Suitability of dysphonia measurements for telemonitoring of Parkinson's disease

Max A. Little, Patrick E. McSharry, Eric J. Hunter, Jennifer Spielman, Lorraine O. Ramig

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We present an assessment of the practical value of existing traditional and non-standard measures for discriminating healthy people from people with Parkinson's disease (PD) by detecting dysphonia. We introduce a new measure of dysphonia, Pitch Period Entropy (PPE), which is robust to many uncontrollable confounding effects including noisy acoustic environments and normal, healthy variations in voice frequency. We collected sustained phonations from 31 people, 23 with PD. We then selected 10 highly uncorrelated measures, and an exhaustive search of all possible combinations of these measures finds four that in combination lead to overall correct classification performance of 91.4%, using a kernel support vector machine. In conclusion, we find that non-standard methods in combination with traditional harmonics-to-noise ratios are best able to separate healthy from PD subjects. The selected non-standard methods are robust to many uncontrollable variations in acoustic environment and individual subjects, and are thus well-suited to telemonitoring applications.
    Original languageEnglish
    Article number4636708
    Pages (from-to)1015-1022
    Number of pages8
    JournalIEEE Transactions on Biomedical Engineering
    Volume56
    Issue number4
    DOIs
    Publication statusPublished - Apr 2009

    Bibliographical note

    © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    Keywords

    • biomedical measurements
    • nervous system
    • speech analysis
    • telemedicine

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