Abstract
Motor variability in gait is frequently linked to fall risk, yet field-based biomechanical joint evaluations are scarce. We evaluated the validity and sensitivity of an inertial measurement unit (IMU)-driven biomechanical model of joint angle variability for gait. Fourteen healthy young adults completed seven-minute trials of treadmill gait at several speeds and arm swing amplitudes. Trunk, pelvis, and lower-limb joint kinematics were estimated by IMU- and optoelectronic-based models using OpenSim. We calculated range of motion (ROM), magnitude of variability (meanSD), local dynamic stability (λmax), persistence of ROM fluctuations (DFAα), and regularity (SaEn) of each angle over 200 continuous strides, and evaluated model accuracy (RMSD: root mean square difference), consistency (ICC2,1: intraclass correlation), biases, limits of agreement, and sensitivity to within-participant gait responses (effects of speed and swing). RMSDs of joint angles were 1.7–9.2° (pooled mean of 4.8°), excluding ankle inversion. ICCs were mostly good to excellent in the primary plane of motion for ROM and in all planes for meanSD and λmax, but were poor to moderate for DFAα and SaEn. Modelled speed and swing responses for ROM, meanSD, and λmax were similar. Results suggest that the IMU-driven model is valid and sensitive for field-based assessments of joint angle time series, ROM in the primary plane of motion, magnitude of variability, and local dynamic stability.
Highlights
Possessing too much or too little motor variability, the natural variability in sensorimotor actions [1], is well linked to walking-related fall risk
Fallers exhibit greater stride-to-stride variability in spatiotemporal outputs compared to non-fallers [2,3]. This difference may emerge from altered stride-to-stride joint angle patterns that have been observed with older age, including lower local dynamic stability [4], lower regularity [5], and a shift in the magnitude of variability in ankle motion from the sagittal to the frontal plane [6]
Based on values pooled across conditions, mean root mean squared differences (RMSD) was less than 5◦ for all trunk angles, pelvis AA and internal/external rotation (IE), hip FE, and knee FE, with all other angles except pelvis FE and ankle AA approaching the 5◦ threshold
Summary
Possessing too much or too little motor variability, the natural variability in sensorimotor actions [1], is well linked to walking-related fall risk These actions include whole-body and joint motions that vary over time from stride to stride. Fallers exhibit greater stride-to-stride variability in spatiotemporal outputs (e.g., stride time) compared to non-fallers [2,3] This difference may emerge from altered stride-to-stride joint angle patterns that have been observed with older age, including lower local dynamic stability (measured by the local divergence exponent) [4], lower regularity (measured by the sample entropy) [5], and a shift in the magnitude of variability in ankle motion from the sagittal to the frontal plane (measured by the standard deviation) [6]. Using this motion capture approach, large-scale evaluations of motor variability in realistic and clinically-relevant gait scenarios are infeasible
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