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dc.contributor.authorMolina Vilaplana, Javier 
dc.contributor.authorLópez Coronado, Juan 
dc.contributor.authorFeliú Batlle, Jorge Juan 
dc.date.accessioned2009-07-03T10:06:26Z
dc.date.available2009-07-03T10:06:26Z
dc.date.issued2004-10
dc.identifier.citationMOLINA VILAPLANA, Javier, FELIU BATLLE, Jorge, LÓPEZ CORONADO, Juan. A neural model of hand grip formation during reach to grasp. En: IEEE International Conference on Systems, Man & Cybernetics (2004: The Hague, Netherlands). 2004 EEE International Conference on Systems, Man & Cybernetic: The Hague, Netherlands, 10 - 13 October, 2004. The Hague, Netherlands: Institute of Electrical and Electronics Engineers. Vol.1, 10-13 Oct. 2004. 542 - 546 p. ISBN 0-7803-8566-7es
dc.identifier.isbn0-7803-8566-7
dc.description.abstractIn this paper, we investigate the spatio temporal dynamics of hand pre-shaping during prehension through a biologically plausible neural network model. It is proposed that the hand grip formation in prehension con be understood in terms of basic motor programs that can be resealed both spatially and temporally to accommodate different task demands. The model assumes a timing coordinative role to propioceptive reafferent information generated by the reaching component of the movement, moidiiig the need of a pre-organized firnctional temporal structure for the timing of prehension as some previous models have proposed. Predictions of the model in both Normal and Altered initial hand aperture conditions match key kinematic features present in human data. The differences between the proposed model and previous models predictions are used to tiy to identifi the majorprinciples underlying prehensile behavior.es
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dc.language.isoenges
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE).es
dc.rightsCopyright © 2004 IEEEes
dc.titleA neural model of hand grip formation during reach to graspes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.subjectModelos neuronaleses
dc.subjectDato humanoes
dc.subjectNeurorobotes
dc.subjectExtensión de agarrees
dc.subjectNeural modelses
dc.subjectHuman dataes
dc.subjectNeuroroboticses
dc.subjectReach to Graspes
dc.subject.otherIngeniería de Sistemas y Automáticaes
dc.identifier.urihttp://hdl.handle.net/10317/1066
dc.identifier.doi10.1109/ICSMC.2004.1398355


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