Natural Language Analysis to Detect Parkinson’s Disease

Pérez-Toro PA, Vasquez Correa J, Strauß M, Orozco Arroyave JR, Nöth E (2019)


Publication Type: Conference contribution

Publication year: 2019

Journal

Publisher: Springer Verlag

Book Volume: 11697 LNAI

Pages Range: 82-90

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Ljubljana SI

ISBN: 9783030279462

DOI: 10.1007/978-3-030-27947-9_7

Abstract

Parkinson’s disease (PD) is a neuro-degenerative disorder that produces motor and non-motor impairments. Non-motor impairments include communication and mood disorders. Most of the studies in the literature have been focused on the analysis of motor symptoms. However, non-motor signs are also present in most of the cases. This paper addresses the study of language production as a potential tool to diagnose and monitor the neurological state of PD patients. The study proposes the use of natural language processing methods to extract features from transcriptions obtained from spontaneous speech recordings to discriminate between healthy control people and PD patients. The analysis considered classical features such as Bag of Words and Term Frequency-Inverse Document Frequency, along with methods based on word-embeddings. Accuracies of up to 72% are obtained when discriminating between PD patients and healthy subjects, which confirms that there is information embedded in the language production that can be used for the assessment of the disease.

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How to cite

APA:

Pérez-Toro, P.A., Vasquez Correa, J., Strauß, M., Orozco Arroyave, J.R., & Nöth, E. (2019). Natural Language Analysis to Detect Parkinson’s Disease. In Kamil Ekštein (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 82-90). Ljubljana, SI: Springer Verlag.

MLA:

Pérez-Toro, P. A., et al. "Natural Language Analysis to Detect Parkinson’s Disease." Proceedings of the 22nd International Conference on Text, Speech, and Dialogue, TSD 2019, Ljubljana Ed. Kamil Ekštein, Springer Verlag, 2019. 82-90.

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