Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

Journal of the Royal Society Interface

Volumn 8, Issue 59, 2011, Pages 842-855

  Tsanas, Athanasios ^a   Little, Max A ^a   McSharry, Patrick E ^a   Ramig, Lorraine O ^b,c  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF COLORADO   (United States)

^c University of Arizona   (United States)

Author keywords

Nonlinear regression and classification; Nonlinear speech signal processing; Parkinson's disease; Telemedicine; Unified Parkinson's disease rating scale

Indexed keywords

ALGORITHMS; FEATURE EXTRACTION; NEURODEGENERATIVE DISEASES; PARKS; RATING; REGRESSION ANALYSIS; SIGNAL PROCESSING; SPEECH RECOGNITION; TELEMEDICINE;

ANALYSIS ALGORITHMS; CLASSIFICATION ALGORITHM; CLINICAL EVALUATION; CLINICAL TRIAL; LARGE DATABASE; NON-LINEAR REGRESSION; NON-LINEAR SIGNAL PROCESSING; NON-PARAMETRIC REGRESSION; NONLINEAR SPEECH SIGNAL PROCESSING; OPTIMAL SUBSETS; PARKINSON'S DISEASE; ROBUST FEATURE SELECTION; SIGNAL PROCESSING ALGORITHMS; SPEECH SIGNAL PROCESSING; SPEECH TESTS; TELE-MONITORING;

SPEECH COMMUNICATION;

ACCURACY; ADULT; ALGORITHM; ARTICLE; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; CLINICAL ASSESSMENT; CONTROLLED STUDY; DATA BASE; DISEASE SEVERITY; FEMALE; HUMAN; MALE; MULTICENTER STUDY; NONLINEAR SYSTEM; PARKINSON DISEASE; SIGNAL PROCESSING; SPEECH ANALYSIS; TELEMONITORING; UNIFIED PARKINSON DISEASE RATING SCALE;

EID: 79955730724     PISSN: 17425689     EISSN: 17425662     Source Type: Journal    
DOI: 10.1098/rsif.2010.0456     Document Type: Article

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