Participatory Design for Mental Health Data Visualization on a Social Robot

TL;DR

This paper explores using participatory design to develop mental health data visualizations on social robots, aiming to enhance understanding and communication of mental health data through HRI.

Contribution

It introduces a novel participatory design approach for visualizing mental health data on social robots, advancing HRI and data visualization integration.

Findings

Developed initial mental health data visualizations on a social robot

Demonstrated feasibility of participatory design in HRI contexts

Laid groundwork for future research in robot-based data visualization

Abstract

The intersection of data visualization and human-robot interaction (HRI) is a burgeoning field. Understanding, communicating, and processing different kinds of data for creating versatile visualizations can benefit HRI. Conversely, expressing different kinds of data generated from HRI through effective visualizations can provide interesting insights. Our work adds to the literature of this growing domain. In this paper, we present our exploratory work on visualizing mental health data on a social robot. Particularly, we discuss development of mental health data visualizations using a participatory design (PD) approach. As a first step with mental health data visualization on a social robot, this work paves the way for relevant further work and using social robots as data visualization tools.