The quadriceps muscle of knee joint modelling using neural network approach: Part 2

Ahmad Kamaruddin, Saadi and Md Ghani, Nor Azura and Mohamed Ramli, Norazan and Mohamed Nasir, Noorhamizah and Ksm Kader Ibrahim, Babul Salam and Huq, Mohammad Saiful (2017) The quadriceps muscle of knee joint modelling using neural network approach: Part 2. In: 2016 IEEE Conference on Open Systems, ICOS 2016, 10-12 October, 2016, Holiday Villa Resort Langkawi, Kedah.

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Abstract

— Artificial neural network has been implemented in many filed, and one of the most famous estimators. Neural network has long been known for its ability to handle a complex nonlinear system without a mathematical model and has the ability to learn sophisticated nonlinear relationships provides. Theoretically, the most common algorithm to train the network is the backpropagation (BP) algorithm which is based on the minimization of the mean square error (MSE). Subsequently, this paper displays the change of quadriceps muscle model by using fake savvy strategy named backpropagation neural system nonlinear autoregressive (BPNN-NAR) model in perspective of utilitarian electrical affectation (FES). A movement of tests using FES was driven. The data that is gotten is used to develop the quadriceps muscle model. 934 planning data, 200 testing and 200 endorsement data set are used as a part of the change of muscle model. It was found that BPNNNARMA is suitable and efficient to model this type of data. A neural network model is the best approach for modelling nonlinear models such as active properties of the quadriceps muscle with one input, namely output namely muscle force.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	7581/57339
Uncontrolled Keywords:	Artificial neural network, backpropagation, nonlinear autoregressive, quadriceps muscle
Subjects:	R Medicine > RC Internal medicine R Medicine > RD Surgery
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Science Kulliyyah of Science > Department of Computational and Theoretical Sciences
Depositing User:	Dr Saadi Kamaruddin
Date Deposited:	20 Jun 2017 12:42
Last Modified:	19 Feb 2020 17:32
URI:	http://irep.iium.edu.my/id/eprint/57339

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