A novel Parkinson’s Disease Diagnosis Index using higher-order spectra features in EEG signals
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/article/10.1007/s00521-016-2756-z/fulltext.html
Reference59 articles.
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2. Valls-Sole J, Valldeoriola F (2002) Neurophysiological correlate of clinical signs in Parkinson’s disease. Clin Neurophysiol 113(6):792–805
3. Hossen A, Muthuraman M, Raethjen J, Deuschl G, Heute U (2010) Discrimination of Parkinsonian tremor from essential tremor by implementation of a wavelet-based soft-decision technique on EMG and accelerometer signals. Biomed Signal Process Control 5:181–188
4. Ma C, Ouyang J, Chen HL, Zhao XH (2014) An efficient diagnosis system for Parkinson’s disease using kernel-based extreme learning machine with subtractive clustering features weighting approach. Comput Math Methods Med 2014:1–14. doi: 10.1155/2014/985789
5. Daliri MR (2013) Chi square distance kernel of the gaits for the diagnosis of Parkinson’s disease. Biomed Signal Process Control 8(1):66–70
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