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Robust and adaptive terrain classification and gait event detection system

UQ. Shaikh, M. Shahzaib, S. Shakil, FA. Bhatti, M. Aamir Saeed

. 2023 ; 9 (11) : e21720. [pub] 20231031

Status not-indexed Language English Country England, Great Britain

Document type Journal Article

Persistent link   https://www.medvik.cz/link/bmc23022596

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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