Title :
Features based on quasi-sinudoidal modeling for tremor detection in Parkinsonian voice
Author :
Ben Rhouma, Alaa ; Ben Jebara, Sofia
Author_Institution :
COSIM Lab., Carthage Univ., Ariana, Tunisia
Abstract :
This paper aims defining features to characterize Parkinsonian voice affected by tremor. It uses quasi-sinusoidal modelling of signals which assumes that speech signal is a sum of sinusoids with time-linearly varying instantaneous amplitudes and frequencies permits. The parameters of this model are calculated and their behavior is analyzed. The statistical analysis using box-plots permits to show the ability of this model to discriminate the Parkinsonian voice from the healthy voice.
Keywords :
acoustic signal detection; acoustic signal processing; diseases; feature extraction; medical signal processing; neurophysiology; physiological models; signal classification; speech processing; statistical analysis; waveform analysis; Parkinsonian voice characterization; Parkinsonian voice classification; Parkinsonian voice features; Parkinsonian voice tremor detection; box-plots; model parameter behavior analysis; model parameter calculation; quasi-sinudoidal modeling based features; sinusoid sum; speech signal model; statistical analysis; time-linear instantaneous amplitude variation; time-linear instantaneous frequency variation; Databases; Harmonic analysis; Noise; Parkinson´s disease; Speech; Time-frequency analysis; Parkinson´s disease; features for discrimination; quasi-sinusoidal model; tremor;
Conference_Titel :
Advanced Technologies for Signal and Image Processing (ATSIP), 2014 1st International Conference on
Conference_Location :
Sousse
DOI :
10.1109/ATSIP.2014.6834651
