Chia Bejarano Noelia, Pedrocchi Alessandra, Nardone Antonio, Schieppati Marco, Baccinelli Walter, Monticone Marco, Ferrigno Giancarlo, Ferrante Simona
Neuroengineering and Medical Robotics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy.
Posture and Movement Laboratory, Division of Physical Medicine and Rehabilitation, Scientific Institute of Veruno, Fondazione Salvatore Maugeri (IRCCS), Veruno, Novara, Italy.
Ann Biomed Eng. 2017 May;45(5):1204-1218. doi: 10.1007/s10439-017-1802-z. Epub 2017 Jan 31.
The aim of this study was to develop a methodology based on muscle synergies to investigate whether rectilinear and curvilinear walking shared the same neuro-motor organization, and how this organization was fine-tuned by the walking condition. Thirteen healthy subjects walked on rectilinear and curvilinear paths. Electromyographic data from thirteen back and lower-limb muscles were acquired, together with kinematic data using inertial sensors. Four macroscopically invariant muscle synergies, extracted through non-negative matrix factorization, proved a shared modular organization across conditions. The fine-tuning of muscle synergies was studied through non-negative matrix reconstruction, applied by fixing muscle weights or activation profiles to those of the rectilinear condition. The activation profiles tended to be recruited for a longer period and with a larger amplitude during curvilinear walking. The muscles of the posterior side of the lower limb were those mainly influenced by the fine-tuning, with the muscles inside the rotation path being more active than the outer muscles. This study shows that rectilinear and curvilinear walking share a unique motor command. However, a fine-tuning in muscle synergies is introduced during curvilinear conditions, adapting the kinematic strategy to the new biomechanical needs.
本研究的目的是开发一种基于肌肉协同作用的方法,以研究直线行走和曲线行走是否共享相同的神经运动组织,以及这种组织如何根据行走条件进行微调。13名健康受试者在直线和曲线路径上行走。采集了来自13块背部和下肢肌肉的肌电图数据,以及使用惯性传感器获取的运动学数据。通过非负矩阵分解提取的四种宏观不变肌肉协同作用,证明了不同条件下存在共享的模块化组织。通过非负矩阵重建研究肌肉协同作用的微调,方法是将肌肉权重或激活模式固定为直线行走条件下的权重或模式。在曲线行走过程中,激活模式倾向于在更长的时间内以更大的幅度被募集。下肢后侧的肌肉是主要受微调影响的肌肉,旋转路径内的肌肉比外部肌肉更活跃。这项研究表明,直线行走和曲线行走共享独特的运动指令。然而,在曲线行走条件下会引入肌肉协同作用的微调,使运动学策略适应新的生物力学需求。