TY - JOUR
T1 - Discrimination of parkinsonian tremor from essential tremor by implementation of a wavelet-based soft-decision technique on emg and accelerometer signals
AU - Hossen, A.
AU - Muthuraman, M.
AU - Raethjen, J.
AU - Deuschl, G.
AU - Heute, U.
N1 - Funding Information:
The support by DAAD (German Academic Exchange Service) through a research scholarship for the first author and the support from the German Research Council (Deutsche Forschungsgemeinschaft, DFG: SFB 855) are gratefully acknowledged.
PY - 2010/7
Y1 - 2010/7
N2 - A wavelet-decomposition with soft-decision algorithm is used to estimate an approximate powerspectral density (PSD) of both accelerometer and surface EMG signals for the purpose of discrimination of Parkinson tremor from essential tremor. A soft-decision wavelet-based PSD estimation is used with 256 bands for a signal sampled at 800 Hz. The sum of the entropy of the PSD in band 6 (7.8125-9.375 Hz) and band 11 (15.625-17.1875 Hz) is used as a classification factor. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. A "voting" between three results obtained from accelerometer signal and two EMG signals is applied to obtain the final discrimination. A total accuracy of discrimination of 85% is obtained.
AB - A wavelet-decomposition with soft-decision algorithm is used to estimate an approximate powerspectral density (PSD) of both accelerometer and surface EMG signals for the purpose of discrimination of Parkinson tremor from essential tremor. A soft-decision wavelet-based PSD estimation is used with 256 bands for a signal sampled at 800 Hz. The sum of the entropy of the PSD in band 6 (7.8125-9.375 Hz) and band 11 (15.625-17.1875 Hz) is used as a classification factor. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. A "voting" between three results obtained from accelerometer signal and two EMG signals is applied to obtain the final discrimination. A total accuracy of discrimination of 85% is obtained.
KW - Accelerometer signals
KW - Discrimination
KW - EMG
KW - Essential tremor
KW - Parkinson tremor
KW - Power-spectral density
KW - Soft-decision Technique
KW - Wavelet-decomposition
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U2 - 10.1016/j.bspc.2010.02.005
DO - 10.1016/j.bspc.2010.02.005
M3 - Article
AN - SCOPUS:78651424111
SN - 1746-8094
VL - 5
SP - 181
EP - 188
JO - Biomedical Signal Processing and Control
JF - Biomedical Signal Processing and Control
IS - 3
ER -