JMIR Publications

ABSTRACT

Background:

To identify individual fall risk it is important to understand the complex interplay of fall-related factors.

Objective:

Therefore, the aim of this work is to operationalise a prototypical dynamic fall risk model regarding four ecologically valid real-world scenarios (opening door, slipping, tripping, and usage of public transportation).

Methods:

We will recruit 20 community-dwelling people aged 60 years or older. In order to identify several fall-related intrinsic fall risk factors, appropriate clinical assessments will be selected. The experimental setup is adaptable so that the level of fall risk for each activity and each environmental factor is adjustable. An eight camera motion tracking system will be used to record absolute body motions and limits of stability. All lab experiments will also be recorded by inertial sensors (L5, dominant leg) and video camera. Logistic regression analyses will be used to model the association between risk factors and falls. Continuous fall risk will be modelled by generalised linear regression models using margin of stability as outcome parameter.

Results:

Recruitment and measurement initially began in October 2020 but was halted because of the COVID-19 pandemic. Recruitment and measurements recommenced in October 2022, and by February 2023, 25 of the planned 30 subjects has been measured.

Conclusions:

The setup will enable the analysis of fall events and their circumstances ecologically valid in a laboratory setting and thereby will provide important information to estimate the individual instantaneous fall risk.