Publication detail

Robust and Adaptive Terrain Classification and Gait Event Detection System

SHAIKH, U. SHAHZAIB, M. SHAKIL, S. BHATTI, F. MALIK, A.

Original Title

Robust and Adaptive Terrain Classification and Gait Event Detection System

Type

journal article in Web of Science

Language

English

Original 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.

Keywords

Gait event detection (GED), terrain classification, adaptive.

Authors

SHAIKH, U.; SHAHZAIB, M.; SHAKIL, S.; BHATTI, F.; MALIK, A.

Released

31. 10. 2023

Publisher

Elsevier

Location

Oxford

ISBN

2405-8440

Periodical

Heliyon

Year of study

9

Number

11

State

United States of America

Pages from

1

Pages to

12

Pages count

12

URL

https://www.sciencedirect.com/science/article/pii/S2405844023089284

BibTex

@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",
  issn="2405-8440",
  url="https://www.sciencedirect.com/science/article/pii/S2405844023089284"
}