The quadriceps muscle of knee joint modelling using neural network approach: Part 1
Artificial neural approach has been executed in various recorded, and a champion amongst the most understood widespread approximators. Neural framework has for quite a while been known for its ability to handle a complex nonlinear system without a logical model and can learn refined nonlinear a...
| Main Authors: | , , , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
IEEE
2017
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/62934/ http://irep.iium.edu.my/62934/ http://irep.iium.edu.my/62934/ http://irep.iium.edu.my/62934/1/62934%20The%20Quadriceps%20Muscle%20of%20Knee%20Joint%20Modelling.pdf http://irep.iium.edu.my/62934/2/62934%20The%20quadriceps%20muscle%20of%20knee%20joint%20modelling%20using%20neural%20SCOPUS.pdf |
| Summary: | Artificial neural approach has been executed in
various recorded, and a champion amongst the most understood
widespread approximators. Neural framework has for quite a
while been known for its ability to handle a complex nonlinear
system without a logical model and can learn refined nonlinear
associations gives. Theoretically, the most surely understood
computation to set up the framework is the backpropagation
(BP) count which relies on upon the minimization of the mean
square error (MSE). This paper exhibits the improvement of
quadriceps muscle model by utilizing counterfeit smart
procedure named backpropagation neural network nonlinear
autoregressive (BPNN-NAR) model in view of utilitarian
electrical incitement (FES). A progression of tests utilizing FES
was led. The information that is gotten is utilized to build up the
quadriceps muscle model. 934 preparing information, 200
testing and 200 approval information set are utilized as a part
of the improvement of muscle model. It was found that BPNNNAR
is suitable and efficient to model this type of data. A neural
network model is the best approach for modelling non-linear
models such as active properties of the quadriceps muscle with
one input, namely output namely muscle force. |
|---|