DCU study outlines AI independent living solution for older adults

The system integrates various technologies such as smartwatches, voice-activated assistants, contact sensors, and smart plugs to gather comprehensive data on users’ activities and environments. This system uses AI and machine learning algorithms to analyze this data, enabling the detection and prediction of changes in the routines of older adults. To address privacy and security concerns the system was designed to be highly customizable, giving users autonomy over the components they chose to use.

The development of the NEX system was carried out in 3 key phases with a strong focus on diverse stakeholder involvement. The initial exploratory phase recruited 17 participants, including older adults and family caregivers. The subsequent co-design and testing phase expanded the scope of the consultation to include a comprehensive web-based survey completed by 380 older adults, family caregivers, health care professionals, and home care support staff.

This phase also included prototype testing at home by 7 older adults to assess technology needs, requirements, and the initial acceptability of the system. Finally, workshops were held between academic and industry partners to analyze data collected in the earlier stages and to discuss recommendations for the future development of the system.

The project brings together researchers from the School of Psychology, School of Computing, Insight and the School of Health and Human Performance, as well as RSCI and the Royal College of Physicians.