Designing a human-centered intelligent system to monitor & explain abnormal patterns of older adults

• Main Authors: LEE, Min Hun, Siewiorek, Daniel P., Bernardino, Alexandre
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: aging; caregivers; health/assistive technology; older adults; quality of life; remote monitoring; Gerontology; Numerical Analysis and Scientific Computing; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/8462; https://ink.library.smu.edu.sg/context/sis_research/article/9465/viewcontent/3597638.3614501_pv.pdf
• Institution: Singapore Management University

Older adult care technologies are increasingly explored to support the independent living of older adults by monitoring their abnormal activities and informing caregivers to provide intervention if necessary. However, the adoption of these technologies remains challenging due to several factors (e.g. lack of usability). In this work, we present a human-centered, intelligent system for older adult care. Our proposed designs of the system were created based on the findings from a focus group session with caregivers. This system monitors the abnormal activities of an older adult using wireless motion sensors and machine learning models. In addition, unlike previous work that only notifies an outcome of activity recognition and abnormal detection models to a caregiver, the system supports interactive dialogue responses to explain the abnormal activities of an older adult to a caregiver and allow the caregiver to elicit additional information about the older adult and the older adult to proactively share his/her status with the caregiver for an adequate intervention.