Finger kinematic modeling and real-time hand motion estimation
Finger kinematic modeling and real-time hand motion estimation
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DOI：
10.1007/s10439-007-9364-0
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发表时间：
2007-11-01
影响因子：
3.8
通讯作者：
Ferrigno, G.
中科院分区：
文献类型：
--
作者：
Cerveri, P.;De Momi, E.;Ferrigno, G.
本文介绍了利用多摄像机系统和24个表面标记对手指运动进行实时定量重建的方法和实验研究。该方法利用了关节手的运动学模型，该模型由22个功能自由度和全局旋转平移的刚体段组成的层次链。这项工作的重点是生物力学分析目的的运动学手模型的实验评估。从静态姿势，一个完全自动的校准程序，基于人体测量和几何约束，计算轴，旋转中心，然后利用作为手模型的交互式实时动画的基础。运动跟踪，基于自动标记标记和预测过滤器，授权通过引入功能性手指姿势的约束。验证是通过不同的右手运动任务，包括自愿屈曲伸展拇指，自愿外展内收拇指，把握，手指指向四个正常受试者。性能进行测试的角度分布，基于模型的能力，预测标记轨迹和跟踪成功的实时运动估计的可重复性。结果表明，在受试者内的模型校准的重复性，以不同的姿势和重新标记的范围内的0.5和2毫米，分别。运动学估计在预测能力（食指：最大RMSE 2.02 mm;拇指：最大RMSE 3.25 mm）和运动再现性（R-2系数-食指：0.96，拇指：0.94）方面证明是令人满意的。在快速抓取序列（60 Hz）期间，残留标记物遮挡的百分比小于1%，50 Hz的处理和可视化频率证实了运动估计系统的实时能力。
This paper describes methods and experimental studies concerned with quantitative reconstruction of finger movements in real-time, by means of multi-camera system and 24 surface markers. The approach utilizes a kinematic model of the articulated hand which consists in a hierarchical chain of rigid body segments characterized by 22 functional degrees of freedom and the global roto-translation. This work is focused on the experimental evaluation of a kinematical hand model for biomechanical analysis purposes.From a static posture, a completely automatic calibration procedure, based on anthropometric measures and geometric constraints, computes axes, and centers of rotations which are then utilized as the base of an interactive real-time animation of the hand model. The motion tracking, based on automatic marker labeling and predictive filter, is empowered by introducing constraints from functional finger postures. The validation is performed on four normal subjects through different right-handed motor tasks involving voluntary flexion-extension of the thumb, voluntary abduction-adduction of the thumb, grasping, and finger pointing. Performances are tested in terms of repeatability of angular profiles, model-based ability to predict marker trajectories and tracking success during real-time motion estimation. Results show intra-subject repeatability of the model calibration both to different postures and to re-marking in the range of 0.5 and 2 mm, respectively. Kinematic estimation proves satisfactory in terms of prediction capability (index finger: maximum RMSE 2.02 mm; thumb: maximum RMSE 3.25 mm) and motion reproducibility (R-2 coefficients-index finger: 0.96, thumb: 0.94). During fast grasping sequence (60 Hz), the percentage of residual marker occlusions is less than 1% and processing and visualization frequency of 50 Hz confirms the real-time capability of the motion estimation system.