Therapy Progress Indicator (TPI): Combining speech parameters and the subjective unit of distress

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

A posttraumatic stress disorder (PTSD) is a severe handicap in daily life and its treatment is complex. To evaluate the success of treatments, an objective and unobtrusive expert system was envisioned: an therapy progress indicator (TPI). Speech was considered as an excellent candidate for providing an objective, unobtrusive emotion measure. Speech of 26 PTSD patients was recorded while they participated in two reliving sessions: re-experiencing their last panic attack and their last joyful occasion. As a subjective measure, the subjective unit of distress was determined, which enabled the validation of derived speech features. A set of parameters of the speech features: signal, power, zero crossing ratio, and pitch, was found to discriminate between the two sessions. A regression model involving these parameters was able to distinguish between positive and negative distress. This model lays the foundation for an TPI for patients with PTSD, which enables objective and unobtrusive evaluations of therapies.

Original languageEnglish
Title of host publicationProceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009
Publication date2009
Article number5349554
ISBN (Print)9781424447992
DOIs
Publication statusPublished - 2009
Event2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009 - Amsterdam, Netherlands
Duration: 10 Sep 200912 Sep 2009

Conference

Conference2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009
LandNetherlands
ByAmsterdam
Periode10/09/200912/09/2009
Sponsorhumaine, University of Twente, GaTE - Game research for training and entertainment, Philips, IOP - Mens-Machine Interactie
SeriesProceedings - 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009

ID: 337216668