2 January 2018 Hopfield neural network and optical fiber sensor as intelligent heart rate monitor
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This paper presents a design and fabrication of an intelligent fiber-optic sensor used for examining and monitoring heart rate activity. It is found in the literature that the use of fiber sensors as heart rate sensor is widely studied. However, the use of smart sensors based on Hopfield neural networks is very low. In this work, the sensor is a three fibers without cladding of about 1 cm, fed by laser light of 1550 nm of wavelength. The sensing portions are mounted with a micro sensitive diaphragm to transfer the pulse pressure on the left radial wrist. The influenced light intensity will be detected by a three photodetectors as inputs into the Hopfield neural network algorithm. The latter is a singlelayer auto-associative memory structure with a same input and output layers. The prior training weights are stored in the net memory for the standard recorded normal heart rate signals. The sensors’ heads work on the reflection intensity basis. The novelty here is that the sensor uses a pulse pressure and Hopfield neural network in an integrity approach. The results showed a significant output measurements of heart rate and counting with a plausible error rate.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kussay Nugamesh Mutter "Hopfield neural network and optical fiber sensor as intelligent heart rate monitor", Proc. SPIE 10456, Nanophotonics Australasia 2017, 104564T (2 January 2018); doi: 10.1117/12.2283012; https://doi.org/10.1117/12.2283012

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