title: Computationally efficient QRS detection analysis based on dual-slope method.
abstract: This paper presents a computationally efficient QRS detection algorithm for wearable electrocardiogram (ECG) applications based on dual-slope analysis. In general, ECG signals of arrhythmias are pseudo-periodic and contaminated with noises like the patient's contraction muscles, respiration, 60 Hz interference and other types which impede correct QRS detection. To resolve this problem, in this paper, a technique is presented which is based on two slopes on both sides of a peak in ECG signal. Based on these slopes, a variable measuring steepness is developed and R peaks are detected. The algorithm was evaluated against MIT/BIH arrhythmia database and achieved 99.38% detection rate. This method was compared with one of the recently developed dual-slope based QRS detection methods. The results showed that the proposed method has 12.48 times faster runtime than the old method.
authors.forename: M Riadh
authors.initials: MR
authors.lastname: Arefin
authors.forename: Reza
authors.initials: R
authors.lastname: Fazel-Rezai
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000000981:diagnostic imaging; D016208:Databases, Factual; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D014463:Ultrasonography