000			03202nam a22003975i 4500
001			85121
003			ES-MaUEC
005			20230207040456.0
007			cr nn 008mamaa
008			151028s2016 gw a s 001 0 eng d
020			_a9783319257068
024	7		_a10.1007/978-3-319-25706-8 _2doi
040			_aES-MaUEC
050		4	_aRC350.N48 _bF74 2016 EB
082	0	4	_a610.28
100	1		_aFreeman, Chris _0local _997839 _0Local
245	1	0	_aControl System Design for Electrical Stimulation in Upper Limb Rehabilitation : _bModelling, Identification and Robust Performance _cby Chris Freeman
250			_a1st ed.
264		1	_aCham _bSpringer International Publishing _c2016
300			_a1 recurso en línea (XIII, 176 p.) _b57 ilustraciones, 20 ilustraciones en color
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
505	0		_aIntroduction.-Modelling and Identification -- Combined FES & Robotic Upper Limb Dynamics -- Model Identification -- Feedback Control Design -- Iterative Learning Control Design -- Clinical Application: Multiple Sclerosis -- Constrained ILC for Human Motor Control -- Clinical Application: Goal-orientated Stroke Rehabilitation -- Electrode Array-based Stimulation -- Clinical Application: Fully Functional Stroke Rehabilitation -- Conclusions and Future Research Directions.
520	3		_aThis book presents a comprehensive framework for model-based electrical stimulation (ES) controller design, covering the whole process needed to develop a system for helping people with physical impairments perform functional upper limb tasks such as eating, grasping and manipulating objects. The book first demonstrates procedures for modelling and identifying biomechanical models of the response of ES, covering a wide variety of aspects including mechanical support structures, kinematics, electrode placement, tasks, and sensor locations. It then goes on to demonstrate how complex functional activities of daily living can be captured in the form of optimisation problems, and extends ES control design to address this case. It then lays out a design methodology, stability conditions, and robust performance criteria that enable control schemes to be developed systematically and transparently, ensuring that they can operate effectively in the presence of realistic modelling uncertainty, physiological variation and measurement noise.
710	2		_aSpringerLink (Online service) _0Local _9106996
942			_2lcc _cLE
988			_aEBOOK, EBSPRINGER
650		7	_aNeuroestimulación _9158566 _0comprobar BNE20011428982 _2embne
650		7	_aRehabilitación _0comprobar BNE19900980029 _2embne _9140038
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-3-319-25706-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9783319257068
907			_a.b1294399x _b10-10-17 _c21-11-16
998			_am _a_alco _a_vill _b10-10-17 _cm _dz _ei _feng _ggw _h0
945			_aRC350.N48 F74 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11588147 _z06-04-17
999			_c85121 _d85121 _x1