A high-speed C++/MEX solution for long-duration arterial blood pressure characteristic locations detection |
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Authors: | MR Homaeinezhad A Ghaffari M Aghaee HN Toosi R Rahmani |
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Institution: | 1. Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran;2. CardioVascular Research Group (CVRG), K.N. Toosi University of Technology, Tehran, Iran;3. Department of Mechatronic Engineering, K.N. Toosi University of Technology, Tehran, Iran;4. Tehran University of Medical Science (TUMS), Cardiovascular Division (Catheter Laboratory) of Imam Khomeini Hospital, Tehran, Iran |
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Abstract: | The major concentration of this study is to describe the structure of a C++/MEX solution for robust detection and delineation of arterial blood pressure (ABP) signal events. Toward this objective, the original ABP signal was pre-processed by application of à trous discrete wavelet transform (DWT) to extract several dyadic scales. Then, a sliding window with fixed length was moved on the appropriately selected scale. In each slid, mean, variance, Skewness and Kurtosis values of the excerpted segment were superimposed to generate a newly defined multiple higher order moments (MHOM) metric to be used as the detection decision statistic (DS). Then, after application of an adaptive-nonlinear transformation for making the DS baseline static, the histogram parameters of the enhanced DS were used for regulation of the α-level Neyman–Pearson classifier aimed for false alarm probability (FAP)-bounded delineation of the ABP events. The proposed method was applied to all 18 subjects of the MIT-BIH Polysomnographic Database (359,000 beats). The end-systolic and end-diastolic locations of the ABP signal as well as the dicrotic notch pressure were extracted and values of sensitivity Se = 99.86% and positive predictivity P+ = 99.95% were obtained for the detection of all ABP events. This paper proves the proposed MHOM-based ABP events detection–delineation algorithm as an improvement because of its merits such as: high robustness against measurement noises, acceptable detection–delineation accuracy of the ABP events in the presence of severe heart valvular, arrhythmic dysfunctions within a tolerable computational burden (processing time) and having no parameters dependency on the acquisition sampling frequency. |
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