Literature DB >> 30446216

The effects of knee support on the sagittal lower-body joint kinematics and kinetics of deep squats.

Emily Dooley1, James Carr2, Eric Carson2, Shawn Russell3.   

Abstract

Little work has been done to examine the deep squat position (>130° sagittal knee flexion). In baseball and softball, catchers perform this squat an average of 146 times per nine-inning game. To alleviate some of the stress on their knees caused by this repetitive loading, some catchers wear foam knee supports.
OBJECTIVES: This work quantifies the effects of knee support on lower-body joint kinematics and kinetics in the deep squat position.
METHODS: Subjects in this study performed the deep squat with no support, foam support, and instrumented support. In order to measure the force through the knee support, instrumented knee supports were designed and fabricated. We then developed an inverse dynamic model to incorporate the support loads. From the model, joint angles and moments were calculated for the three conditions.
RESULTS: With support there is a significant reduction in the sagittal moment at the knee of 43% on the dominant side and 63% on the non-dominant side compared to without support. These reductions are a result of the foam supports carrying approximately 20% of body weight on each side.
CONCLUSION: Knee support reduces the moment necessary to generate the deep squat position common to baseball catchers. Given the short moment arm of the patella femoral tendon, even small changes in moment can have a large effect in the tibial-femoral contact forces, particularly at deep squat angles. Reducing knee forces may be effective in decreasing incidence of osteochondritis dissecans.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Baseball catchers; Injury prevention; Knee injury; Knee moment; Osteochondritis dissecans; Squats

Mesh:

Year:  2018        PMID: 30446216     DOI: 10.1016/j.jbiomech.2018.10.024

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  1 in total

1.  A data process of human knee joint kinematics obtained by motion-capture measurement.

Authors:  Jian-Ping Wang; Shi-Hua Wang; Yan-Qing Wang; Hai Hu; Jin-Wei Yu; Xuan Zhao; Jin-Lai Liu; Xu Chen; Yu Li
Journal:  BMC Med Inform Decis Mak       Date:  2021-04-08       Impact factor: 2.796

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.