Dynamic Criterion to Quantify Instability During Locomotion

• Published in: 2024 International Symposium on 3D Analysis of Human Movement (3DAHM) pp. 1 - 5
• Main Authors: Lalles, Ariane, Watier, Bruno, Pillet, Helene
• Format: Conference Proceeding
• Language: English
• Published: IEEE 03.12.2024
• Subjects: acceleration; biomechanics; deceleration; gait; Instruments; Legged locomotion; Mechanical variables measurement; Motion capture; Perturbation methods; Protocols; Real-time systems; risk-of-falls; Robot sensing systems; Sensitivity; Three-dimensional displays; treadmill
• DOI: 10.1109/3DAHM62677.2024.10920803

Despite numerous teams attempted to quantify fall risks during gait, few used dynamic criteria to assess instability. While most studies focused on kinematic criteria (e.g., extrapolated center of mass, virtual pivot point, inverted pendulum model.), this study proposes, based on a theoretical approach, to use a dynamic criterion by measuring the distance between the body center of mass (BCoM) and the minimal moment axis of the external mechanical action applied to the body. This can easily be linked to the variation of the whole-body angular momentum. So far, in this preliminary study, eight asymptomatic volunteers walked on dual-belt instrumented treadmill equipped with two force platforms (Treadmetrix©). This protocol was approved by an ethical committee (RCB 2020-A01357-32). All participants provided their informed consent. A motion capture system (Vicon©) was used to obtain three-dimensional kinematics. After walking at a stable speed (1.2m/ s ), volunteers were subjected to acceleration and deceleration perturbations (3m/ s 2 and 10 m/s2 up to 2.04 and 0.36m/s) causing trips and slips. While participants were informed about the disruptions, no information was given regarding the type and the timing occurrence. Results showed significant variations of the mean and maximal distance during pre-perturbation phases and perturbation phases during both slips (p<0.001) and trips (p<0.001) (10m/s2). Future validation is needed with high-risk individuals to establish thresholds for inevitable falls. In the long run, this could be used to detect in real time with embedded systems people at risk of falls, or in rehabilitation protocols. The results of this study could also benefit to the control of humanoid robots during gait.