Mulla Daanish M, Majoni Nigel, Tilley Paul M, Keir Peter J
Department of Kinesiology, McMaster University, Hamilton, ON, Canada.
Department of Kinesiology, McMaster University, Hamilton, ON, Canada.
J Biomech. 2025 Mar;181:112534. doi: 10.1016/j.jbiomech.2025.112534. Epub 2025 Jan 23.
Recording and quantifying hand and finger movement is essential for understanding the neuromechanical control of the hand. Typically, kinematics are collected through marker-based optoelectronic motion capture systems. However, marker-based systems are time-consuming to setup, expensive, and cumbersome, especially for finger tracking. Advances in markerless systems have potential to overcome these limitations, as demonstrated by recent applications in lower extremity biomechanics research. In this work, we aimed to integrate markerless systems for hand biomechanics research by combining open source markerless motion capture pipelines (MediaPipe and Anipose) and investigating the number of cameras required for tracking single finger flexion-extension movements. Finger movements were recorded at three different speeds (0.50, 0.75, 1 Hz) for each of the instructed fingers (index, middle, ring, little) using 4 webcams. Finger joint angles were compared when using all 4 webcams for triangulating 3D hand key points versus all 2- and 3-camera subset combinations. The number of cameras was found to affect joint angles, with differences up to 20° when using 2 or 3 cameras compared to using all 4 cameras. However, we found some 2-camera orientations had minimal differences compared to using all 4 cameras (< 4° difference for the sum of finger [metacarpal, proximal interphalangeal, and distal phalangeal] joint angles). Thus, there can be little to no benefit of adding more than 2 cameras for 3D markerless tracking of the hand during single finger flexion-extension with optimal camera placement.
记录和量化手部及手指运动对于理解手部的神经力学控制至关重要。通常，运动学数据是通过基于标记的光电运动捕捉系统收集的。然而，基于标记的系统设置耗时、成本高昂且操作繁琐，尤其是在手指跟踪方面。无标记系统的进展有可能克服这些局限性，正如最近在下肢生物力学研究中的应用所证明的那样。在这项工作中，我们旨在通过结合开源无标记运动捕捉管道（MediaPipe和Anipose）来整合用于手部生物力学研究的无标记系统，并研究跟踪单指屈伸运动所需的摄像头数量。使用4个网络摄像头，以三种不同速度（0.50、0.75、1赫兹）记录每个被指示手指（食指、中指、无名指、小指）的运动。比较使用所有4个网络摄像头对3D手部关键点进行三角测量时与所有2个和3个摄像头子集组合时的手指关节角度。发现摄像头数量会影响关节角度，与使用所有4个摄像头相比，使用2个或3个摄像头时差异高达20°。然而，我们发现一些2个摄像头的方向与使用所有4个摄像头相比差异最小（手指[掌指关节、近端指间关节和远端指间关节]关节角度总和的差异<4°）。因此，在单指屈伸过程中，对于手部的3D无标记跟踪，在摄像头放置最佳的情况下，添加超过2个摄像头几乎没有益处。
