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1篇 您的检索式：作者名="Vincent Crocher"

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		题名	作者	年代	出处	被引量
	1	Learning control in robot-assisted rehabilitation of motor skills-a显示文摘The key idea in iterative learning control is captured by the intuition of‘practice makes perfect’.The underlying learning is based on a gradient descent algorithm iteratively optimising an appropriate input–output measured criterion.How this paradigm is used to model quantitatively,at an input/output level,the learning that happens in the context of human motor skill learning is discussed in this note.Experimental studies of human motor learning,in robotically controlled environments,indicate that a model consisting of a classical(iterative)learning control augmented with an appropriate kinematic model of human motor motion fits the observed human learning behaviour well.In the context of the rehabilitation of motor skills,such models promise better human–machine interfaces that extend the capability and capacity of rehabilitation clinicians by creating effective robot–patient–clinician feedback loops.The economic promise of robot-assisted rehabilitation is to greatly extend the intervention capacity above what presently can be achieved by rehabilitation systems:addressing the needs of more people,over longer periods of time and at a distance in the comfort of their own personal environment.Moreover,the robot platforms provide for a more rigorous and quantitative evaluation of the patient’s motor skill across the entire personal rehabilitation trajectory,which opens up opportunities for improved,more individually tuned rehabilitation regimes.	Shou-Han Zhou Justin Fong Vincent Crocher Ying Tan Denny Oetomo Iven Mareels	2016	Journal of Control and Decision2016，3，1：	1

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