IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms.
Gerasimos Bastas, Joshua J Fleck, Richard A Peters and 1 others
PMID 29807270WHAT IT FOUND
Zero-crossing algorithms demarcate steps more accurately than peak-detection algorithms for people with lower limb prostheses.
Using the wrong algorithm can distort gait symmetry data, so clinicians should verify the algorithm used by their IMU system.
Key findings
01The zero-crossing algorithm provided the lowest acceleration variability in 64.7% of transtibial and 81.2% of transfemoral amputee subjects, outperforming peak-detection methods.
02Peak-detection algorithms caused large systematic errors in estimating step duration and symmetry for amputees, whereas they performed similarly to zero-crossing methods in healthy controls.
03The study did not compare IMU outputs against ground-truth data like force plates, relying instead on the consistency of the algorithms' own outputs.
STILL TO COME
How it was doneWhat they foundWhat it means for PTsWhat it means for OTs
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What it does not show
The study did not compare IMU results against a gold standard like force plates or motion capture, so it assessed algorithm consistency rather than absolute accuracy. The algorithms primarily analyzed z-axis acceleration, which might miss nuances captured by integrating other axes. The study did not test how sensitive the algorithms are to imperfect sensor placement or variations in belt tightness, which are common in real-world clinical settings. Participants were all K3 or K4 level amputees who could walk without assistive devices, so results may not apply to those with more impaired gait or who use walkers or crutches.
Declared interests
None of the authors reported conflicts of interest.
The easy way to misread this
Do not assume that all IMU systems provide accurate gait symmetry data for amputees. Many commercial systems use peak-detection algorithms, which this study showed can produce large errors in step duration and variability for this population, potentially leading to incorrect clinical conclusions about gait quality.