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008			160224s2016 gw | s |||| 0|eng d
020			_a9783319267067
040			_aES-MaUEC
050		4	_aTJ211.43 _bH863 2016
082	0	4	_a005.437
082	0	4	_a4.019
245	1	0	_aHuman and Robot Hands : _bSensorimotor Synergies to Bridge the Gap Between Neuroscience and Robotics _cedited by Matteo Bianchi, Alessandro Moscatelli
250			_a1st ed.
260			_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XI, 283 páginas) _b97 ilustraciones, 66 ilustraciones en color
336			_aTexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aSpringer Series on Touch and Haptic Systems _x2192-2977
505	0		_aIntroduction -- Part I: Neuroscience -- Dexterous Manipulation: From High-level Representation to Low-level Co-ordination of Digit Force and Position -- Digit Position and Force Synergies During Unconstrained Grasping -- The Motor Control of Hand Movements in the Human Brain: Toward the Definition of a Cortical Representation of Postural Synergies -- Synergy Control in Subcortical Circuitry: Insights from Neurophysiology -- Neuronal "Op-Amps" Implement Adaptive control in Biology and Robotics -- Sensorimotor Synergies:Fusion of Cutaneous Touch and Proprioception in the Perceived Hand Kinematics -- Part II: Robotics, Models and Sensing Tools -- From Soft to Adaptive Synergies:The PISA/IIT Softhand -- A Learn by Demonstration Approach for Closed-loop Robust Anthromorphic Grasp Planning -- Teleimpudance Control: Overview and Application -- Incremental Learning of Muscle Synergies:From Calibrating a Prothesis to Interacting with it -- How to Map Human Hand Synergies onto Robotic Hands Using the�Syngrasp Matlab Toolbox -- Quasi-static Analysis of Synergistically Underactuated Robotic Hands in Grasp and Manipulation Tasks -- A simple Model of the Hand for the Analysis of Object Exploration -- Synergy-based Optimal Sensing Techniques for Hand Pose Reconstruction.
520	3		_aThis book looks at the common problems both human and robotic hands encounter when controlling the large number of joints, actuators and sensors required to efficiently perform motor tasks such as object exploration, manipulation and grasping. The authors adopt an integrated approach to explore the control of the hand based on sensorimotor synergies that can be applied in both neuroscience and robotics. Hand synergies are based on goal-directed, combined muscle and kinematic activation leading to a reduction of the dimensionality of the motor and sensory space, presenting a highly effective solution for the fast and simplified design of artificial systems. Presented in two parts, the first part, Neuroscience, provides the theoretical and experimental foundations to describe the synergistic organization of the human hand. The second part, Robotics, Models and Sensing Tools, exploits the framework of hand synergies to better control and design robotic hands and haptic/sensing systems/tools, using a reduced number of control inputs/sensors, with the goal of pushing their effectiveness close to the natural one. Human and Robot Hands provides a valuable reference for students, researchers and designers who are interested in the study and design of the artificial hand.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, asignarmaterias , EBSPRINGER
650		7	_aNeurociencias _0comprobar BNE20012490612 _2embne _9158907
650	0	7	_aInterfaces de usuario _0 _2embne _9149839
700	1		_aBianchi, Matteo. _eeditor literario _924301 _0comprobar BNE19961897577
700	1		_aMoscatelli, Alessandro. _eeditor literario _998034 _0Local
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-26706-7 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319267067
907			_a.b12945110 _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _ggw _h0
945			_aTJ211.43 H863 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i1158905x _z06-04-17
999			_c85233 _d85233 _x1