Some traditional and nontraditional features are analyzed for the parkinson disease classification. Various classifiers are used for this purpose.
Parkinson voice has tremor in it and it is visible in
jitter and shimmer values.Jitter values are higher in
parkinson subjects than the healthy one. Same
results are observed in case of shimmer.The
harmonic to noise ratio values are high for the
healthy one. The non-traditional measures show
appreciable differentiation between the two classes.
All the three features DFA, Spread1 and PPE have
higher values for parkinson subjects than the healthy
one. The tansig transfer function neural network