S A Hoeksel1, J R Jansen, J A Blom, J J Schreuder. 1. Department of Anesthesiology, Cardiovascular Research Institute Maastricht, Maastricht University, The Netherlands.
Abstract
OBJECTIVE: A novel algorithm to detect the dicrotic notch in arterial pressure signals is proposed. Its performance is evaluated using both aortic and radial artery pressure signals, and its robustness to variations in design parameters is investigated. METHODS: Most previously published dicrotic notch detection algorithms scan the arterial pressure waveform for the characteristic pressure change that is associated with the dicrotic notch. Aortic valves, however, are closed by the backwards motion of aortic blood volume. We developed an algorithm that uses arterial flow to detect the dicrotic notch in arterial pressure waveforms. Arterial flow is calculated from arterial pressure using simulation results with a three-element windkessel model. Aortic valve closure is detected after the systolic upstroke and at the minimum of the first negative dip in the calculated flow signal. RESULTS: In 7 dogs ejection times were derived from a calculated aortic flow signal and from simultaneously measured aortic flow probe data. A total of 86 beats was analyzed; the difference in ejection times was -0.6 +/- 5.4 ms (means +/- SD). The algorithm was further evaluated using 6 second epochs of radial artery pressure data measured in 50 patients. Model simulations were carried out using both a linear windkessel model and a pressure and age dependent nonlinear windkessel model. Visual inspection by an experienced clinician confirmed that the algorithm correctly identified the dicrotic notch in 98% (49 of 50) of the patients using the linear model, and 96% (48 of 50) of the patients using the nonlinear model. The position of the dicrotic notch appeared to be less sensitive to variations in algorithm's design parameters when a nonlinear windkessel model was used. CONCLUSIONS: The detection of the dicrotic notch in arterial pressure signals is facilitated by first calculating the arterial flow waveform from arterial pressure and a model of arterial afterload. The method is robust and reduces the problem of detecting a dubious point in a decreasing pressure signal to the detection of a well-defined minimum in a derived signal.
OBJECTIVE: A novel algorithm to detect the dicrotic notch in arterial pressure signals is proposed. Its performance is evaluated using both aortic and radial artery pressure signals, and its robustness to variations in design parameters is investigated. METHODS: Most previously published dicrotic notch detection algorithms scan the arterial pressure waveform for the characteristic pressure change that is associated with the dicrotic notch. Aortic valves, however, are closed by the backwards motion of aortic blood volume. We developed an algorithm that uses arterial flow to detect the dicrotic notch in arterial pressure waveforms. Arterial flow is calculated from arterial pressure using simulation results with a three-element windkessel model. Aortic valve closure is detected after the systolic upstroke and at the minimum of the first negative dip in the calculated flow signal. RESULTS: In 7 dogs ejection times were derived from a calculated aortic flow signal and from simultaneously measured aortic flow probe data. A total of 86 beats was analyzed; the difference in ejection times was -0.6 +/- 5.4 ms (means +/- SD). The algorithm was further evaluated using 6 second epochs of radial artery pressure data measured in 50 patients. Model simulations were carried out using both a linear windkessel model and a pressure and age dependent nonlinear windkessel model. Visual inspection by an experienced clinician confirmed that the algorithm correctly identified the dicrotic notch in 98% (49 of 50) of the patients using the linear model, and 96% (48 of 50) of the patients using the nonlinear model. The position of the dicrotic notch appeared to be less sensitive to variations in algorithm's design parameters when a nonlinear windkessel model was used. CONCLUSIONS: The detection of the dicrotic notch in arterial pressure signals is facilitated by first calculating the arterial flow waveform from arterial pressure and a model of arterial afterload. The method is robust and reduces the problem of detecting a dubious point in a decreasing pressure signal to the detection of a well-defined minimum in a derived signal.
Authors: J A Zelano; W Ko; R Lazzaro; W D Lazenby; S Topaz; W J Kolff; O W Isom; K H Krieger Journal: Ann Thorac Surg Date: 1992-01 Impact factor: 4.330
Authors: Nils P Johnson; Wenguang Li; Xi Chen; Barry Hennigan; Stuart Watkins; Colin Berry; William F Fearon; Keith G Oldroyd Journal: Eur Heart J Date: 2019-08-14 Impact factor: 29.983
Authors: Alexei A Kamshilin; Igor S Sidorov; Laura Babayan; Maxim A Volynsky; Rashid Giniatullin; Oleg V Mamontov Journal: Biomed Opt Express Date: 2016-11-16 Impact factor: 3.732
Authors: Andrea Donelli; Jos R C Jansen; Bas Hoeksel; Paolo Pedeferri; Ramzi Hanania; Jan Bovelander; Francesco Maisano; Alessandro Castiglioni; Alfieri Ottavio; Jan J Schreuder Journal: J Clin Monit Comput Date: 2002 Apr-May Impact factor: 2.502
Authors: N A Garofalo; F J Teixeira-Neto; J C Rodrigues; S A Cerejo; A J A Aguiar; D R Becerra-Velásquez Journal: J Vet Intern Med Date: 2016-05-30 Impact factor: 3.333
Authors: Frank Lam; Hsiang-Wei Lu; Chung-Che Wu; Zekeriya Aliyazicioglu; James S Kang Journal: Comput Math Methods Med Date: 2017-05-22 Impact factor: 2.238
Authors: Sergio Valsecchi; Giovanni B Perego; Jan J Schreuder; Federica Censi; Jos R C Jansen Journal: J Clin Monit Comput Date: 2007-06-01 Impact factor: 1.977