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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/38548
Title: Bulbar ALS detection based on analysis of voice perturbation and vibrato
Authors: Vashkevich, M.
Petrovsky, A.
Rushkevich, Y.
Keywords: публикации ученых
acoustic signal processing
bioacoustics, diseases
jitter
medical signal processing
patient diagnosis
speech
speech processing
Issue Date: 2019
Publisher: Poland
Citation: Vashkevich, M. Bulbar ALS Detection Based on Analysis of Voice Perturbation and Vibrato / M. Vashkevich, A. Petrovsky, Y. Rushkevich // Proc. of International Conference Signal Processing Algorithms, Architectures, Arrangements, and Applications (SPA'2019), Poznan, Poland, 18-20 September 2019. – P. 267 – 272. – DOI: 10.23919/SPA.2019.8936657.
Abstract: On average the lack of biological markers causes a one year diagnostic delay to detect amyotrophic lateral sclerosis (ALS). To improve the diagnostic process an automatic voice assessment based on acoustic analysis can be used. The purpose of this work was to verify the suitability of the sustain vowel phonation test for automatic detection of patients with ALS. We proposed enhanced procedure for separation of voice signal into fundamental periods that requires for calculation of perturbation measurements (such as jitter and shimmer). Also we proposed method for quantitative assessment of pathological vibrato manifestations in sustain vowel phonation. The study's experiments show that using the proposed acoustic analysis methods, the classifier based on linear discriminant analysis attains 90.7% accuracy with 86.7% sensitivity and 92.2% specificity.
URI: https://libeldoc.bsuir.by/handle/123456789/38548
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