LAUSR

This article discusses the practical applications of artificial intelligence in digital physical activity and falls prevention interventions for older adults. It notes the range of technologies that can be used to collect digital datasets on older adult health and how machine learning algorithms can be applied to these to improve our understanding of physical activity and falls. In particular, these advanced computational techniques could help personalize exercises, feedback, and notifications to older people, improve adherence to and reduce attrition from digital health interventions, and enhance monitoring by providing predictive analytics on the physiological and environmental conditions that contribute to physical activity and falls in aging populations.