Open AccessTechnique for QRS complex detection using particle swarm optimisation
Author(s) -
Jain Shweta,
Kumar Anil,
Bajaj Varun
Publication year - 2016
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2016.0023
Subject(s) - particle swarm optimization , qrs complex , sensitivity (control systems) , inertia , pattern recognition (psychology) , computer science , feature (linguistics) , artificial intelligence , algorithm , engineering , electronic engineering , physics , medicine , cardiology , linguistics , philosophy , classical mechanics
A new technique for QRS complex detection of electrocardiogram signals, using particle swarm optimisation (PSO)‐based adaptive filter (AF), is proposed. In the proposed method, the AF, based on PSO, is used to generate the feature. An effective detection algorithm, containing search‐backs for missed peaks, is also proposed. In the experiment, five PSO variants are tested on MIT‐BIH arrhythmia database. The linear decreasing inertia variant of PSO, achieves the best results with sensitivity, positive predictivity and detection error rate of 99.75, 99.83 and 0.42%, respectively. Effectiveness of the proposed method is validated by comparing fidelity parameter of proposed method with state‐of‐the‐art methods.