Jarvis, C., Gollee, H., Kwende, M.M.N., Salmons, S., and Murray-Smith, D.J. (1996) Towards an optimized muscle controller. In: Pedotti, A., Quintern, J. and Riener, R. (eds.) Neuroprosthetics: Basic Research to Clinical Applications. Springer Verlag, Berlin, Germany, pp. 123-128. ISBN 9783540610847
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The use of skeletal muscle ventricles to assist the failing heart is a potential solution to the problems associated with cardiac transplantation. In this approach, circulatory assistance would be provided by an auxiliary pump (Skeletal muscle ventricle or SMV) formed from the patient's own back muscle and activated by an implanted controller. We do not yet have sufficient understanding of the function of SMVs to use them safely and effectively in humans, but the feasibility of the technique has been established - SMVs have worked for up to two years in dogs. Skeletal muscle itself is a highly complex linear motor. Its passive mechanical properties, the relationship between its neural input and its mechanical output and the dependence of its mechanical output on its loading conditions, are all non-linear. Together with the geometrical complexities of thick walled pumping chambers, these factors preclude analytical modelling of of SMVs from first principles. A new approach is needed to link these many interacting factors together. Developments in systems engineering and computer science in terms of local linear network models (LLNMs), and new methods of controller design based on LLMNs, have considerable potential for this application. LLMN methods have evolved recently from the general field of artificial neural networks. The ultimate goal of this project is to generate controllers for SMVs based on LLMNs. Such controllers would elicit pumping work from the assist device, with due regard to the history of activation of the muscle, and with the fewest possible neural impulses. The latter condition must be met in order to maintain the balance between the desirable increase in endurance and the undesirable reduction in speed and power that are both consequences of activation of skeletal muscle in the long term.
|Item Type:||Book Sections|
|Keywords:||muscle, control, skeletal muscle, heart, ventricle, nonlinear, local linear network model.|
|Glasgow Author(s) Enlighten ID:||Murray-Smith, Professor David and Gollee, Dr Henrik|
|Authors:||Jarvis, C., Gollee, H., Kwende, M.M.N., Salmons, S., and Murray-Smith, D.J.|
|Subjects:||Q Science > QA Mathematics > QA76 Computer software|
Q Science > QP Physiology
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
|College/School:||College of Science and Engineering > School of Engineering > Systems Power and Energy|