Gabel Charles Philip, Guy Bernard, Mokhtarinia Hamid Reza, Melloh Markus
Research Section, Access Physiotherapy, Coolum Beach 4573, Australia.
Ecole des Mines de Saint-Etienne, Saint Etienne 4200, Loire, France.
World J Orthop. 2021 Jun 18;12(6):360-375. doi: 10.5312/wjo.v12.i6.360.
Slacklining, the neuromechanical action of balance retention on a tightened band, is achieved through self-learned strategies combining dynamic stability with optimal energy expenditure. Published slacklining literature is recent and limited, including for neuromechanical control strategy models. This paper explores slacklining's definitions and origins to provide background that facilitates understanding its evolution and progressive incorporation into both prehabilitation and rehabilitation. Existing explanatory slacklining models are considered, their application to balance and stability, and knowledge-gaps highlighted. Current slacklining models predominantly derive from human quiet-standing and frontal plane movement on stable surfaces. These provide a multi-tiered context of the unique and complex neuro-motoric requirements for slacklining's multiple applications, but are not sufficiently comprehensive. This consequently leaves an incomplete understanding of how slacklining is achieved, in relation to multi-directional instability and complex multi-dimensional human movement and behavior. This paper highlights the knowledge-gaps and sets a foundation for the required explanatory control mechanisms that evolve and expand a more detailed model of multi-dimensional slacklining and human functional movement. Such a model facilitates a more complete understanding of existing performance and rehabilitation applications that opens the potential for future applications into broader areas of movement in diverse fields including prostheses, automation and machine-learning related to movement phenotypes.
走扁带,即在拉紧的带子上保持平衡的神经力学动作,是通过将动态稳定性与最佳能量消耗相结合的自我学习策略来实现的。已发表的关于走扁带的文献较新且有限,包括神经力学控制策略模型方面。本文探讨走扁带的定义和起源,以提供有助于理解其演变以及如何逐步纳入预康复和康复过程的背景知识。文中考虑了现有的走扁带解释模型、它们在平衡和稳定性方面的应用,并突出了知识空白。当前的走扁带模型主要源自人体在稳定表面上的安静站立和额面运动。这些模型为走扁带多种应用所特有的复杂神经运动需求提供了多层次的背景,但不够全面。因此,对于在多方向不稳定以及复杂的多维人体运动和行为方面如何实现走扁带,人们的理解并不完整。本文突出了这些知识空白,并为所需的解释性控制机制奠定基础,这些机制将发展并扩展一个更详细的多维走扁带和人体功能运动模型。这样一个模型有助于更全面地理解现有的性能和康复应用,为未来在包括假肢、自动化以及与运动表型相关的机器学习等不同领域的更广泛运动领域中的应用开辟了潜力。