Robust and Adaptive Terrain Classification and Gait Event Detection System
Date
Authors
Shaikh, UQ
Shahzaib, M
Shakil, S
Bhatti, FA
Aamir Saeed, M
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier BV
Abstract
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.Description
Keywords
4605 Data Management and Data Science, 46 Information and Computing Sciences, 42 Health Sciences, 4207 Sports Science and Exercise, Prevention
Source
Heliyon, ISSN: 2405-8440 (Print), Elsevier BV, 9(11), e21720-e21720. doi: 10.1016/j.heliyon.2023.e21720
Publisher's version
Rights statement
© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).