A fully automated algorithm for heart rate detection in post-dive precordial Doppler ultrasound

Abstract

Background: Doppler ultrasound is used currently in decompression research for the evaluation of venous gas emboli (VGE). Estimation of heart rate from post-dive Doppler ultrasound recordings can provide a tool for the evaluation of physiological changes from decompression stress, as well as aid in the development of automated VGE detection algorithms that relate VGE presence to cardiac activity. Method: An algorithm based on short-term autocorrelation was developed in MATLAB to estimate the heart rate in post-dive precordial Doppler ultrasound. The algorithm was evaluated on 21 previously acquired and labeled precordial recordings spanning Kisman-Masurel (KM) codes of 111–444 (KM I–IV) with manually derived instantaneous heart rates. Results: A window size of at least two seconds was necessary for robust and accurate instantaneous heart rate estimation with a mean error of 1.56 ± 7.10 bpm. Larger window sizes improved the algorithm performance, at the cost of beat-to-beat heart rate estimates. We also found that our algorithm provides good results for low KM grade Doppler recordings with and without flexion, and high KM grades without flexion. High KM grades observed after movement produced the greatest mean absolute error of 6.12 ± 8.40 bpm. Conclusion: We have developed a fully automated algorithm for the estimation of heart rate in post-dive precordial Doppler ultrasound recordings.