@inproceedings{3034b1f630064bae932b4ebbd3c82832,
title = "Robust detection of systolic peaks in arterial blood pressure signal",
abstract = "The heart rate signal is one of the most important physiological signals characterizing the human heart. The heart bits are usually determined on the basis of the electrocardiographic (ECG) signal. However, they can be also detected by monitoring systolic peaks in a arterial blood pressure (ABP) signal. The pressure signal, as other physiological signals, may be disturbed with noise. In this work we propose the method of precise location of the systolic peaks in ABP signal in the presence of noise, by applying the detection function waveform and fuzzy clustering. The new method is tested using real signals from the MIT-BIH Polysomnographic Database. The results obtained during experiments show the high effectiveness of the proposed method in relation to reference methods.",
keywords = "ABP signal, Fuzzy clustering, Systolic peak detection",
author = "Tomasz Pander and Robert Czaba{\'n}ski and Tomasz Przyby{\l}a and Stanis{\l}aw Pietraszek and Micha{\l} Je{\.z}ewski",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 16th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2017 ; Conference date: 11-06-2017 Through 15-06-2017",
year = "2017",
doi = "10.1007/978-3-319-59063-9\_63",
language = "English",
isbn = "9783319590622",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "700--709",
editor = "Ryszard Tadeusiewicz and Zurada, \{Jacek M.\} and Zadeh, \{Lotfi A.\} and Leszek Rutkowski and Marcin Korytkowski and Rafal Scherer",
booktitle = "Artificial Intelligence and Soft Computing - 16th International Conference, ICAISC 2017, Proceedings",
address = "Germany",
}