COMPARATIVE STUDY
JOURNAL ARTICLE
RESEARCH SUPPORT, N.I.H., EXTRAMURAL
Add like
Add dislike
Add to saved papers

IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms.

Gait & Posture 2018 July
BACKGROUND: Inertial Measurement Unit (IMU)-based gait analysis algorithms have previously been validated in healthy controls. However, little is known about the efficacy, performance, and applicability of these algorithms in clinical populations with gait deviations such as lower limb prosthesis users (LLPUs).

RESEARCH QUESTION: To compare the performance of 3 different IMU-based algorithms to demarcate steps from LLPUs.

METHODS: We used a single IMU sensor affixed to the midline lumbopelvic region of 17 transtibial (TTA), 16 transfemoral (TFA) LLPUs, and 14 healthy controls (HC). We collected acceleration and angular velocity data during overground walking trials. Step demarcation was evaluated based on fore-aft acceleration, detecting either: (i) maximum acceleration peak, (ii) zero-crossing, or (iii) the peak immediately preceding a zero-crossing. We quantified and compared the variability (standard deviation) in acceleration waveforms from superposed step intervals, and variability in step duration, by each algorithm.

RESULTS: We found that the zero-crossing algorithm outperformed both peak detection algorithms in 65% of TTAs, 81% of TFAs, and 71% of HCs, as evidenced by lower standard deviations in acceleration, more consistent qualitative demarcation of steps, and more normally distributed step durations.

SIGNIFICANCE: The choice of feature-based algorithm with which to partition IMU waveforms into individual steps can affect the quality and interpretation of estimated gait spatiotemporal metrics in LLPUs. We conclude that the fore-aft acceleration zero-crossing serves as a more reliable feature for demarcating steps in the gait patterns of LLPUs.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app