Robust and Adaptive Terrain Classification and Gait Event Detection System
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Shaikh, UQ
Shahzaib, M
Shakil, S
Bhatti, FA
Aamir Saeed, M
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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.
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4605 Data Management and Data Science, 46 Information and Computing Sciences, 42 Health Sciences, 4207 Sports Science and Exercise, Prevention
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Heliyon, ISSN: 2405-8440 (Print), Elsevier BV, 9(11), e21720-e21720. doi: 10.1016/j.heliyon.2023.e21720
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© 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/).
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Except where otherwise noted, this item's license is described as © 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/).