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Designing of Artificial Intelligence Model-Free Controller Based on Output Error to Control Wound Healing Process | OMICS International| Abstract
ISSN: 2090-4967

Biosensors Journal
Open Access

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  • Research Article   
  • Biosens J 2017, Vol 6(2): 147
  • DOI: 10.4172/2090-4967.1000147

Designing of Artificial Intelligence Model-Free Controller Based on Output Error to Control Wound Healing Process

Azizi A*
Department of Engineering, German University of Technology, Muscat, Oman
*Corresponding Author : Azizi A, Department of Engineering, German University of Technology, Muscat, Oman, Tel: 968 22 061111, Email: [email protected]

Received Date: Jul 19, 2017 / Accepted Date: Sep 08, 2017 / Published Date: Sep 12, 2017

Abstract

The complexity of biological systems demands the use of appropriate controllers in order to control the final quality of the system based on the effects of inputs of the system. Wound healing is a complex biological process dependent on multiple variables: tissue oxygenation, wound size, contamination, etc. Many of these factors depend on multiple factors themselves. Mechanisms for some interactions between these factors are still unknown. The artificial intelligence appears as an interesting alternative to control such systems and to satisfy the desired requirement. In this paper we try to simulate and control wound healing process with focusing on remodeling phase by neural networks as an intelligence technique. For these purposes some materials like mathematical modeling, finite elements method, and effect of external forces on the scar tissue are used here.

Keywords: Neural networks; Simulation; Control; Wound healing; Remodeling phase; External forces; Mathematical modeling; Finite elements

Citation: Azizi A (2017) Designing of Artificial Intelligence Model-Free Controller Based on Output Error to Control Wound Healing Process. Biosens J 6: 147. Doi: 10.4172/2090-4967.1000147

Copyright: ©2017 Azizi A. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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