TY - GEN
T1 - Improved discrete fourier transform based spectral feature for surface electromyogram signal classification
AU - He, Jiayuan
AU - Zhang, Dingguo
AU - Sheng, Xinjun
AU - Meng, Jianjun
AU - Zhu, Xiangyang
PY - 2013
Y1 - 2013
N2 - An improved discrete Fourier transform (iDFT) is presented in this study as a novel feature for surface electromyogram (sEMG) pattern classification. It employs the principle that the spectrum of sEMG signals changes regarding different motions. iDFT feature focuses on global information of local bands to increase the inter-class distance. The experiment results showed that iDFT feature had a better separability than two other spectral features, auto regression (AR) and Power spectral density (PSD), both on experienced and inexperienced subjects. The optimal bandwidth is between 30 and 50 Hz and influence of division methods is not significant. With the low computation cost and property of insensitivity to sampling frequency, our proposed method provides a competitive choice for prosthetic control.
AB - An improved discrete Fourier transform (iDFT) is presented in this study as a novel feature for surface electromyogram (sEMG) pattern classification. It employs the principle that the spectrum of sEMG signals changes regarding different motions. iDFT feature focuses on global information of local bands to increase the inter-class distance. The experiment results showed that iDFT feature had a better separability than two other spectral features, auto regression (AR) and Power spectral density (PSD), both on experienced and inexperienced subjects. The optimal bandwidth is between 30 and 50 Hz and influence of division methods is not significant. With the low computation cost and property of insensitivity to sampling frequency, our proposed method provides a competitive choice for prosthetic control.
UR - http://www.scopus.com/inward/record.url?scp=84886491328&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84886491328&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2013.6611143
DO - 10.1109/EMBC.2013.6611143
M3 - Conference contribution
C2 - 24111330
AN - SCOPUS:84886491328
SN - 9781457702167
VL - 2013
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 6897
EP - 6900
BT - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
T2 - 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Y2 - 3 July 2013 through 7 July 2013
ER -