Human-Centered AI for Dementia Care: Using Reinforcement Learning for Personalized Interventions Support in Eating and Drinking Scenarios

Wen-Tseng Chang, Shihan Wang, Stephanie Kramer, Michel Oey, Somaya Ben Allouch

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

For people with early-dementia (PwD), it can be challenging to remember to eat and drink regularly and maintain a healthy independent living. Existing intelligent home technologies primarily focus on activity recognition but lack adaptive support. This research addresses this gap by developing an AI system inspired by the Just-in-Time Adaptive Intervention (JITAI) concept. It adapts to individual behaviors and provides personalized interventions within the home environment, reminding and encouraging PwD to manage their eating and drinking routines. Considering the cognitive impairment of PwD, we design a human-centered AI system based on healthcare theories and caregivers’ insights. It employs reinforcement learning (RL) techniques to deliver personalized interventions. To avoid overwhelming interaction with PwD, we develop an RL-based simulation protocol. This allows us to evaluate different RL algorithms in various simulation scenarios, not only finding the most effective and efficient approach but also validating the robustness of our system before implementation in real-world human experiments. The simulation experimental results demonstrate the promising potential of the adaptive RL for building a human-centered AI system with perceived expressions of empathy to improve dementia care. To further evaluate the system, we plan to conduct real-world user studies.
Original languageEnglish
Title of host publicationHHAI 2024: Hybrid Human AI Systems for the Social Good
Subtitle of host publicationProceedings of the Third International Conference on Hybrid Human-Artificial Intelligence
EditorsFabian Lorig, Jason Tucker, Adam Dahlgren Lindström, Frank Dignum, Pradeep Murukannaiah, Andreas Theodorou, Pinar Yolum
PublisherIOS Press
Pages84-93
Volume386
ISBN (Electronic)9781643685229
DOIs
Publication statusPublished - 2024

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume386
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

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