Department of Electronics, Mathematics and Natural Sciences, University of Gävle, Gävle, Sweden.
Robotics, Perception and Learning (RPL), School of Computer Science and Communication, Royal Institute of Technology (KTH), Stockholm, Sweden.
Med Biol Eng Comput. 2019 Feb;57(2):339-367. doi: 10.1007/s11517-018-1903-3. Epub 2018 Oct 26.
In this survey, we review the field of human shoulder functional kinematic representations. The central question of this review is to evaluate whether the current approaches in shoulder kinematics can meet the high-reliability computational challenge. This challenge is posed by applications such as robot-assisted rehabilitation. Currently, the role of kinematic representations in such applications has been mostly overlooked. Therefore, we have systematically searched and summarised the existing literature on shoulder kinematics. The shoulder is an important functional joint, and its large range of motion (ROM) poses several mathematical and practical challenges. Frequently, in kinematic analysis, the role of the shoulder articulation is approximated to a ball-and-socket joint. Following the high-reliability computational challenge, our review challenges this inappropriate use of reductionism. Therefore, we propose that this challenge could be met by kinematic representations, that are redundant, that use an active interpretation and that emphasise on functional understanding.
在这项调查中，我们回顾了人类肩部功能运动学表现的领域。本次综述的核心问题是评估当前的肩部运动学方法是否能够满足高可靠性计算的挑战。这种挑战是由机器人辅助康复等应用所带来的。目前，运动学表现的作用在这些应用中大多被忽视了。因此，我们系统地搜索并总结了现有的关于肩部运动学的文献。肩部是一个重要的功能关节，其大范围的运动（ROM）带来了几个数学和实际的挑战。在运动学分析中，肩部关节通常被近似为一个球窝关节。为了应对高可靠性计算的挑战，我们的综述挑战了这种不适当的简化论使用。因此，我们提出，这种挑战可以通过运动学表现来解决，这些表现是冗余的，使用主动解释，并强调功能理解。
