title: R-point detection for noise affected ECG recording through signal segmentation.
abstract: In this work we propose a novel approach for filtering noise-affected electrocardiogram (ECG) signals. The proposed method, mainly based on signal approximation by means of linear segments, has been applied for R-peaks recognition and has been compared with both cardiologists' manual marking and the automatic Laguna's method. The obtained results show that when compared to the Laguna's method the proposed algorithm provides a smaller mean error and a better error distribution.
authors.affiliation: Department of Matter Physics and Electronic Engineering, University of Messina, Italy. mgaleano@ingegneria.unime.it
authors.forename: M
authors.initials: M
authors.lastname: Galeano
authors.forename: A
authors.initials: A
authors.lastname: Calisto
authors.forename: A
authors.initials: A
authors.lastname: Bramanti
authors.forename: S
authors.initials: S
authors.lastname: Serrano
authors.forename: G
authors.initials: G
authors.lastname: Campobello
authors.forename: B
authors.initials: B
authors.lastname: Azzerboni
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted