An I-vector-based approach for discriminating between patients with Parkinson's disease and healthy people

Rania Khaskhoussy; Yassine Ben Ayed

doi:10.1117/12.2623240

4 March 2022 An I-vector-based approach for discriminating between patients with Parkinson's disease and healthy people

Rania Khaskhoussy, Yassine Ben Ayed

Author Affiliations +

Proceedings Volume 12084, Fourteenth International Conference on Machine Vision (ICMV 2021); 120840A (2022) https://doi.org/10.1117/12.2623240
Event: Fourteenth International Conference on Machine Vision (ICMV 2021), 2021, Rome, Italy

Abstract

Parkinson's disease (PD) is one of the neurological disorders that affect the central nervous system leads to cognitive, emotional and speech disorders. Many methods have been proposed over time for discriminating between people with PD and healthy people using signals processing. In this paper, a new approach is defined using i-vector subspace modelling to discriminate healthy people from people with PD. The i-vectors features is one of the crucial parameters that prove promising results in the domain of speech recognition. In this study two i-vectors dimensionality (100 and 200 dimensions) extracted from voice recordings using Gaussian Mixture Models based on Universal Background Model (GMM-UBM) size (64, 128 and 256 Gaussians). To the end, we assess the effect of the i-vectors features by using Support Vector Machine (SVM). The results reveal show that the proposed approach can be strongly recommended for classifying Parkinson's patient from healthy individuals.

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Rania Khaskhoussy and Yassine Ben Ayed "An I-vector-based approach for discriminating between patients with Parkinson's disease and healthy people", Proc. SPIE 12084, Fourteenth International Conference on Machine Vision (ICMV 2021), 120840A (4 March 2022); https://doi.org/10.1117/12.2623240

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