COMPUTER AIDED DIAGNOSIS FOR MENTAL HEALTH CARE - On the Clinical Validation of Sensitive Machines

Frans van der Sluis, Ton Dijkstra, Egon L. van den Broek

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.

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Paper Citation


in Harvard Style

van der Sluis F., Dijkstra T. and L. van den Broek E. (2012). COMPUTER AIDED DIAGNOSIS FOR MENTAL HEALTH CARE - On the Clinical Validation of Sensitive Machines . In Proceedings of the International Conference on Health Informatics - Volume 1: BSSS, (BIOSTEC 2012) ISBN 978-989-8425-88-1, pages 493-498. DOI: 10.5220/0003891404930498


in Bibtex Style

@conference{bsss12,
author={Frans van der Sluis and Ton Dijkstra and Egon L. van den Broek},
title={COMPUTER AIDED DIAGNOSIS FOR MENTAL HEALTH CARE - On the Clinical Validation of Sensitive Machines},
booktitle={Proceedings of the International Conference on Health Informatics - Volume 1: BSSS, (BIOSTEC 2012)},
year={2012},
pages={493-498},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003891404930498},
isbn={978-989-8425-88-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: BSSS, (BIOSTEC 2012)
TI - COMPUTER AIDED DIAGNOSIS FOR MENTAL HEALTH CARE - On the Clinical Validation of Sensitive Machines
SN - 978-989-8425-88-1
AU - van der Sluis F.
AU - Dijkstra T.
AU - L. van den Broek E.
PY - 2012
SP - 493
EP - 498
DO - 10.5220/0003891404930498