A real-time algorithm for the quantification of blood pressure waveforms

• Published in: IEEE transactions on biomedical engineering Vol. 49; no. 7; pp. 662 - 670
• Main Authors: Navakatikyan, M.A., Barrett, C.J., Head, G.A., Ricketts, J.H., Malpas, S.C.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.07.2002; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Amplitude estimation; Animals; Arterial blood pressure; Autonomic Nervous System - physiology; Band pass filters; Baroreflex - physiology; Biological and medical sciences; Blood pressure; Blood Pressure Determination - methods; Blood Pressure Determination - statistics & numerical data; Filter bank; Frequency; Heart Rate - drug effects; Heart Rate - physiology; Medical sciences; Nasopharynx - physiology; Nitroprusside - pharmacology; Phenylephrine - pharmacology; Position measurement; Pulse measurements; Rabbits; Reflex - physiology; Signal analysis; Signal processing; Signal Processing, Computer-Assisted
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2002.1010849

A real-time algorithm for quantification of biological oscillatory signals, such as arterial blood pressure (BP) is proposed which does not require user intervention and works on waveforms complicated by rapid changes in the mean level, frequency, or by the presence of arrhythmia. The algorithm is based on the continous independent assessment of the refractory period (RP). In the first stage, a sample of the signal is band-pass filtered. During the next stage: 1) the local maxima in the filtered signal are identified and their pulse amplitudes (PA) measured on the side opposite to the possible notch position and 2) those maxima whose PA exceeds some threshold are selected and an array of RP values is formed as a fraction of the moving estimate of the interval between successive selected peaks. Finally, the original signal is analyzed by means of two moving averages (MAs) with short and long averaging time intervals. The true peaks are determined as the maxima between intersections of MAs if the peak-to-peak or the intersection-to-intersection intervals since the previous peak and the previous intersection exceed the R.P. The algorithm proved to be superior against three commercially available heartbeat detectors yielding an error rate of 0.09%.