Robust and Adaptive Terrain Classification and Gait Event Detection System

Date
2023-11-01
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
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/).