NeuroControl: system identification approach for clinical benefit.

Progress in diagnosis and treatment of movement disorders after neurological diseases like stroke, cerebral palsy, dystonia and at old age requires understanding of the altered capacity to adequately respond to physical obstacles in the environment. With posture and movement disorders, the control o...

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Bibliographic Details
Main Authors: Carel G.M. Meskers, Jurriaan ede Groot, Erwin ede Vlugt, Alfred eSchouten
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-09-01
Series:Frontiers in Integrative Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnint.2015.00048/full
Description
Summary:Progress in diagnosis and treatment of movement disorders after neurological diseases like stroke, cerebral palsy, dystonia and at old age requires understanding of the altered capacity to adequately respond to physical obstacles in the environment. With posture and movement disorders, the control of muscles is hampered, resulting in aberrant force generation and improper impedance regulation. Understanding of this improper regulation not only requires the understanding of the role of the neural controller, but also attention for the 1) the interaction between the neural controller and the plant, comprising the biomechanical properties of the skeleton including the viscoelastic properties of the contractile (muscle) and non-contractile (connective) tissues: neuromechanics and 2) the closed loop nature of neural controller and biomechanical system in which cause and effect interact and are hence difficult to separate. Properties of the neural controller and the biomechanical system need to be addressed synchronously by the combination of haptic robotics, (closed loop) system identification, and neuro-mechanical modelling. In this paper, we argue that assessment of neuromechanics in response to well defined environmental conditions and tasks may provide for key parameters to understand posture and movement disorders in neurological diseases and as biomarkers to increase accuracy of prediction models for functional outcome and effects of intervention.
ISSN:1662-5145