Three-dimensional modeling of the human hand with motion constraints

Yasumuro, Yoshihiro; Chen, Qian; Chihara, Kazuo

doi:10.1016/s0262-8856(98)00118-8

Cited by 29 publications

(11 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A consistent approximation consists on representing the 8 bones of the carpus, which finely articulate with each other, into a single rigid segment. 1,4,35 Grouping the four metacarpal bones in the hand dorsum into a single segment represents a good compromise between complexity and accuracy of the representation. 5,37 Two functional DoFs, namely flexion-extension and abduction-adduction, characterize the wrist joint.…”

Section: Hand Skeleton Model and Marker Protocolmentioning

confidence: 99%

Finger Kinematic Modeling and Real-Time Hand Motion Estimation

et al. 2007

View full text Add to dashboard Cite

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.

show abstract

Section: Hand Skeleton Model and Marker Protocolmentioning

confidence: 99%

Finger Kinematic Modeling and Real-Time Hand Motion Estimation

et al. 2007

View full text Add to dashboard Cite

show abstract

“…Most of them, which are based on the human skeleton, and which were developed for predicting grip posture, focus only on the kinematic structure of the human hand. [2][3][4][5][6][7][8] In these models, the deformable aspect of the hand and its real mechanical behavior are not taken into account.…”

Section: Introductionmentioning

confidence: 99%

A first step in finite-element simulation of a grasping task

Chamoret

Bodo

Roth

2016

Computer Assisted Surgery

View full text Add to dashboard Cite

This paper investigates a biomechanical aspect of human hand during grasping, using the finiteelement method. A realistic three-dimensional finite-element (FE) model of a human hand is developed, including wrist bones, phalanges, soft tissues and skin, reconstructed from medical computed tomography (CT) scan images. Material laws of the literature have been implemented in the model, in order to be able to simulate a simple activity of grasping. In a human design context, this model allows an interesting biomechanical study, which simulates the grasping task in a biofidelic manner. This model is a first step in the modeling of the human hand that can lead to future studies dealing with the interaction of the hand with its environment for the improvement of safety requirements of future products development.

show abstract

“…A hand shape can be estimated by searching for the best matching sample from the given model. An articulated hand model requires more than 20 degrees of freedom, although actual fingers are interdependent and constrained by their applications [7]. Many algorithms have been developed for efficiently searching in the high-dimensional configuration space based on optimization-based methods [8,5,9,6], physical constraints [10], multiple hypotheses, and multiple cue integration [11], among others.…”

Section: Related Workmentioning

confidence: 99%