Implementation of Adaptive filtering algorithms for removal of Noise from ECG signal Pramod R. Bokde Nitin K. Choudhari Department of Electronics Engg. Department of Electronics & Communication Engg. Priyadarshini Bhagwati College of Engg. Priyadarshini Bhagwati College of Engg. Nagpur, India Nagpur, India pramod.bokde@gmail.com drnitinchoudhari@gmail.com Abstract : Electrocardiography (ECG) is a non-invasive technique which is used for reading the electrical activity of the heart. It can be detected by several electrodes attached to the body surface and recorded using an external electronic circuit. This real noise free ECG signal can be used to detect different heart diseases, but a recorded ECG signal is not noise free. Noise existing in ECG signals can be removed using analog devices or using digital filters. As computational microprocessor power increases, the need to remove noise has been shifted to the use of digital filters. One of the very effective digital filters to remove the ECG noise is adaptive filtering techniques. In this paper, several adaptive filtering algorithms are proposed for noise cancellation of ECG signals and determining the accuracy of ECG signal features. Different adaptive filter algorithms used in this research work re Least Mean Square (LMS), Normalized Least Mean Squares (NLMS), Kernel Least Mean Squares (KLMS) and Normalized Kernel Least Mean Squares(NKLMS). The main focus of this paper is to compare the performance of the proposed kernel adaptive filter to already existing least mean squares filter and demonstrates usage of different adaptive filtering techniques to cancel noise sources from an ECG signal and to accurately detect its characteristics. Keywords: Artifact, Kernel, Accuracy, Baseline wander, PLI, QRS Complex, Adaptive filters etc. I. INTRODUCTION Electrocardiography (ECG) records the electrical activity of the heart. It can be detected by several electrodes attached to the different positions of the body and recorded by using an external electronic device. It is used as a test to gather information about different heart diseases. A typical ECG signal consists of a P-wave, a QRS complex and a T-wave. Figure 1 below shows the standard noise free ECG signal. Figure 1 : Standard ECG Signal ECG noise is contributed by environmental and biological sources. In this paper, the cause of each noise source along with the methods to eliminate the noise will be discussed. 1.1. Power Line Interference : It is an environmental noise in the ECG that results from poorly grounded ECG recording machine. Because of the alternating feature of the current, this noise appears at 50 Hz and its harmonics. For removal of this type of noise, Type I adaptive filter is used to subtract 50 Hz sinusoidal from ECG signal. 1.2. Baseline Wander : Baseline drift is a biological noise that appears in ECG signal. In this noise, an iso-electric line shifts its position. It can be caused by moving electrodes, patient movement, improper electrode contact etc. during recording of ECG signal. The adaptive filter that is used to remove this noise is a special case of notch filtering, with a notch at zero frequency to remove 0-0.5 Hz frequencies. For removal, type I filter is used with reference noise. 1.3. Motion Artifact :This is most difficult biological noise to cancel. The spectrum of this noise is broad and it completely overlaps the ECG signal spectrum. Linear filtering methods are unable to remove this noise source. Adaptive filter can eliminate this noise source by having the adaptive filter reference input set to an impulse value of 1 that corresponds to the beginning of the P-wave. In this way, adaptive filter only subtracts the P-QRS-T Pramod R Bokde et al, Int.J.Computer Technology & Applications,Vol 6 (1),51-56 IJCTA | Jan-Feb 2015 Available online@www.ijcta.com 51 ISSN:2229-6093