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UNOBTRUSIVE MONITORING OF SPEECH IMPAIRMENTS OF PARKINSON'S DISEASE PATIENTS THROUGH MOBILE DEVICES

Citation Author(s):
T. Arias-Vergara, J.C. Vásquez-Correa, J.R. Orozco-Arroyave, P. Klumpp, E. Noeth
Submitted by:
Philipp Klumpp
Last updated:
13 April 2018 - 7:08am
Document Type:
Poster
Document Year:
2018
Event:
Presenters:
Philipp Klumpp
Paper Code:
#2184
 

Parkinson’s disease (PD) produces several speech impairments in the patients. Automatic classification of PD patients is performed considering speech recordings collected in non- controlled acoustic conditions during normal phone calls in a unobtrusive way. A speech enhancement algorithm is applied to improve the quality of the signals. Two different classification approaches are considered: the classification of PD patients and healthy speakers and a multi-class experiment to classify patients in several stages of the disease. According to the results it is possible to classify PD patients and healthy controls with a AUC of up to 0.87. This work is a step for- ward to the development of telemonitoring systems to assess the speech of the patients.

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