Applied Sciences, Vol. 14, Pages 11312: Fall Risk Assessment In Active Elderly Through The Use Of Inertial Measurement Units: Determining The Right Postural Balance Variables And Sensor Locations

Applied Sciences, Vol. 14, Pages 11312: Fall Risk Assessment in Active Elderly Through the Use of Inertial Measurement Units: Determining the Right Postural Balance Variables and Sensor Locations

Applied Sciences doi: 10.3390/app142311312

Authors: Youssef Nkizi Ornwipa Thamsuwan

Falls among the elderly have been a significant public health challenge, with severe consequences for individuals and healthcare systems. Traditional balance assessment methods often lack ecological validity, necessitating more comprehensive and adaptable evaluation techniques. This research explores the use of inertial measurement units to assess postural balance in relation to the Berg Balance Scale outcomes. We recruited 14 participants from diverse age groups and health backgrounds, who performed 14 simulated tasks while wearing inertial measurement units on the head, torso, and lower back. Our study introduced a novel metric, i.e., the volume that envelops the 3-dimensional accelerations, calculated as the convex hull space, and used this metric along with others defined in previous studies. Through logistic regression, we demonstrated significant associations between various movement characteristics and the instances of balance loss. In particular, greater movement volume at the lower back (p = 0.021) was associated with better balance, while root-mean-square lower back angular velocity (p = 0.004) correlated with poorer balance. This study revealed that sensor location and task type (static vs. dynamic) significantly influenced the coefficients of the logistic regression model, highlighting the complex nature of balance assessment. These findings underscore the potential of IMUs in providing detailed objective balance assessments in the elderly by identifying specific movement patterns associated with balance impairment across various contexts. This knowledge can guide the development of targeted interventions and strategies for fall prevention, potentially improving the quality of life for older adults.