Reducing Slip Risk: A Feasibility Study of Gait Training with Semi-Real-Time Feedback of Foot–Floor Contact Angle

Abstract

Slip-induced falls, responsible for approximately 40% of falls, can lead to severe injuries and in extreme cases, death. A large foot–floor contact angle (FFCA) during the heel-strike event has been associated with an increased risk of slip-induced falls. The goals of this feasibility study were to design and assess a method for detecting FFCA and providing cues to the user to generate a compensatory FFCA response during a future heel-strike event. The long-term goal of this research is to train gait in order to minimize the likelihood of a slip event due to a large FFCA. An inertial measurement unit (IMU) was used to estimate FFCA, and a speaker provided auditory semi-real-time feedback when the FFCA was outside of a 10–20 degree target range following a heel-strike event. In addition to training with the FFCA feedback during a 10-min treadmill training period, the healthy young participants completed pre- and post-training overground walking trials. Results showed that training with FFCA feedback increased FFCA events within the target range by 16% for “high-risk” walkers (i.e., participants that walked with more than 75% of their FFCAs outside the target range) both during feedback treadmill trials and post-training overground trials without feedback, supporting the feasibility of training FFCA using a semi-real-time FFCA feedback system.

Advances in Biomechanics-Based Motion Analysis

“…To meet the huge demands for wearable motion capture and remote motion analysis in healthcare sectors [ 18 , 19 , 20 , 21 ], new trends are emerging to optimize existing motion analysis models or combine them with the novel statistical, machine learning, or deep learning algorithms. Li et al [ 22 ] proposed the use of multivariable linear regression models and a composite index, which was derived from the most significant differences in patients with anterior cruciate ligament deficiency (ACLD) vs. healthy controls, to facilitate the clinical diagnosis of ACLD.…”