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Year : 2021  |  Volume : 10  |  Issue : 1  |  Page : 54

Evaluating the effect of Parkinson's disease on jitter and shimmer speech features

1 Department of Electrical Engineering, Biomedical Engineering Group, Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Mashhad, Iran
2 Department of Neurology. School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
3 Department of Biomedical Engineering, Islamic Azad University of Mashhad, Mashhad, Iran

Correspondence Address:
Dr. Mohammad-R Akbarzadeh-T
Department of Electrical Engineering, Center of Excellence on Soft Computing and Intelligent Information Processing, Ferdowsi University of Mashhad, Azadi Square, Mashhad
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/abr.abr_254_21

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Background: Parkinson's disease (PD) is a neurological disorder caused by decreasing dopamine in the brain. Speech is one of the first functions that are disrupted. Accordingly, speech features are a promising indicator in PD diagnosis for telemedicine applications. The purpose of this study is to investigate the impact of Parkinson's disease on a minimal set of Jitter and Shimmer voice indicators and studying the difference between male and female speech features in noisy/noiseless environments. Materials and Methods: Our data includes 47 samples from nursing homes and neurology clinics, with 23 patients and 24 healthy individuals. The optimal feature for each category is studied separately for the men's and women's samples. The focus here is on the phonation in which the vowel/a/is expressed by the participants. The main features, including Jitter and Shimmer perturbations, are extracted. To find an optimal pair under both noisy and noiseless circumstance, we use the Relief feature selection strategy. Results: This research shows that the Jitter feature for men and women with Parkinson's is 21 and 33.4, respectively. While the Shimmer feature is 0.1 and 0.06. In addition, by using these two features alone, we reach a correct diagnosis rate of 79% and 81% for noisy and noiseless states, respectively. Conclusion: The PD effects on the speech features can be accurately identified. Evaluating the extracted features suggests that the absolute value of the selected feature in men with PD is higher than for healthy ones. Whereas, in the case of women, this is the opposite.

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