Result Details
Robust and Adaptive Terrain Classification and Gait Event Detection System
SHAHZAIB, M.
Shakil Sadia, Dr., M.Sc.
BHATTI, F.
Malik Aamir Saeed, prof., Ph.D., DCSY (FIT)
Real-time gait event detection (GED) system can be utilized for gait analysis and tracking fitness activities. GED for various types of terrains (e.g., stair-walk, uneven surfaces, etc.) is still an open research problem. This study presents an inertial sensor-based approach for real-time GED system that works for diverse terrains in an uncontrolled environment. The GED system classifies three types of terrains, i.e., flat-walk, stair-ascend and stair-descend, with an average classification accuracy of 99%. It also accurately detects various gait events, including, toe-strike, heel-rise, toe-off, and heel-strike. It is computationally efficient, implemented on a low-cost microcontroller, works in real-time and can be used in portable rehabilitation devices for use in dynamic environments.
Gait event detection (GED), terrain classification, adaptive.
@article{BUT185297,
author="SHAIKH, U. and SHAHZAIB, M. and SHAKIL, S. and BHATTI, F. and MALIK, A.",
title="Robust and Adaptive Terrain Classification and Gait Event Detection System",
journal="Heliyon",
year="2023",
volume="9",
number="11",
pages="1--12",
doi="10.1016/j.heliyon.2023.e21720",
url="https://www.sciencedirect.com/science/article/pii/S2405844023089284"
}