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A Cyber-Physical-Human System design for challenging behaviour monitoring in people with dementia

  • University of Groningen, University Medical Center Groningen, Department of Primary and Long-term Care
  • University of Groningen, University Medical Center Groningen, Faculty of Medical Sciences, Department of General Practice, Geriatrics
  • Federal University of Espírito (UFES), Department of Electrical Engineering, LabTeL - Telecommunications Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic

Abstract

The demand for assistive technology is expected to rise alongside the increasing care needs of aging populations. Ambient intelligence, particularly context awareness, offers potential benefits in addressing challenges faced by the healthcare system. In dementia care, context awareness can facilitate early detection of behavioural issues and proactive management of challenging behaviours. This paper presents a context-aware Cyber-Physical-Human System designed to monitor challenging behaviours in individuals with dementia. The system provides caregivers with interpretable situational information and enables them to personalize situational awareness. Designed for integration within nursing homes, it continuously monitors behaviour and influencing factors of behaviours in people with dementia. The system is built on three pillars: a digital twin of people and their environment, an Internet of Health Things (IoHT) infrastructure, and artificial agents. The integration of artificial agents enables near real-time calibration, ensuring situations are adequately communicated with caregivers. An initial implementation was evaluated in a Dutch nursing-home pilot, where IoT-integrated sensors recorded sound, light, climate conditions, activity, and heart rate. Caregivers contributed by conducting behavioural assessments using a custom-developed digital annotation application. Future work will focus on developing methods for real-time calibration by the proposed artificial agents to enhance the reliability of context awareness.
Original languageEnglish
Title of host publicationSensor-Based Activity Recognition and Artificial Intelligence
Subtitle of host publication10th International Workshop, iWOAR 2025 Enschede, The Netherlands, September 18–19, 2025
PublisherSpringer Nature
Pages99-115
Number of pages17
ISBN (Electronic)978-3-032-13312-0
ISBN (Print)978-3-032-13311-3
DOIs
Publication statusPublished - 2 Jan 2026
EventiWOAR 2025: 10th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence - University of Twente, Enschede, Netherlands
Duration: 18 Sept 2025 → 19 Sept 2025
https://iwoar.org/2025/index.html

Publication series

SeriesLecture Notes in Computer Science
Number16292
ISSN0302-9743

Workshop

WorkshopiWOAR 2025
Country/TerritoryNetherlands
CityEnschede
Period18/09/25 → 19/09/25
Internet address

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 03 - Good Health and Well-being
    SDG 03 Good Health and Well-being
  2. SDG 09 - Industry, Innovation, and Infrastructure
    SDG 09 Industry, Innovation, and Infrastructure

Keywords

  • artificial agents
  • challenging behaviour
  • cyber physical human system
  • digital twin
  • nursing home care

Research Focus Areas Hanze University of Applied Sciences * (mandatory by Hanze)

  • Healthy Ageing

Research Focus Areas Research Centre or Centre of Expertise * (mandatory by Hanze)

  • Artificial Intelligence
  • Cyberfysical systems

Publinova themes

  • ICT and Media
  • Technology
  • Health

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