THERADIA WoZ: An Ecological Corpus for Appraisal-based Affect Research in Healthcare

TL;DR

THERADIA WoZ is an ecological audiovisual corpus capturing affective responses of elderly individuals during cognitive training, annotated with appraisal-based and achievement-related affect labels, facilitating affective computing research in healthcare.

Contribution

This paper introduces THERADIA WoZ, a novel ecological corpus with detailed annotations for affective research in healthcare, including baseline prediction methods.

Findings

Corpus includes 61 participants with detailed audiovisual and affect annotations.

Baseline models for affect prediction show promising results.

The dataset is publicly available for research use.

Abstract

We present THERADIA WoZ, an ecological corpus designed for audiovisual research on affect in healthcare. Two groups of senior individuals, consisting of 52 healthy participants and 9 individuals with Mild Cognitive Impairment (MCI), performed Computerised Cognitive Training (CCT) exercises while receiving support from a virtual assistant, tele-operated by a human in the role of a Wizard-of-Oz (WoZ). The audiovisual expressions produced by the participants were fully transcribed, and partially annotated based on dimensions derived from recent models of the appraisal theories, including novelty, intrinsic pleasantness, goal conduciveness, and coping. Additionally, the annotations included 23 affective labels drew from the literature of achievement affects. We present the protocols used for the data collection, transcription, and annotation, along with a detailed analysis of the annotated dimensions and labels. Baseline methods and results for their automatic prediction are also presented. The corpus aims to serve as a valuable resource for researchers in affective computing, and is made available to both industry and academia.