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Design of a Virtual Reality System for Affect Analysis in Facial Expressions (VR-SAAFE); Application to Schizophrenia

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PubDate: July 2016

Teams: Vanderbilt University

Writers: E. Bekele ; D. Bian ; J. Peterman ; S. Park ; N. Sarkar

PDF: Design of a Virtual Reality System for Affect Analysis in Facial Expressions (VR-SAAFE); Application to Schizophrenia

Abstract

Schizophrenia is a life-long, debilitating psychotic disorder with poor outcome that affects about 1% of the population. Although pharmacotherapy can alleviate some of the acute psychotic symptoms, residual social impairments present a significant barrier that prevents successful rehabilitation. With limited resources and access to social skills training opportunities, innovative technology has emerged as a potentially powerful tool for intervention. In this paper, we present a novel virtual reality (VR)-based system for understanding facial emotion processing impairments that may lead to poor social outcome in schizophrenia. We henceforth call it a VR System for Affect Analysis in Facial Expressions (VR-SAAFE). This system integrates a VR-based task presentation platform that can minutely control facial expressions of an avatar with or without accompanying verbal interaction, with an eye-tracker to quantitatively measure a participants real-time gaze and a set of physiological sensors to infer his/her affective states to allow in-depth understanding of the emotion recognition mechanism of patients with schizophrenia based on quantitative metrics. A usability study with 12 patients with schizophrenia and 12 healthy controls was conducted to examine processing of the emotional faces. Preliminary results indicated that there were significant differences in the way patients with schizophrenia processed and responded towards the emotional faces presented in the VR environment compared with healthy control participants. The preliminary results underscore the utility of such a VR-based system that enables precise and quantitative assessment of social skill deficits in patients with schizophrenia.

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