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Control system design for electrical...

Freeman, Chris.

Control system design for electrical stimulation in upper limb rehabilitationmodelling, identification and robust performance /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Control system design for electrical stimulation in upper limb rehabilitationby Chris Freeman.
其他題名:	modelling, identification and robust performance /
作者:	Freeman, Chris.
出版者:	Cham :Springer International Publishing :2016.
面頁冊數:	xiii, 176 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Neural stimulation.
電子資源:	http://dx.doi.org/10.1007/978-3-319-25706-8
ISBN:	9783319257068$q(electronic bk.)

Control system design for electrical stimulation in upper limb rehabilitationmodelling, identification and robust performance /
Freeman, Chris.

Control system design for electrical stimulation in upper limb rehabilitationmodelling, identification and robust performance /[electronic resource] :by Chris Freeman. - Cham :Springer International Publishing :2016. - xiii, 176 p. :ill., digital ;24 cm.

Introduction -- 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.

This 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.

ISBN: 9783319257068$q(electronic bk.)

Standard No.: 10.1007/978-3-319-25706-8doiSubjects--Topical Terms:

286640
Neural stimulation.

LC Class. No.: RC350.N48 / F74 2016

Dewey Class. No.: 616.804645

Control system design for electrical stimulation in upper limb rehabilitationmodelling, identification and robust performance /
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505 0 $a Introduction -- 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 $a This 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.
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