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Unstable gait is a risk factor for falls. Wearable accelerometers enable remote monitoring of daily walking. Here, new methods for measuring stride-to-stride oscillations are validated against optical motion capture, normative data determined, and dependency on walking speed investigated. Walks by 13 young people (mean age 32 years) at fast, usual, and slow speeds were completed. Accelerometers were attached to the head and pelvis and stride-to-stride oscillation velocity and displacement were measured. Continuous tilt corrections were applied, filter cut-offs scaled by step frequency, and thresholds optimized using optical motion capture as a reference. Oscillations depended on walking speed, accelerometer placement, and measurement axis. Vertical oscillations increased with walking speed (Pearson's r = 0.78-0.89) and were the most accurate (1.4-2.3% error). Mediolateral or anterioposterior oscillations were less accurate (5.9-19.5% error) and had more complex relationships with walking speed (increasing, decreasing, uncorrelated, and/or 'U-shaped' minimum at usual speed). In healthy gait, the head and pelvis undergo regular oscillations, measurable with accelerometers. The results suggest head oscillations in the transverse plane are attenuated by the trunk, and there may be advantages in minimizing stride-to-stride oscillations that coincide with self-selected usual pace. These methods may prove useful for remote assessment of changing health, mental status, and/or fall risk.
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Brodie et al. (2015) studied this question.
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