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Control System Design for Electrical...
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Control System Design for Electrical Stimulation in Upper Limb Rehabilitation = Modelling, Identification and Robust Performance /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Control System Design for Electrical Stimulation in Upper Limb Rehabilitation/ by Chris Freeman.
Reminder of title:
Modelling, Identification and Robust Performance /
Author:
Freeman, Chris.
Description:
XIII, 176 p.online resource. :
Contained By:
Springer Nature eBook
Subject:
Biomedical engineering. -
Online resource:
https://doi.org/10.1007/978-3-319-25706-8
ISBN:
9783319257068
Control System Design for Electrical Stimulation in Upper Limb Rehabilitation = Modelling, Identification and Robust Performance /
Freeman, Chris.
Control System Design for Electrical Stimulation in Upper Limb Rehabilitation
Modelling, Identification and Robust Performance /[electronic resource] :by Chris Freeman. - 1st ed. 2016. - XIII, 176 p.online resource.
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
Standard No.: 10.1007/978-3-319-25706-8doiSubjects--Topical Terms:
588770
Biomedical engineering.
LC Class. No.: R856-857
Dewey Class. No.: 610.28
Control System Design for Electrical Stimulation in Upper Limb Rehabilitation = Modelling, Identification and Robust Performance /
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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.
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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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