Background: Although the magnitude of ankle motion is influenced by joint congruence and ligament elasticity, there is a lack of understanding on ankle stiffness between subjects with and without flat foot.
Objective: This study investigated a quantified ankle stiffness difference between subjects with and without flat foot.
Methods: There were forty-five age- and gender-matched subjects who participated in the study. Each subject was seated upright with the tested foot held firmly onto a footplate that was attached to a torque sensor by the joint-driving device.
Results: The flat foot group (mean ± standard deviation) demonstrated increased stiffness during ankle dorsiflexion (0.37 ± 0.16 for flat foot group, 0.28 ± 0.10 for control group; t=-2.11, p=0.04). However, there was no significant group difference during plantar flexion (0.35 ± 0.15 for flat foot group, 0.33 ± 0.07 for control group; t=0.64, p=0.06).
Conclusion: The results of this study indicated that the flat foot group demonstrated increased ankle stiffness during dorsiflexion regardless of demographic factors. This study highlights the need for kinematic analyses and joint stiffness measures during ankle dorsiflexion in subjects with flat foot.
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http://dx.doi.org/10.1016/j.foot.2015.11.003 | DOI Listing |
Primates
January 2025
Laboratory of Biological Anthropology, Graduate School of Human Sciences, Osaka University, Suita, Osaka, Japan.
Gibbons, a type of lesser ape, are brachiators but also walk bipedally and without forelimb assistance, not only on the ground but also on tree branches. The arboreal bipedal walking strategy of the gibbons has been studied in previous studies in relation to two-dimensional (2D) kinematic analysis. However, because tree branches and the ground differ greatly in width, leading to a constrained foot contact point on the tree branches, gibbons must adjust their 3D joint motions of trunk and hindlimb on the tree branches.
View Article and Find Full Text PDFClin Biomech (Bristol)
January 2025
Ohio State University Wexner Medical Center, Department of Orthopaedics, Columbus, OH, USA. Electronic address:
Background: Low back pain affects over 80 % of adults, with sacroiliac joint dysfunction accounting for 15-30 % of these cases. Sacroiliac fusion is a surgical procedure for refractory joint pain. While the biomechanics of the joint and its fusion relative to the spinal column are well-known, the hip-spine relationship post-fusion remains unclear.
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Unlabelled: A weight-bearing lateral radiograph (WBLR) of the foot is a gold standard for diagnosing adult-acquired flatfoot deformity. However, it is difficult to measure the major axis of bones in WBLR without using auxiliary lines. Herein, we develop semantic segmentation with a deep learning model (DLm) on the WBLR of the foot for enhanced diagnosis of pes planus and pes cavus.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Orthopedics, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P. R. China.
Purpose: The present study is to explore the appropriate plantar support force for its effect on improving the collapse of the medial longitudinal arch with flexible flatfoot.
Methods: A finite element model with the plantar fascia attenuation was constructed simulating as flexible flatfoot. The appropriate plantar support force was evaluated.
World J Orthop
December 2024
Department of Orthopaedic Surgery, Massachusetts General Hospital, Boston, MA 02114, United States.
Background: Pes planus (flatfoot) and pes cavus (high arch foot) are common foot deformities, often requiring clinical and radiographic assessment for diagnosis and potential subsequent management. Traditional diagnostic methods, while effective, pose limitations such as cost, radiation exposure, and accessibility, particularly in underserved areas.
Aim: To develop deep learning algorithms that detect and classify such deformities using smartphone cameras.
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