Wearable sensors measuring bodily movements used in free-living conditions may help predict falls in older persons. Assessing their use in this context is essential to identify potential challenges related to fall risk screening. Therefore, this study aimed to assess the feasibility of conducting a prospective study comparing self-rated and wearable sensor-based measures for the assessment and prediction of falls in older persons in free-living conditions. A prospective pilot and feasibility study was conducted in six municipalities in Sweden. Data was collected using a systematic questionnaire, a fall journal, a wearable sensor, and a research log. Data from 32 older persons (median age 81 years, 63% women) who completed a six-month fall journal were included in the statistical analysis. The proportion of persons interested in participating in the study varied, ranging from 5% to 73%. Several problems were identified regarding data collection and technical equipment. In total, 51% of the participants obtained a complete set of data on the first try using the wearable sensor. Maximal angular velocity was higher for fallers than non-fallers (p=0.054). The study was considered feasible; however, the issues that arose need to be addressed, emphasising the need for pilot and feasibility studies before undertaking a large-scale study using these technologies in new settings. This study underscores the importance of person-centred data collection processes. Further studies should confirm whether maximal angular velocity could be a predictor of future falls. • Using wearable sensors to assess fall risk under free-living conditions is feasible. • When wearable sensors are used in a new context, various challenges arise. • Data collection using wearable sensors needs to be person-centred.
Törnblom et al. (Sun,) studied this question.