DocumentCode
2733901
Title
Detection of involuntary human hand motions using Empirical Mode Decomposition and Hilbert-Huang Transform
Author
Zhang, James Z. ; Price, Brant T. ; Adams, Robert D. ; Burbank, Kenneth ; Knaga, Theodore J.
Author_Institution
Dept. of Eng. & Technol., Western Carolina Univ., Cullowhee, NC
fYear
2008
fDate
10-13 Aug. 2008
Firstpage
157
Lastpage
160
Abstract
Involuntary human hand motions, or tremors, are normally regarded as a non-stationary process. Traditional analysis methods approximate tremor signals as stationary processes. In this paper, we present a novel tremor detection method using Empirical Mode Decomposition (EMD) and Hilbert-Huang Transform (HHT). The results are expected to be helpful for real-time tremor suppression.
Keywords
Hilbert transforms; image motion analysis; medical image processing; signal detection; Hilbert-Huang transform; empirical mode decomposition; involuntary human hand motion detection; nonstationary process; real-time tremor suppression; tremor detection method; tremor signals; Data mining; Digital signal processing; Frequency; Humans; Least squares approximation; Motion detection; Signal analysis; Signal processing; Signal processing algorithms; Signal resolution;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2008. MWSCAS 2008. 51st Midwest Symposium on
Conference_Location
Knoxville, TN
ISSN
1548-3746
Print_ISBN
978-1-4244-2166-4
Electronic_ISBN
1548-3746
Type
conf
DOI
10.1109/MWSCAS.2008.4616760
Filename
4616760
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