Digital Signal Processing

    

Detection of a and B Waves in the Acceleration Photoplethysmogram

Authors: Mohamed Elgendi, Ian Norton, Matt Brearley, Derek Abbott, Dale Schuurmans

Background: Analyzing acceleration photoplethysmogram (APG) signals measured after exercise is challenging. In this paper, a novel algorithm that can detect a waves and consequently b waves under these conditions is proposed. Accurate a and b wave detection is an important rst step for the assessment of arterial stiness and other cardiovascular parameters. Methods: Nine algorithms based on xed thresholding are compared, and a new algorithm is introduced to improve the detection rate using a testing set of heat stressed APG signals containing a total of 1,540 heart beats. Results: The new a detection algorithm demonstrates the highest overall detection accuracy|99.78% sensitivity, 100% positive predictivity|over signals that suer from 1) non-stationary eects, 2)irregular heartbeats, and 3) low amplitude waves. In addition, the proposed b detection algorithm achieved an overall sensitivity of 99.78% and a positive predictivity of 99.95%. Conclusions: The proposed algorithm presents an advantage for real-time applications by avoiding human intervention in threshold determination.

Comments: 26 Pages. The paper is published in Biomedical Engineering Online and its citation is: Elgendi M, Norton I, Brearley M, Abbott D, Schuurmans D (2014) Detection of a and b waves in the acceleration photoplethysmogram. Biomedical Engineering Online 13: 139.

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Submission history

[v1] 2013-01-10 23:43:34
[v2] 2014-01-22 07:21:13
[v3] 2014-10-22 17:21:02

Unique-IP document downloads: 1206 times

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