TY - JOUR
T1 - Low-complexity R-peak detection for ambulatory fetal monitoring
AU - Rooijakkers, M.J.
AU - Rabotti, C.
AU - Oei, S.G.
AU - Mischi, M.
PY - 2012
Y1 - 2012
N2 - Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.
AB - Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.
U2 - 10.1088/0967-3334/33/7/1135
DO - 10.1088/0967-3334/33/7/1135
M3 - Article
C2 - 22735075
SN - 0967-3334
VL - 33
SP - 1135
EP - 1150
JO - Physiological Measurement
JF - Physiological Measurement
IS - 7
ER -