Verification of A Fast Training Algorithm for Multi-Channel sEMG Classification Systems to Decode Hand Configuration

Title
Verification of A Fast Training Algorithm for Multi-Channel sEMG Classification Systems to Decode Hand Configuration
Authors
이한진김기훈박명수박종현오상록
Issue Date
2012-05
Publisher
ICRA2012
Citation
, 3167-3172
Abstract
In this study, we evaluated a fast training algorithm to decode human hand configuration from sEMG signals on the forearms of five subjects. Eight skin surface electrodes were placed on the forearm of each subject to detect the sEMG signals corresponding to four different hand configurations and relax state. The preamplifier, which has 100 - 10000 times amplification gain and a 15 - 500 Hz bandpass filter, was designed to amplify the signals and eliminate noise. In order to enhance the performance of the classifier, feature extraction using class information was developed. The randomly assigned non-update learning method guarantees high speed classifier learning. The algorithm has been verfied by experiments with five subjects.
URI
http://pubs.kist.re.kr/handle/201004/42457
Appears in Collections:
KIST Publication > Conference Paper
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