Automated measurement of head movement synchrony during dyadic depression severity interviews - Robotics Institute Carnegie Mellon University

Automated measurement of head movement synchrony during dyadic depression severity interviews

S. Bhatia, R. Goecke, Z. Hammal, and J. F. Cohn
Conference Paper, Proceedings of 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG '19), pp. 1 - 8, May, 2019

Abstract

With few exceptions, most research in automated assessment of depression has considered only the patient's behavior to the exclusion of the therapist's behavior. We investigated the interpersonal coordination (synchrony) of head movement during patient-therapist clinical interviews. Our sample consisted of patients diagnosed with major depressive disorder. They were recorded in clinical interviews (Hamilton Rating Scale for Depression, HRSD) at 7-week intervals over a period of 21 weeks. For each session, patient and therapist 3D head movement was tracked from 2D videos. Head angles in the horizontal (pitch) and vertical (yaw) axes were used to measure head movement. Interpersonal coordination of head movement between patients and therapists was measured using windowed cross-correlation. Patterns of coordination in head movement were investigated using the peak picking algorithm. Changes in head movement coordination over the course of treatment were measured using a hierarchical linear model (HLM). The results indicated a strong effect for patient-therapist head movement synchrony. Within-dyad variability in head movement coordination was found to be higher than between-dyad variability, meaning that differences over time in a dyad were higher as compared to the differences between dyads. Head movement synchrony did not change over the course of treatment with change in depression severity. To the best of our knowledge, this study is the first attempt to analyze the mutual influence of patient-therapist head movement in relation to depression severity.

BibTeX

@conference{Bhatia-2019-120223,
author = {S. Bhatia and R. Goecke and Z. Hammal and J. F. Cohn},
title = {Automated measurement of head movement synchrony during dyadic depression severity interviews},
booktitle = {Proceedings of 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG '19)},
year = {2019},
month = {May},
pages = {1 - 8},
}