Table 2.

Support Vector Machine (SVM) Features Selected for Generating the Classifier.

	FEATURES EXTRACTED
Raw signal	Minimum(1), Maximum(2), Standard deviation(3), root mean square(4)
First Derivative of Raw Signal	Minimum(5), Maximum(6)
Area Under the Curve	(7)
Width Between Peaks	(8)
Number of Peaks	(9)
Autocorrelation Maximum	(10)
Cepstrum of Raw Signal	Minimum(11), Maximum(12), Standard deviation(13), Mean(14)
First Derivative of Cepstrum	Minimum(15), Standard deviation(16)
Z score	Minimum(17)
Complex Cepstrum	Mean(18)
Power Spectrum of Raw Signal	Maximum(19)