Publication Type:

Conference Paper

Source:

Energy Procedia, Elsevier Ltd, Volume 117, p.393-400 (2017)

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030637108&doi=10.1016%2fj.egypro.2017.05.154&partnerID=40&md5=b5ba7f09e195a50d544645a5b71c64e5

Keywords:

Blood, Clinical management systems, Computation theory, Computer aided engineering, Fuzzy logic, light emitting diodes, Modern medicine, Neural networks, Noninvasive medical procedures, Oximeters, oxygen saturation, Oxygenated hemoglobin, Power control, Pulse oximeters, Red led lights, SpO2, Transmission characteristics

Abstract:

Pulse oximeters are ubiquitous in modern medicine to noninvasively measure the percentage of oxygenated hemoglobin in a patient's blood. Pulse oximeters are well adapted, simpler and quite easy to measure. In this paper, An ANN based model using LabVIEW is proposed to measure and estimate the SpO2 present in the blood. Infra red (IR) and red LED lights are passed through the fingers and the ratio of transmission characteristics (R value) is calculated through LabVIEW system. Based on the R value the oxygen saturation SPO2 is calculated. This study is done through aNETka, which is an ANN work system designed in LabVIEW. Finally the result is compared with both fuzzy logic and linear regression based methods. The proposed method shows that ANN can be efficiently used in clinical management systems and also proved its consistency and accuracy. © 2017 The Authors. Published by Elsevier Ltd.

Notes:

cited By 0; Conference of 1st International Conference on Power Engineering Computing and CONtrol, PECCON 2017 ; Conference Date: 2 March 2017 Through 4 March 2017; Conference Code:130810

Cite this Research Publication

G. P. Gupta, Nair, R. R., and Jeyanthi, R., “An ANN based SpO2 Measurement for Clinical Management Systems”, in Energy Procedia, 2017, vol. 117, pp. 393-400.

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