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Detection of a and b waves in the acceleration photoplethysmogram
Mohamed Elgendi1, Ian Norton, Matt Brearley
1Department of Computing Science, University of Alberta, 2-32 Athabasca Hall, T6G 2E1 Edmonton, Canada. moe.elgendi@gmail.com.
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 first step for the assessment of arterial stiffness and other cardiovascular parameters.
Methods:
Nine algorithms based on fixed 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 suffer from 1) non-stationary effects, 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.
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