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.