Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues

TLDR

Falls pose a major health hazard for the elderly and patients with neurodegenerative diseases, prompting extensive research into detection and prevention using smartphone hardware, yet no comprehensive review has been published. This study surveys smartphone-based fall detection and prevention solutions, presenting a taxonomy and systematic comparison of existing approaches. The authors construct a taxonomy and systematically compare studies, analyzing trends in the integration of external sensors with smartphones. The review identifies three challenges and three open issues, and shows a trend toward incorporating external sensing units to improve system usability.

Abstract

This paper presents a state-of-the-art survey of smartphone (SP)-based solutions for fall detection and prevention. Falls are considered as major health hazards for both the elderly and people with neurodegenerative diseases. To mitigate the adverse consequences of falling, a great deal of research has been conducted, mainly focused on two different approaches, namely, fall detection and fall prevention. Required hardware for both fall detection and prevention are also available in SPs. Consequently, researchers’ interest in finding SP-based solutions has increased dramatically over recent years. To the best of our knowledge, there has been no published review on SP-based fall detection and prevention. Thus in this paper, we present the taxonomy for SP-based fall detection and prevention solutions and systematic comparisons of existing studies. We have also identified three challenges and three open issues for future research, after reviewing the existing articles. Our time series analysis demonstrates a trend towards the integration of external sensing units with SPs for improvement in usability of the systems.