Computer Aided Diagnosis for mental health care: On the Clinical Validation of Sensitive Machines

Sluis van der, Frans and Dijkstra, Ton and Broek van den, Egon L. (2012) Computer Aided Diagnosis for mental health care: On the Clinical Validation of Sensitive Machines. In: International Conference on Health Informatics, HealthInf 2012, 1-4 February 2012, Vilamoura, Algarve, Portugal.

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Abstract:	This study explores the feasibility of sensitive machines; that is, machines with empathic abilities, at least to some extent. A signal processing and machine learning pipeline is presented that is used to analyze data from two studies in which 25 Post-Traumatic Stress Disorder (PTSD) patients participated. The feasibility of speech as a stress detector was validated in a clinical setting, using the Subjective Unit of Distress (SUD). 13 statistical parameters were derived from five speech features, namely: amplitude, zero crossings, power, high-frequency power, and pitch. To achieve a low dimensional representation, a subset of 28 parameters was selected and, subsequently, compressed into 11 principal components (PC). Using a Multi-Layer Perceptron neural network (MLP), the set of 11 PC were mapped upon 9 distinct quantizations of the SUD. The MLP was able to discriminate between 2 stress levels with 82.4% accuracy and up to 10 stress levels with 36.3% accuracy. With stress baptized as being the black death of the 21st century, this work can be conceived as an important step towards computer aided mental health care.
Item Type:	Conference or Workshop Item
Copyright:	© 2012 SciTePress
Faculty:	Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:	Human Media Interaction (HMI)
Link to this item:	http://purl.utwente.nl/publications/79668
Related URL:	http://www.healthinf.biostec.org/
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