Effect of Neurons on the Performance of Microbend Optical Biosensor

Osteoporosis is a very severe disease of bones. It leads to an increased risk of fracture. Existing biosensors need improvement to detect the early onset of osteoporosis. Fiber Optic microbend biosensor is being developed to achieve such an improvement. Microbend sensors are based on Microbend induced excess transmission loss of an optical fiber. Artificial Neural Networks (ANN) were a key development in the field of machine learning. They were inspired by biological findings relating to the behavior of the brain as a network of units called neurons. The basics of these neurons has been utilized to analyze the performance of ANN based simulink model in terms of mean square error (mse). The best validation performance in terms of mse is 0.044938 for one neuron. The percentage accuracy of the designed biosensor is obtained as 94%.

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