Classification of Parkinson Disease Based on Analysis and Synthesis of Voice Signal

Classification of Parkinson Disease Based on Analysis and Synthesis of Voice Signal

Vikas Mittal, R. K. Sharma
Copyright: © 2021 |Pages: 22
DOI: 10.4018/IJHISI.20211001.oa30
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Abstract

The most important application of voice profiling is pathological voice detection. Parkinson's disease is a chronic neurological degenerative disease affecting the central nervous system responsible for essentially progressive evolution movement disorders. 70% to 90% of Parkinson’s disease (PD) patients show an affected voice. This paper proposes a methodology for PD based on acoustic, glottal, physical, and electrical parameters. The results show that the acoustic parameter is more important in the case of Parkinson’s disease as compared to glottal and physical parameters. The authors achieved 97.2% accuracy to differentiate Parkinson and healthy voice using jitter to pitch ratio proposed algorithm. The Authors also proposed an algorithm of poles calculation of the vocal tract to find formants of the vocal tract. Further, formants are used for finding the transfer function of vocal tract filter. In the end, the authors suggested parameters of the electrical vocal tract model are also changed in the case of PD voices.
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2. Literature Review

Over the years, increasing attention has been given to studying people suffering from PD on the basis of voice and speech patterns (Rusz, 2015; Saxena, 2014). To date, about 90% of PD patients are projected to suffer speech related problems (Little, 2009). Rouzbahani & Daliri (2011) defined a technique to diagnose PD in humans using voice signals. Saloni, et al. (2016) had proposed classifying PD via local angular frequency and instantaneous deviation in the waveform. In advance-stage PD, the voice is often neither audible nor intelligible, thereby leading to deterioration in the functioning of vocal folds. To identify the effects of speech and voice disorders in PD, there are many speaking exercises that could be used. Sustained phonation, freely spoken spontaneous expression are the most traditional of these (Mittal, 2020).

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