Factors that Affect Personalization of Robots for Older Adults

TL;DR

This paper presents a taxonomy of key factors influencing the personalization of assistive robots for older adults, based on field studies, to guide deployment in caregiving settings.

Contribution

It introduces a novel taxonomy categorizing factors affecting robot personalization in senior care, derived from empirical field studies.

Findings

Identifies five main categories of factors: users, care partners, robot, facility, external circumstances.

Highlights how these factors influence interaction customization and alert modifications.

Provides a framework for deploying personalized assistive robots in complex caregiving environments.

Abstract

We introduce a taxonomy of important factors to consider when designing interactions with an assistive robot in a senior living facility. These factors are derived from our reflection on two field studies and are grouped into the following high-level categories: primary user (residents), care partners, robot, facility and external circumstances. We outline how multiple factors in these categories impact different aspects of personalization, such as adjusting interactions based on the unique needs of a resident or modifying alerts about the robot's status for different care partners. This preliminary taxonomy serves as a framework for considering how to deploy personalized assistive robots in the complex caregiving ecosystem.