Related Experiment Video
Updated: Sep 23, 2025
07:24
Home-Based Monitor for Gait and Activity Analysis
Published on: August 8, 2019
6.8K
Estimation of gait parameters using leg velocity for amputee population
Zohaib Aftab1,2, Rizwan Shad1
1Department of Mechanical Engineering, Faculty of Engineering, University of Central Punjab, Lahore, Pakistan.
Plos One
|May 13, 2022
Summary
Lower-leg angular velocity accurately predicts heel strike and temporal gait parameters in amputees. Toe-off prediction shows higher error, but accuracy improves with prosthetic leg use and mobility level.
Area of Science:
- Biomechanics
- Rehabilitation Engineering
- Clinical Gait Analysis
Background:
- Gait parameter quantification is crucial for assessing gait deficits in clinical research.
- Lower-limb kinematics, particularly leg velocity, show promise for gait parameter estimation but require validation in amputees.
Purpose of the Study:
- To assess the accuracy of lower-leg angular velocity in predicting key gait events (toe-off and heel strike) and temporal parameters in individuals with transfemoral amputation.
- To evaluate the performance of a novel dual-minima algorithm for gait event detection using shank velocity data.
Main Methods:
- Utilized an open dataset of treadmill walking from 10 unilateral transfemoral amputees.
- Developed a rule-based dual-minima algorithm to detect toe-off and heel strike events from shank velocity signals.
- Compared algorithm predictions against force platform data for 3000 walking cycles.
Main Results:
- High accuracy was achieved for heel strike (HS) prediction and step/stride timings (mean errors 0 to -13ms).
- Toe-off (TO) prediction showed greater error (mean 35-81ms), consistently predicting TO earlier than actual.
- Prediction accuracy varied between sound and prosthetic legs, with better TO accuracy on the prosthetic side, and improved with higher K-level mobility.
Conclusions:
- Leg velocity combined with the dual-minima algorithm offers a viable method for predicting temporal gait parameters in transfemoral amputees.
- The algorithm demonstrates varying degrees of accuracy, with notable differences between prosthetic and sound limbs and correlation with mobility levels.
