title: P-wave morphology assessment by a gaussian functions-based model in atrial fibrillation patients.
abstract: Aim of this study was to present a P-wave model, based on a linear combination of Gaussian functions, to quantify morphological aspects of P-wave in patients prone to atrial fibrillation (AF). Five-minute ECG recordings were performed in 25 patients with permanent dual chamber pacemakers. Patients were divided into high-risk and low-risk groups, including patients with and without AF episodes in the last 6 mo preceding the study, respectively. ECG signals were acquired using a 32-lead mapping system for high-resolution biopotential measurement (ActiveTwo, Biosemi, The Netherlands, sample frequency 2 kHz, 24-bit resolution). Up to 8 Gaussian models have been computed for each averaged P-wave extracted from every lead. The P-wave morphology was evaluated by extracting seven parameters. Classical time-domain parameters, based on P-wave duration estimation, have been also estimated. We found that the P-wave morphology can be effectively modeled by a linear combination of Gaussian functions. In addition, the combination of time-domain and morphological parameters extracted from the Gaussian function-based model of the P-wave improves the identification of patients having different risks of developing AF.
authors.affiliation: Department of Technologies and Health, Istituto Superiore di Sanità, Rome 00161, Italy. censi@iss.it
authors.forename: Federica
authors.initials: F
authors.lastname: Censi
authors.forename: G
authors.initials: G
authors.lastname: Calcagnini
authors.forename: C
authors.initials: C
authors.lastname: Ricci
authors.forename: R P
authors.initials: RP
authors.lastname: Ricci
authors.forename: M
authors.initials: M
authors.lastname: Santini
authors.forename: A
authors.initials: A
authors.lastname: Grammatico
authors.forename: P
authors.initials: P
authors.lastname: Bartolini
mesh_terms: D000368:Aged; D000465:Algorithms; D001185:Artificial Intelligence; D001281:Atrial Fibrillation / Q000175:diagnosis* / Q000503:physiopathology*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D015233:Models, Statistical; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity