Typically, research and industry presented various practical solutions for assisting the elderly and their caregivers against falls via detecting falls and triggering notification alarms calling for help as soon as falls occur to diminish fall consequences. Furthermore, fall likelihood prediction systems have emerged lately based on the manipulation of the medical and behavioral history of elderly patients in order to predict the possibility of falls occurrence. This paper presents an extensive review of the state-of-the-art trends and technologies of fall detection and prevention systems assisting elderly people and their caregivers. Furthermore, this paper discusses the main challenges facing elderly fall prevention, along with a comparison of various machine learning algorithms on the cStick dataset.
Khunteta et al. (2025) studied this question.