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 arterial blood pressure (ABP) pulses. The algorithm employs a windowed and weighted slope sum function (SSF) to extract ABP waveform features. Adaptive 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 MIT-BIH Polysomnographic Database. The algorithm detected 99.31% of the 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% of the 39,848 beats in the reference database, the difference between the manually-edited and algorithm-determined ABP pulse onset was less than or equal to 20 ms. The C source code of the algorithm has been contributed to PhysioToolkit and is freely available from the PhysioNet website (http://www.physionet.org).