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Factors that Affect Personalization of Robots for Older Adults

Laura Stegner, Emmanuel Senft, Bilge Mutlu

TL;DR

This paper addresses the challenge of personalizing assistive robots for older adults in senior living facilities. It develops a taxonomy of factors by synthesizing two field studies: caregiver-workflow ethnography and Situated Participatory Design with residents using the Stretch RE1 robot. The framework organizes factors into five categories—Primary User, Care partners, Robot, Facility, External Circumstances—and connects them to an interaction component model to guide real-time personalization. It highlights dynamic personalization as essential and discusses practical limitations and directions for deploying personalized robots within complex, multi-stakeholder caregiving ecosystems.

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.

Factors that Affect Personalization of Robots for Older Adults

TL;DR

This paper addresses the challenge of personalizing assistive robots for older adults in senior living facilities. It develops a taxonomy of factors by synthesizing two field studies: caregiver-workflow ethnography and Situated Participatory Design with residents using the Stretch RE1 robot. The framework organizes factors into five categories—Primary User, Care partners, Robot, Facility, External Circumstances—and connects them to an interaction component model to guide real-time personalization. It highlights dynamic personalization as essential and discusses practical limitations and directions for deploying personalized robots within complex, multi-stakeholder caregiving ecosystems.

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.
Paper Structure (14 sections, 2 figures)

This paper contains 14 sections, 2 figures.

Table of Contents

  1. Introduction
  2. Method
  3. Taxonomy
  4. Interaction components
  5. Factors
  6. Primary User (Resident)
  7. Care partners
  8. Robot
  9. Facility
  10. External Circumstances
  11. Discussion
  12. Dynamic Personalization
  13. Perfect Personalization --- A Fool's Errand
  14. Limitations & Future Work

Figures (2)

  • Figure 1: Designing robots to assist residents in senior living facilities necessitates considering a wide range of factors, which we introduce as a taxonomy to guide future researchers. This photograph from one of our field studies is annotated with some considerations for robot design that are based on our taxonomy.
  • Figure 2: Factors to consider when personalizing a robot within the caregiving ecosystem, grouped into five categories.