Computational and Mathematical Methods in Medicine / 2017 / Article / Tab 2

Research Article

Dysphonic Voice Pattern Analysis of Patients in Parkinson’s Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods

Table 2

Voice perturbation and nonlinear dynamic parameters measured from the acoustic signals of 31 subjects [5, 7].

Abbreviations Feature description

MDVP:F0 (Hz) Average vocal fundamental frequency
MDVP:Fhi (Hz) Maximum vocal fundamental frequency
MDVP:Flo (Hz) Minimum vocal fundamental frequency
MDVP:Jitter(%) MDVP jitter in percentage
MDVP:Jitter(Abs) MDVP absolute jitter in ms
MDVP:RAP MDVP relative amplitude perturbation
MDVP:PPQ MDVP five-point period perturbation quotient
Jitter:DDP Average absolute difference of differences between jitter cycles
MDVP:Shimmer MDVP local shimmer
MDVP:Shimmer(dB) MDVP local shimmer in dB
Shimmer:APQ3 Three-point amplitude perturbation quotient
Shimmer:APQ5 Five-point amplitude perturbation quotient
MDVP:APQ11 MDVP 11-point amplitude perturbation quotient
Shimmer:DDA Average absolute differences between the amplitudes of consecutive periods
NHR Noise-to-harmonics ratio
HNR Harmonics-to-noise ratio
RPDE Recurrence period density entropy measure
D2 Correlation dimension
DFA Signal fractal scaling exponent of detrended fluctuation analysis
Spread1 Two nonlinear measures of fundamental
Spread2 Frequency variation
PPE Pitch period entropy