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负荷与着陆高度操控后的单腿着陆神经力学数据

Single-leg landing neuromechanical data following load and land height manipulations.

作者信息

Nordin Andrew D, Dufek Janet S

机构信息

University of Michigan, United States.

University of Nevada, Las Vegas, United States.

出版信息

Data Brief. 2016 Jul 16;8:1024-30. doi: 10.1016/j.dib.2016.07.011. eCollection 2016 Sep.

DOI:10.1016/j.dib.2016.07.011
PMID:27508258
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4969247/
Abstract

Lower extremity sagittal kinematic and kinetic data are summarized alongside electrical muscle activities during single-leg landing trials completed in contrasting external load and landing height conditions. Nineteen subjects were analyzed during 9 landing trials in each of 6 experimental conditions computed as percentages of subject anthropometrics (bodyweight: BW and subject height: H; BW, BW+12.5%, BW+25%, and H12.5%, H25%). Twelve lower extremity variables (sagittal hip, knee, ankle angles and moments, vertical ground reaction force (GRFz), gluteus maximus, biceps femoris, vastus medials, medial gastrocnemius, and tibialis anterior muscles) were assessed using separate principal component analyses (PCA). Variable trends across conditions were summarized in "Neuromechanical synergies in single-leg landing reveal changes in movement control. Human Movement Science" (Nordin and Dufek, 2016) [1], revealing changes in landing biomechanics and movement control.

摘要

在不同外部负荷和着陆高度条件下完成的单腿着陆试验中,下肢矢状面运动学和动力学数据与肌肉电活动一同进行了总结。对19名受试者在6种实验条件下的9次着陆试验进行了分析,这些条件以受试者人体测量学指标(体重:BW和受试者身高:H;BW、BW + 12.5%、BW + 25%以及H12.5%、H25%)的百分比来计算。使用单独的主成分分析(PCA)评估了12个下肢变量(矢状面髋关节、膝关节、踝关节角度和力矩、垂直地面反作用力(GRFz)、臀大肌、股二头肌、股内侧肌、腓肠肌内侧头和胫骨前肌)。条件之间的变量趋势总结于《单腿着陆中的神经力学协同作用揭示运动控制的变化。人类运动科学》(诺丁和杜菲克,2016年)[1],揭示了着陆生物力学和运动控制的变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/5ad2a2ecb9ab/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/2222afaa2c19/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/cba0634af1a7/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/8f9a0dac9466/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/ca11bfeab792/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/168e8ab991cf/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/5ad2a2ecb9ab/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/2222afaa2c19/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/cba0634af1a7/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/8f9a0dac9466/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/ca11bfeab792/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/168e8ab991cf/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/189c/4969247/5ad2a2ecb9ab/gr6.jpg

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本文引用的文献

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Hum Mov Sci. 2016 Oct;49:66-78. doi: 10.1016/j.humov.2016.06.007. Epub 2016 Jun 21.
2
Application of principal component analysis in clinical gait research: identification of systematic differences between healthy and medial knee-osteoarthritic gait.主成分分析在临床步态研究中的应用:识别健康和内侧膝骨关节炎步态之间的系统差异。
J Biomech. 2013 Sep 3;46(13):2173-8. doi: 10.1016/j.jbiomech.2013.06.032. Epub 2013 Aug 1.
3
Electromyography normalization methods for high-velocity muscle actions: review and recommendations.
高速肌肉动作的肌电图标准化方法:综述与建议
J Appl Biomech. 2013 Oct;29(5):600-8. doi: 10.1123/jab.29.5.600. Epub 2012 Dec 27.