Minimizing outliers on cardiovascular signals: an open-source solution

Abstract Context: Intravenous cardiovascular recording of conscious animals is susceptible to outlier’s presence, due to freely movement and manipulations. These outliers can interfere on heart rate variability results, indicating erroneous results of sympathetic or parasympathetic modulation.Objective: Develop an automated computational approach to minimize the presence of outliers in cardiovascular recorded signals.Method: An application was developed according to the problem addressed based on free-use web frameworks.Results: The use of the proposed application detected and minimized respectively 1% and 0.97% of points outliers in signals of systolic arterial pressure (SAP) and pulse interval (PI) from a representative blood pressure recording. As until then the work of minimization of outliers was carried out manually; the use of the new application considerably reduced time spend analyzing the data.Conclusion: The proposed algorithm can detect and minimize interferent points, reducing chances of an erroneous interpretation about the cardiovascular modulation by the autonomic nervous system. The method can also significantly reduce the time of manual point-to-point screening performed by researchers.