An Open-source Algorithm to Detect Onset of Arterial Blood Pressure Pulses


In this paper; we present an effective algorithm for detecting the onset of anerial blood pressure (ABP) pulses. The algorithm employs a windowed and weighted slope sum function (SSF) to extract ABP wavefonn features. Aahptive thresholding and search strategies are applied to the SSF signal to detect ABP pulses and to determine their onsets. Two evaluation procedures were employed. First, pulse detection accuracy was evaluated by comparing the algorithm's pulse detections with reference ECG annotations using the MlT-BIH Polysomnographic Database. The algorithm detected 99.31 8 ofthe 368,364 beats annotated in the ECG. Second, the accuracy of pulse onset determination was established using a newly created, manually-edited reference ABP signal database. For 96.41% ofthe 39,848 beats in the reference database, the difference between the manually-edited and algorithmdetermined ABP pulse onset was less than or equal to 20 ms. The C source code of the algorithm h a s been contributed to PhysioToolkit and is freely available from the PhysioNet websire (http:/

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@inproceedings{Zong2003AnOA, title={An Open-source Algorithm to Detect Onset of Arterial Blood Pressure Pulses}, author={Weiwei Zong}, year={2003} }