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Published byLee Cameron Modified over 9 years ago
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Dr. Athanasios Tsanas (‘Thanasis’), EPSRC post-doctoral research fellow, Oxford Centre for Industrial and Applied Mathematics & Institute of Biomedical Engineering, University of Oxford Current issues in healthcare 2. Probabilistic Parkinson’s disease detection using speech signals Centre for Doctoral Training in Healthcare Innovation
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The Problem Death of dopaminergic cells in basal ganglia Dopaminergic cells facilitate motor control 60-80% dopaminergic cells have died before clinical diagnosis too late to intercept Parkinson’s disease symptom progression No known biomarker of Parkinson’s disease (PD) Difficult diagnosis: 100% only post-mortem Speech may be one of the earliest indicators of PD onset Early diagnosis can improve the quality of life of PD subjects Optimized treatment (hitherto no known cure available) Possibly surgery at later stages
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Speech signals & PD problems Lungs: inefficient control of expiration Vocal folds: incomplete collision, vortices, aperiodicity Vocal tract: loss of muscle co-ordination
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General methodology Speech signal Extract feature vector Feature selection Report results Statistical machine learning (mapping features PD) Sustained vowel “ahh…”
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Questions What sort of speech characteristics should we be aiming to extract from the signals? Which are the state of the art speech signal processing algorithms, and can you suggest some ways to extend/improve them? Who are the leading researchers/research groups on the topic of mining speech signals for medical information? Hint: background information, and check some useful references: http://people.maths.ox.ac.uk/tsanas/Preprints/DPhil%20thesis.pdf http://people.maths.ox.ac.uk/tsanas/Preprints/DPhil%20thesis.pdf
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