Fractal features for automatic detection of dysarthria

Taylor Spangler, N. V. Vinodchandran, Ashok K Samal, Jordan R. Green

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Amytrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease. Difficulty articulating speech, dysarthria, is a common early symptom of ALS. Detecting dysarthria currently requires manual analysis of several different speech tasks by pathology experts. This is time consuming and can lead to misdiagnosis. Many existing automatic classification approaches require manually preprocessing recordings, separating individual spoken utterances from a repetitive task. In this paper, we propose a fully automated approach which does not rely on manual preprocessing. The proposed method uses novel features based on fractal analysis. Acoustic and associated articulatory recordings of a standard speech diagnostic task, the diadochokinetic test (DDK), are used for classification. This study's experiments show that this approach attains 90.2% accuracy with 94.2% sensitivity and 85.1% specificity.

Original languageEnglish (US)
Title of host publication2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages437-440
Number of pages4
ISBN (Electronic)9781509041794
DOIs
Publication statusPublished - Apr 11 2017
Event4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017 - Orlando, United States
Duration: Feb 16 2017Feb 19 2017

Publication series

Name2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017

Other

Other4th IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017
CountryUnited States
CityOrlando
Period2/16/172/19/17

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ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications
  • Biomedical Engineering

Cite this

Spangler, T., Vinodchandran, N. V., Samal, A. K., & Green, J. R. (2017). Fractal features for automatic detection of dysarthria. In 2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017 (pp. 437-440). [7897299] (2017 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BHI.2017.7897299