A1 Journal article (refereed)
A novel method for accurate division of the gait cycle into seven phases using shank angular velocity (2024)
Salminen, M., Perttunen, J., Avela, J., & Vehkaoja, A. (2024). A novel method for accurate division of the gait cycle into seven phases using shank angular velocity. Gait and Posture, In Press. https://doi.org/10.1016/j.gaitpost.2024.04.006
JYU authors or editors
Publication details
All authors or editors: Salminen, Mikko; Perttunen, Jarmo; Avela, Janne; Vehkaoja, Antti
Journal or series: Gait and Posture
ISSN: 0966-6362
eISSN: 1879-2219
Publication year: 2024
Volume: In Press
Publisher: Elsevier
Publication country: Netherlands
Publication language: English
DOI: https://doi.org/10.1016/j.gaitpost.2024.04.006
Publication open access: Openly available
Publication channel open access: Partially open access channel
Abstract
Accurate detection of gait events is crucial for gait analysis, enabling the assessment of gait patterns and abnormalities. Inertial measurement unit (IMU) sensors have gained traction for event detection, mainly focusing on initial contact (IC) and toe-off (TO) events. However, effective detection of other key events such as heel rise (HR), feet adjacent (FA), and tibia vertical (TBV) is essential for comprehensive gait analysis.
Research question
Can a novel IMU-based method accurately detect HR, TO, FA, and TBV events, and how does its performance compare with existing methods?
Methods
We developed and validated an IMU-based method using cumulative mediolateral shank angular velocity (CSAV) for event detection. A dataset of nearly 25,000 gait cycles from healthy adults walking at varying speeds and footwear conditions was used for validation. The method’s accuracy was assessed against force plate and motion capture data and compared with existing TO detection methods.
Results
The CSAV method demonstrated high accuracy in detecting TO, FA, and TBV events and moderate accuracy in HR event detection. Comparisons with existing TO detection methods showcased superior performance. The method's stability across speed and shoe variations underscored its robustness.
Significance
This study introduces a highly accurate IMU-based method for detecting gait events needed to divide the gait cycle into seven phases. The effectiveness of the CSAV method in capturing essential events across different scenarios emphasizes its potential applications. Although HR event detection can be further improved, the precision of the CSAV method in TO, FA, and TBV detection advance the field. This study bridges a critical gap in IMU-based gait event detection by introducing a method for subdividing the swing phase into its subphases. Further research can focus on refining HR detection and expanding the method’s utility across diverse gait contexts, thereby enhancing its clinical and scientific significance.
Keywords: walking (motion); performance (capacity); deviance
Free keywords: gait analysis; shank angular velocity; inertial measurement unit (IMU); event detection
Contributing organizations
Ministry reporting: Yes
Preliminary JUFO rating: 1
