JOURNAL ARTICLE
IMPACT OF FOOTWEAR BENDING STIFFNESS ON LOWER-LIMB WORK REDISTRIBUTION AND RUNNING ECONOMY.
Published In: Journal of Mechanics in Medicine & Biology, 2024, v. 24, n. 8. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: LIU, ZUOLIANG; Yang, Fan; MA, RUIYA; Ding, Li 3 of 3
Abstract
The bending stiffness of footwear impacts running efficiency and lower-limb work redistribution. However, studies integrating both aspects are scarce. This study aimed to examine the impact of footwear stiffness on lower-limb biomechanics, joint work, and overall metabolic efficiency. This study was performed on 12 male recreational runners to complete an experimental protocol while wearing two different running shoes with varying degrees of longitudinal bending stiffness. Paired-sample t tests were applied in this research. The stiffer footwear decreased the range of motion (ROM), angular velocity, negative and positive work of the metatarsophalangeal (MTP) joint, and ROM of the ankle joint. The running economy significantly improved with the stiffer footwear. However, no significant difference was observed in the joint work of other lower limbs. Shoes with increased bending stiffness significantly reduced the MTP joint ROM and angular velocity, thereby reducing negative power and work at the MTP joint and improving running economy for runners. This study provided relevant information for shoe designers, developers, and scientists conducting research on footwear midsole structures and designs. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Mechanics in Medicine & Biology. 2024/10, Vol. 24, Issue 8, p1
- Document Type:Article
- Subject Area:Biology
- Publication Date:2024
- ISSN:0219-5194
- DOI:10.1142/S021951942440044X
- Accession Number:180858101
- Copyright Statement:Copyright of Journal of Mechanics in Medicine & Biology is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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