Assessment of Parkinson’s disease medication state through automatic speech analysis
| Autor: | Alberto Abad, Isabel Pavão Martins, Rita Cardoso, Joaquim J. Ferreira, Rubén Solera-Ureña, Anna Pompili, Isabel Guimarães, Margherita Fabbri |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Parkinson's disease Degenerative Disorder business.industry Computer science Parkinson’s disease speech Deep learning ON-OFF medication state 05 social sciences Disease medicine.disease Automatic assessment 050105 experimental psychology Task (project management) 03 medical and health sciences 0302 clinical medicine Physical medicine and rehabilitation Feature (computer vision) medicine Automatic speech 0501 psychology and cognitive sciences State (computer science) Artificial intelligence business 030217 neurology & neurosurgery |
| Zdroj: | INTERSPEECH |
| Popis: | Parkinson’s disease (PD) is a progressive degenerative disorder of the central nervous system characterized by motor and nonmotor symptoms. As the disease progresses, patients alternate periods in which motor symptoms are mitigated due to medication intake (ON state) and periods with motor complications (OFF state). The time that patients spend in the OFF condition is currently the main parameter employed to assess pharmacological interventions and to evaluate the efficacy of different active principles. In this work, we present a system that combines automatic speech processing and deep learning techniques to classify the medication state of PD patients by leveraging personal speech-based bio-markers. We devise a speakerdependent approach and investigate the relevance of different acoustic-prosodic feature sets. Results show an accuracy of 90.54% in a test task with mixed speech and an accuracy of 95.27% in a semi-spontaneous speech task. Overall, the experimental assessment shows the potentials of this approach towards the development of reliable, remote daily monitoring and scheduling of medication intake of PD patients. info:eu-repo/semantics/publishedVersion |
| Databáze: | OpenAIRE |
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