Fuzzy-genetic photoplethysmograph peak detection

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management, HNICEM 2014 - 7th HNICEM 2014 Joint with 6th International Symposium on Computational Intelligence and Intelligent Informatics, co-located with 10th ERDT Conference

Publication Date

1-1-2014

Abstract

© 2014 IEEE. Photoplethysmography (PPG) promises noninvasive body metrics measurement, especially that of heart rate. However, this system is prone to noise due to motion artifacts. This paper presents a fuzzy inference system, with membership functions and rules tuned by a genetic algorithm that utilizes the principal components of the PPG data accelerometer data from the x, y, and z coordinates in order to recover the peaks from the distorted PPG signal. A comparative test demonstrated that a 56.66% peak-to-peak correspondence to a reference ECG signal is achievable with the fuzzy-genetic system in place.

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Digitial Object Identifier (DOI)

10.1109/HNICEM.2014.7016243

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