Title :
An automatic beat detection algorithm for pressure signals
Author :
Aboy, Mateo ; McNames, James ; Thong, Tran ; Tsunami, Daniel ; Ellenby, Miles S. ; Goldstein, Brahm
Author_Institution :
Electron. Eng. Technol. Dept., Oregon Inst. of Technol., Portland, OR, USA
Abstract :
Beat detection algorithms have many clinical applications including pulse oximetry, cardiac arrhythmia detection, and cardiac output monitoring. Most of these algorithms have been developed by medical device companies and are proprietary. Thus, researchers who wish to investigate pulse contour analysis must rely on manual annotations or develop their own algorithms. We designed an automatic detection algorithm for pressure signals that locates the first peak following each heart beat. This is called the percussion peak in intracranial pressure (ICP) signals and the systolic peak in arterial blood pressure (ABP) and pulse oximetry (SpO2) signals. The algorithm incorporates a filter bank with variable cutoff frequencies, spectral estimates of the heart rate, rank-order nonlinear filters, and decision logic. We prospectively measured the performance of the algorithm compared to expert annotations of ICP, ABP, and SpO2 signals acquired from pediatric intensive care unit patients. The algorithm achieved a sensitivity of 99.36% and positive predictivity of 98.43% on a dataset consisting of 42,539 beats.
Keywords :
blood pressure measurement; blood vessels; cardiology; medical signal detection; medical signal processing; nonlinear filters; oximetry; spectral analysis; arterial blood pressure; automatic beat detection algorithm; cardiac arrhythmia detection; cardiac output monitoring; decision logic; intracranial pressure; pediatric intensive care unit patients; pressure signals; pulse contour analysis; pulse oximetry; rank-order nonlinear filters; spectral heart rate estimates; Algorithm design and analysis; Arterial blood pressure; Biomedical monitoring; Cranial pressure; Cutoff frequency; Detection algorithms; Filter bank; Frequency estimation; Heart beat; Signal design; Arterial blood pressure (ABP); component detection; intracranial pressure (ICP); pressure beat detection; pulse contour analysis; pulse oximetry; Algorithms; Animals; Artificial Intelligence; Biological Clocks; Blood Pressure; Diagnosis, Computer-Assisted; Humans; Intracranial Pressure; Manometry; Oscillometry; Oximetry; Pattern Recognition, Automated; Periodicity; Pulsatile Flow;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2005.855725