title: Real-time electrocardiogram P-QRS-T detection-delineation algorithm based on quality-supported analysis of characteristic templates.
abstract: The main objective of this study is to introduce a simple, low-latency, and accurate algorithm for real-time detection of P-QRS-T waves in the electrocardiogram (ECG) signal. In the proposed method, real-time signal preprocessing, which includes high frequency noise filtering and baseline wander reduction, is performed by applying discrete wavelet transform (DWT). A method based on signal first-order derivative and adaptive threshold adjustment is employed for real-time detection of the QRS complex. Moreover, detection and delineation of P- and T-waves are achieved by correlation analysis conducted between signal and their templates. Besides, signal quality is investigated online, and if the quality of the analysis window is unacceptable, then the algorithm will guess (estimate) the locations of P- and T-waves. The operating characteristics of the proposed algorithm are evaluated by its implementation to an artificially generated ECG signal whose quality is adjustable from the best (Quality, 100%) to the worst (Quality, ≤40%) cases based on the random-walk noise theory. The algorithm was applied to the MIT-BIH arrhythmia database, QT database, and Physionet/CinC challenge 2011competition database. The obtained results, which were based on the QT database, showed sensitivity and positive predictivity of Se=99.63% and P+=99.83%, Se=99.83% and P+=99.98%, and Se=99.74% and P+=99.89% for the detection of P-, QRS-, and T-waves, respectively, and the obtained results, which were based on the MIT-BIH arrhythmia database, showed Se=99.81% and P+=99.70% for the detection of the QRS complex. Moreover, it will be shown that the results of the proposed method are reliable for a minimum signal quality value of 70%. According to numerical assessments, 8-ms after the occurrence of R-wave, its location will be identified by the computer code of the proposed algorithm. This parameter is 198-ms and 177-ms for P- and T-waves, respectively.
authors: Department of Mechanical Engineering, K.N. Toosi University of Technology, Pardis Street, Molla-Sadra Avenue, Vanak. Sq., Tehran, Iran; Mechatronic Mechanisms Laboratory (MML), K.N. Toosi University of Technology, Pardis Street, Molla-Sadra Avenue, Vanak. Sq., Tehran, Iran.
authors: Atiyeh
authors: A
authors: Karimipour
authors: Department of Mechanical Engineering, K.N. Toosi University of Technology, Pardis Street, Molla-Sadra Avenue, Vanak. Sq., Tehran, Iran; Mechatronic Mechanisms Laboratory (MML), K.N. Toosi University of Technology, Pardis Street, Molla-Sadra Avenue, Vanak. Sq., Tehran, Iran. Electronic address: mrezahomaei@yahoo.com.
authors: Mohammad Reza
authors: MR
authors: Homaeinezhad
mesh_terms: D000465:Algorithms; D004562:Electrocardiography / Q000379:methods*; D006801:Humans
keywords: Correlation analysis; Electrocardiogram; P-wave template; Real-time P-wave detection–delineation; Real-time QRS complex detection; Real-time T-wave detection–delineation; T-wave template; Waveform clustering