Assessing fall risk using wearable sensors: a practical discussion

Identification of older people most at risk of falling may facilitate early preventative intervention to reduce the likelihood of falls occurring. While many clinical fall risk assessment techniques exist, they often require subjective assessor interpretation, or are not appropriate for unsupervised screening of larger populations owing to a number of issues including safety, ability to reliably perform the assessment, and requirements for unwieldy apparatus. Researchers have more recently attempted to address some of these deficits by instrumenting new or existing physical fall risk assessments with wearable motion sensors to make such assessments more objective, quicker to administer, and potentially more appropriate for deployment for unsupervised use in the community. The objective of this paper is to discuss various practical questions involving sensor-based fall risk assessment (SFRA). Many of the issues discussed contribute to answering the important question of whether SFRA should or can be used in either a supervised or an unsupervised manner, and what possible deployment scenarios exist for it.