title: QRS detection using adaptive filters: A comparative study.
abstract: Electrocardiogram (ECG) is one of the most important physiological signals of human body, which contains important clinical information about the heart. Monitoring of ECG signal is done through QRS detection. In this paper, an improved QRS detection algorithm, based on adaptive filtering principle, has been designed. Enumeration of the effectiveness of various LMS variants used in adaptive filtering based QRS detection algorithm has been done through fidelity parameters like sensitivity and positive predictivity. Whole family of LMS algorithm has been implemented for comparison. Sign-sign LMS, sign error LMS, basic LMS and normalized LMS are re-implemented, while variable leaky LMS, variable step-size LMS, leaky LMS, recursive least squares (RLS), and fractional LMS are novel combination presented in this paper. After analysis of the obtained results, performance of leaky-LMS algorithm is found to be the best with sensitivity, positive predictivity, and processing time of 99.68%, 99.84%, and 0.45s respectively. Reported results are tested and evaluated over MIT/BIH arrhythmia database. Presented study also concludes that the performance of most of the variants gets affected due to low SNR but the Leaky LMS performs better even under heavy noise conditions.
authors.affiliation: PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, MP 482005, India. Electronic address: er.shweta.jbp@gmail.com.
authors.forename: Shweta
authors.initials: S
authors.lastname: Jain
authors.affiliation: Department of Computer Application, National Institute of Technology, Raipur, CG 492010, India. Electronic address: ahirwalmitul@gmail.com.
authors.forename: M K
authors.initials: MK
authors.lastname: Ahirwal
authors.affiliation: PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, MP 482005, India. Electronic address: anilkdee@gmail.com.
authors.forename: Anil
authors.initials: A
authors.lastname: Kumar
authors.affiliation: PDPM Indian Institute of Information Technology, Design and Manufacturing Jabalpur, MP 482005, India. Electronic address: bajajvarun056@yahoo.co.in.
authors.forename: V
authors.initials: V
authors.lastname: Bajaj
authors.affiliation: Department of Electrical Engineering, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India. Electronic address: gksngfee@gmail.com.
authors.forename: G K
authors.initials: GK
authors.lastname: Singh
keywords: Adaptive filtering; Adaptive thresholding; ECG; Leaky-LMS; QRS complex detection