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A Mobile Application for Detection of Amyotrophic Lateral Sclerosis via Voice Analysis

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Speech and Computer (SPECOM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12997))

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Abstract

Analysis of the state of the art in the field of treatment and diagnosis of a rapidly progressing neurological disease of the amyotrophic lateral sclerosis (ALS) revealed a lack of tools for early diagnosis and monitoring the course of the disease. This paper proposes a method for evaluating the state of the voice function of patients with ALS, intended for use in a mobile application. As a speech probe a long pronunciation of the vowel sound / a / is used from which acoustic features (jitter, shimmer, degree of vibrato pathology, etc.) are extracted. Applying a classifier based on the method of linear discriminant analysis to the obtained vector of parameters, it is possible to obtain an estimate whether the presented voice is pathological and possible progress of the disease. For training and verification of the proposed method, a database of 64 voices (33 healthy, 31 patients with ALS), recorded at the Republican Research and Clinical Center of Neurology and Neurosurgery (Minsk, Belarus), was used. To test the proposed method, a prototype of the mobile application «ALS Expert» was developed with the ability to record, process voice and display the results of voice analysis. The results indicate that the acoustic analysis of the voice and the resulting objective parameters are a promising direction for solving this problem.

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Notes

  1. 1.

    https://github.com/Mak-Sim/Troparion.

  2. 2.

    https://github.com/Mak-Sim/Minsk2020_ALS_database.

  3. 3.

    https://drive.google.com/file/d/14U-t2ajWX5ILfNWx9hBZG1UfpHlhW197/view?usp=sharing.

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Authors and Affiliations

  1. Belarusian State University of Informatics and Radioelectronics, 6 P. Brovky Street, 220013, Minsk, Belarus

    Denis Likhachov, Maxim Vashkevich & Elias Azarov

  2. Republican Research and Clinical Center of Neurology and Neurosurgery, 24 F. Skoriny Street, 220114, Minsk, Belarus

    Katsiaryna Malhina & Yuliya Rushkevich

Authors
  1. Denis Likhachov
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  2. Maxim Vashkevich
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  3. Elias Azarov
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  4. Katsiaryna Malhina
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  5. Yuliya Rushkevich
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Corresponding author

Correspondence to Denis Likhachov .

Editor information

Editors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexey Karpov

  2. Moscow State Linguistic University, Moscow, Russia

    Rodmonga Potapova

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Likhachov, D., Vashkevich, M., Azarov, E., Malhina, K., Rushkevich, Y. (2021). A Mobile Application for Detection of Amyotrophic Lateral Sclerosis via Voice Analysis. In: Karpov, A., Potapova, R. (eds) Speech and Computer. SPECOM 2021. Lecture Notes in Computer Science(), vol 12997. Springer, Cham. https://doi.org/10.1007/978-3-030-87802-3_34

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  • DOI: https://doi.org/10.1007/978-3-030-87802-3_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87801-6

  • Online ISBN: 978-3-030-87802-3

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