title: Extended Kalman smoother with differential evolution technique for denoising of ECG signal.
abstract: Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.
authors.affiliation: Department of Electrical Engineering, NIT Rourkela, Rourkela, Odisha, India. damo.3093@gmail.com.
authors.forename: D
authors.identifier: http://orcid.org/0000-0003-1393-4382
authors.initials: D
authors.lastname: Panigrahy
authors.affiliation: Department of Electrical Engineering, NIT Rourkela, Rourkela, Odisha, India.
authors.forename: P K
authors.initials: PK
authors.lastname: Sahu
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000503:physiopathology; D019992:Databases as Topic; D004562:Electrocardiography; D006801:Humans; D016011:Normal Distribution; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio
keywords: Differential evolution (DE); ECG denoising; Extended Kalman smoother (EKS); Shannon energy and Hilbert transformation method for R peak detection