• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

肌肉与肢体力学

Muscle and Limb Mechanics.

作者信息

Tsianos George A, Loeb Gerald E

机构信息

Rimkus Consulting Group, Inc., San Diego, California, USA.

Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.

出版信息

Compr Physiol. 2017 Mar 16;7(2):429-462. doi: 10.1002/cphy.c160009.

DOI:10.1002/cphy.c160009
PMID:28333378
Abstract

Understanding of the musculoskeletal system has evolved from the collection of individual phenomena in highly selected experimental preparations under highly controlled and often unphysiological conditions. At the systems level, it is now possible to construct complete and reasonably accurate models of the kinetics and energetics of realistic muscles and to combine them to understand the dynamics of complete musculoskeletal systems performing natural behaviors. At the reductionist level, it is possible to relate most of the individual phenomena to the anatomical structures and biochemical processes that account for them. Two large challenges remain. At a systems level, neuroscience must now account for how the nervous system learns to exploit the many complex features that evolution has incorporated into muscle and limb mechanics. At a reductionist level, medicine must now account for the many forms of pathology and disability that arise from the many diseases and injuries to which this highly evolved system is inevitably prone. © 2017 American Physiological Society. Compr Physiol 7:429-462, 2017.

摘要

对肌肉骨骼系统的认识已从在高度受控且往往不符合生理条件的高度特定实验准备中收集个体现象发展而来。在系统层面,现在有可能构建现实肌肉动力学和能量学的完整且合理准确的模型,并将它们结合起来以理解执行自然行为的完整肌肉骨骼系统的动力学。在还原论层面,有可能将大多数个体现象与解释它们的解剖结构和生化过程联系起来。仍然存在两大挑战。在系统层面,神经科学现在必须解释神经系统如何学会利用进化融入肌肉和肢体力学中的许多复杂特征。在还原论层面,医学现在必须解释这个高度进化的系统不可避免易患的许多疾病和损伤所导致的多种形式的病理和残疾。© 2017美国生理学会。《综合生理学》7:429 - 462, 2017。

相似文献

1
Muscle and Limb Mechanics.肌肉与肢体力学
Compr Physiol. 2017 Mar 16;7(2):429-462. doi: 10.1002/cphy.c160009.
2
Biotensegrity and myofascial chains: A global approach to an integrated kinetic chain.生物张力与肌筋膜链:整体观视角下的整合运动链
Med Hypotheses. 2018 Jan;110:90-96. doi: 10.1016/j.mehy.2017.11.008. Epub 2017 Nov 20.
3
Muscle-Tendon-Enthesis Unit.肌肉-肌腱-附着点单元
Semin Musculoskelet Radiol. 2018 Jul;22(3):263-274. doi: 10.1055/s-0038-1641570. Epub 2018 May 23.
4
Bilateral reaching to asymmetrical targets: muscle and joint dynamic interlimb adaptations.双侧伸向不对称目标:肌肉和关节的动态肢体间适应性变化
Res Q Exerc Sport. 1998 Dec;69(4):344-54. doi: 10.1080/02701367.1998.10607709.
5
Stiffness modulation of redundant musculoskeletal systems.冗余肌肉骨骼系统的刚度调节。
J Biomech. 2019 Mar 6;85:101-107. doi: 10.1016/j.jbiomech.2019.01.017. Epub 2019 Jan 22.
6
Effects of distal and proximal arm muscles fatigue on multi-joint movement organization.远端和近端手臂肌肉疲劳对多关节运动组织的影响。
Exp Brain Res. 2006 Apr;170(4):438-47. doi: 10.1007/s00221-005-0227-3. Epub 2005 Dec 21.
7
I.3. Dynamics of human movement.I.3. 人体运动动力学
Stud Health Technol Inform. 2010;152:27-44.
8
Modeling and simulation of musculoskeletal system of human lower limb based on tensegrity structure.基于张拉整体结构的人体下肢肌肉骨骼系统建模与仿真
Comput Methods Biomech Biomed Engin. 2019 Dec;22(16):1282-1293. doi: 10.1080/10255842.2019.1661389. Epub 2019 Sep 5.
9
Lyapunov function and the basin of attraction for a single-joint muscle-skeletal model.单关节肌肉骨骼模型的李雅普诺夫函数与吸引域
J Math Biol. 2007 Apr;54(4):453-64. doi: 10.1007/s00285-006-0052-8.
10
Network structure of the human musculoskeletal system shapes neural interactions on multiple time scales.人体肌肉骨骼系统的网络结构塑造了多个时间尺度上的神经相互作用。
Sci Adv. 2018 Jun 27;4(6):eaat0497. doi: 10.1126/sciadv.aat0497. eCollection 2018 Jun.

引用本文的文献

1
Reassessment of isometric muscle force complexity under different contraction intensities, joint angles, and visual feedback conditions.不同收缩强度、关节角度和视觉反馈条件下等长肌力复杂性的重新评估。
Eur J Appl Physiol. 2025 Jul 1. doi: 10.1007/s00421-025-05880-5.
2
The spinal premotor network driving scratching flexor and extensor alternation.驱动搔抓时屈肌和伸肌交替运动的脊髓运动前网络。
Cell Rep. 2025 Jun 17;44(6):115845. doi: 10.1016/j.celrep.2025.115845.
3
VR Head Tracking as a Useful Tool for the Qualitative Assessment of Cervical Spine Movement.
虚拟现实头部追踪作为颈椎运动定性评估的有用工具
Sensors (Basel). 2025 Mar 29;25(7):2172. doi: 10.3390/s25072172.
4
The spinal premotor network driving scratching flexor and extensor alternation.驱动搔抓屈肌和伸肌交替的脊髓运动前网络。
bioRxiv. 2025 Jan 8:2025.01.08.631866. doi: 10.1101/2025.01.08.631866.
5
Express Visuomotor Responses Reflect Knowledge of Both Target Locations and Contextual Rules during Reaches of Different Amplitudes.在不同幅度的伸展过程中,表达性运动反应反映了对目标位置和上下文规则的双重认知。
J Neurosci. 2023 Oct 18;43(42):7041-7055. doi: 10.1523/JNEUROSCI.2069-22.2023. Epub 2023 Sep 15.
6
The 'Postural Rhythm' of the Ground Reaction Force during Upright Stance and Its Conversion to Body Sway-The Effect of Vision, Support Surface and Adaptation to Repeated Trials.直立姿势时地面反作用力的“姿势节律”及其向身体摆动的转换——视觉、支撑面和重复试验适应的影响
Brain Sci. 2023 Jun 21;13(7):978. doi: 10.3390/brainsci13070978.
7
Numerical instability of Hill-type muscle models.Hill 型肌肉模型的数值不稳定性。
J R Soc Interface. 2023 Feb;20(199):20220430. doi: 10.1098/rsif.2022.0430. Epub 2023 Feb 1.
8
Developing Intelligent Robots that Grasp Affordance.开发能够理解可供性的智能机器人。
Front Robot AI. 2022 Jul 5;9:951293. doi: 10.3389/frobt.2022.951293. eCollection 2022.
9
The evolution of human fatigue resistance.人类抗疲劳能力的演变
J Comp Physiol B. 2022 Jul;192(3-4):411-422. doi: 10.1007/s00360-022-01439-4. Epub 2022 May 12.
10
A model for self-organization of sensorimotor function: spinal interneuronal integration.感觉运动功能的自组织模型:脊髓中间神经元整合。
J Neurophysiol. 2022 Jun 1;127(6):1478-1495. doi: 10.1152/jn.00054.2022. Epub 2022 Apr 27.