Havens Timothy C, Alexander Gregory L, Abbott Carmen C, Keller James M, Skubic Marjorie, Rantz Marilyn
Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO 65211, USA.
J Appl Comput Sci Methods. 2009 Jan 1;2(1):21-42.
In this paper we describe the development of a novel markerless motion capture system and explore its use in documenting elder exercise routines in a health club. This system uses image contour tracking and swarm intelligence methods to track the location of the spine and shoulders during three exercises - treadmill, exercise bike, and overhead lateral pull-down. Validation results show that our method has a mean error of approximately 2 degrees when measuring the angle of the spine or shoulders relative to the horizontal. Qualitative study results demonstrate that our system is capable of providing important feedback about the posture and stability of elders while they are performing exercises. Study participants indicated that feedback from our system would add value to their exercise routines.
在本文中，我们描述了一种新型无标记运动捕捉系统的开发，并探讨了其在记录健康俱乐部中老年人锻炼日常的应用。该系统使用图像轮廓跟踪和群体智能方法来跟踪三种运动（跑步机、健身自行车和高位下拉）过程中脊柱和肩部的位置。验证结果表明，在测量脊柱或肩部相对于水平方向的角度时，我们的方法平均误差约为2度。定性研究结果表明，我们的系统能够在老年人进行锻炼时提供有关其姿势和稳定性的重要反馈。研究参与者表示，我们系统提供的反馈将为他们的锻炼日常增添价值。
