are extracted from the different wavelet coefficient. The graphs obtained for MAV(Mean Absolute Value) from the reconstructed coefficient shows the better performance.
DOI:10.1109/IIC.2015.7150944