Authors:
Frans Van der Sluis
1
;
Egon L. van den Broek
2
and
Ton Dijkstra
3
Affiliations:
1
Human-Media Interaction (HMI), University of Twente, Netherlands
;
2
Human-Centered Computing Consultancy (H-CCC), Netherlands
;
3
Donders Institute for Brain, Cognition, and Behavior, Radboud University, Netherlands
Keyword(s):
Stress, Diagnosis, Indicator, Speech.
Related
Ontology
Subjects/Areas/Topics:
Affective Computing
;
Biomedical Engineering
;
Health Information Systems
;
Support for Clinical Decision-Making
;
Telemedicine
Abstract:
People who suffer from a stress disorder have a severe handicap in daily life. In addition, stress disorders are complex and consequently, hard to define and hard to treat. Semi-automatic assistance was envisioned that helps in the treatment of a stress disorder. Speech was considered to provide an excellent tool for providing an objective, unobtrusive emotion measure. Speech from 25 patients suffering from a stress disorder was recorded while they participated in two storytelling sessions. The Subjective Unit of Distress (SUD) was determined as a subjective measure and enabled the validation of the derived speech features. A regression model with four speech parameters (i.e., signal, power, zero crossing ratio, and pitch), was able to explain 70% of the variance in the SUD measure. As such it lays the foundation for semi-automated assistance for the treatment of patients with stress disorders.