dc.creatorCerveri, P
dc.creatorDe Momi, E
dc.creatorLopomo, N
dc.creatorBaud-Bovy, G
dc.creatorBarros, RML
dc.creatorFerrigno, G
dc.date2007
dc.dateNOV
dc.date2014-11-19T13:53:20Z
dc.date2015-11-26T17:06:26Z
dc.date2014-11-19T13:53:20Z
dc.date2015-11-26T17:06:26Z
dc.date.accessioned2018-03-28T23:54:52Z
dc.date.available2018-03-28T23:54:52Z
dc.identifierAnnals Of Biomedical Engineering. Springer, v. 35, n. 11, n. 1989, n. 2002, 2007.
dc.identifier0090-6964
dc.identifierWOS:000250372400013
dc.identifier10.1007/s10439-007-9364-0
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/66974
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/66974
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/66974
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1279849
dc.descriptionThis 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.
dc.description35
dc.description11
dc.description1989
dc.description2002
dc.languageen
dc.publisherSpringer
dc.publisherNew York
dc.publisherEUA
dc.relationAnnals Of Biomedical Engineering
dc.relationAnn. Biomed. Eng.
dc.rightsfechado
dc.rightshttp://www.springer.com/open+access/authors+rights?SGWID=0-176704-12-683201-0
dc.sourceWeb of Science
dc.subjecthand kinematic model
dc.subjectreal-time tracking
dc.subjectthumb motion
dc.subjectreaching
dc.subjectgrasping
dc.subjectfinger movements
dc.subjectTo-grasp
dc.subjectAnalysis System
dc.subjectMetacarpophalangeal Joint
dc.subjectThumb
dc.subjectRotation
dc.subjectMovements
dc.subjectMonkey
dc.subjectFeasibility
dc.subjectConstraints
dc.subjectParameters
dc.titleFinger kinematic modeling and real-time hand motion estimation
dc.typeArtículos de revistas


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