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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Identifying gender-related gait changes offers valuable insights into the role of gender in motor control. It is anticipated that more difficult gait tasks (obstacle crossing) may reveal gender-specific effects on gait parameters. The present study aimed to explore the gait adaptations of male and female participants when stepping over obstacles of 0 cm, 13 cm, 19 cm, and 26 cm in height. A total of 12 male and 12 female participants were recruited. The Vicon motion capture system and AMTI force plates were utilized to obtain the gait parameters. Moreover, spatiotemporal parameters were investigated. Two-way repeated ANOVA (gender × obstacle height) and three-way repeated ANOVA (gender × obstacle height × leg) were performed to compare gait parameters, respectively. Correlations between maximum joint angle and obstacle height were also evaluated. Significant interactions were observed for leading leg swing time, maximum hip extension angle, maximum knee flexion angle, and maximum ankle plantarflexion angle (gender × obstacle height). There were some differences in gait parameters between males and females in the unobstructed gait, and these changes became more evident as obstacle height increased. This study also identified significant differences in gait parameters between leading and trailing legs when stepping over the obstacle.

Details

Title
Gender Differences in Joint Biomechanics During Obstacle Crossing with Different Heights
Author
Wang, Chenyan 1 ; Guo, Yuan 2 ; Du, Weijin 2 ; Li, Zhiqiang 3 ; Chen, Weiyi 2 

 College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, China; [email protected]; College of Artificial Intelligence, Taiyuan University of Technology, Taiyuan 030024, China[email protected] (W.D.) 
 College of Artificial Intelligence, Taiyuan University of Technology, Taiyuan 030024, China[email protected] (W.D.) 
 Shanxi Key Laboratory of Material Strength & Structural Impact, Taiyuan University of Technology, Taiyuan 030024, China; [email protected]; Shanxi Research Center of Basic Discipline of Mechanics, Taiyuan University of Technology, Taiyuan 030024, China; National Demonstration Center for Experimental Mechanics Education, Taiyuan University of Technology, Taiyuan 030024, China 
First page
189
Publication year
2025
Publication date
2025
Publisher
MDPI AG
e-ISSN
23065354
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3170943957
Copyright
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.