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Reseach Article

Performance Analysis of Photometric Strain Biosensor for Bones using Artificial Neural Network

by Preeti Singh, H. M. Rai
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 54 - Number 8
Year of Publication: 2012
Authors: Preeti Singh, H. M. Rai
10.5120/8586-2337

Preeti Singh, H. M. Rai . Performance Analysis of Photometric Strain Biosensor for Bones using Artificial Neural Network. International Journal of Computer Applications. 54, 8 ( September 2012), 16-19. DOI=10.5120/8586-2337

@article{ 10.5120/8586-2337,
author = { Preeti Singh, H. M. Rai },
title = { Performance Analysis of Photometric Strain Biosensor for Bones using Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 54 },
number = { 8 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 16-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume54/number8/8586-2337/ },
doi = { 10.5120/8586-2337 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:55:09.964948+05:30
%A Preeti Singh
%A H. M. Rai
%T Performance Analysis of Photometric Strain Biosensor for Bones using Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 54
%N 8
%P 16-19
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Osteoporosis is a disease of bones. It leads to an increased risk of fracture. The improvement in biosensor for measuring the strain on bones is required. A photometric biosensor is modeled. It is simulated. The performance of the biosensor is analyzed using Artificial Neural Network (ANN) in terms of layers of neural network. Number of epochs/iterations are carried out. The performance is analyzed in terms of mean square error (mse). The percentage accuracy of sensor is obtained as 93%.

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Index Terms

Computer Science
Information Sciences

Keywords

biosensor bones mean square error microbend layer strain