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Effect of high-pass filtering on ECG signal on the analysis of patients prone to atrial fibrillation
Censi,Federica; Calcagnini,Giovanni; Triventi,Michele; Mattei,Eugenio; Bartolini,Pietro; Corazza,Ivan; Boriani,Giuseppe;
Annali dell'Istituto Superiore di Sanità , 2009, DOI: 10.1590/S0021-25712009000400012
Abstract: the aim of this study was to assess the effect of filtering techniques on the time-domain analysis of the ecg. multi-lead ecg recordings obtained from chronic atrial fibrillation (af) patients after successful external cardioversion have been acquired. several high-pass filtering techniques and three cut-off frequency values were used: bessel and butterworth four-pole and two-pole bidirectional and unidirectional filters, at 0.01, 0.05 and 0.5 hz low cut-off frequency. as a reference, a beat-by-beat linear piecewise interpolation was used to remove baseline wander, on each p-wave. results show that ecg filtering affects the estimation of p-wave duration in a manner that depends upon the type of filter used: particularly, the bidirectional filters caused negligible variation of p-wave duration, while unidirectional ones provoked an increase higher than 8%.
Study of Signal Denoising using Kaiser Window and Butterworth Filter
Richa Gupta,Onkar Chand
International Journal of Electronics and Computer Science Engineering , 2012,
Abstract: A signal in the communication system is the information containing part which is to be process, but during the processing of the signal some noise is added in the signal and signal becomes noisy. This is now mandatory to eliminate this noise from the signal to get information from the signal. In this paper, a wavelet filter based on Butterworth IIR filter and Kaiser Window FIR filter is designed for the signal analysis. Butterworth low pass IIR filter has limited application in signal denoising. It has maximally flat response in the pass band and, therefore, the filter has distorted output. It makes Butterworth filter little applicable in communication systems and other signal analysis technique. The newly designed matched wavelet filter presents a new concept for better signal analysis and disturbance detection in the communication systems. The limitation of Butterworth low pass filter in signal denoising and other applications can be eliminated by using this matched wavelet filter. We have improved performance in signal filtering by using Kaiser Wavelet filter. This Wavelet filter finds applications in signal analysis, communication system and image compression with a lot of other fields.
Nonlinear filtering in ECG Signal Enhancement  [PDF]
N. Siddiah,T.Srikanth,Y. Satish Kumar
International Journal of Computer Science and Communication Networks , 2012,
Abstract: High resolution ECG signals are needed in measuring cardiac abnormalities analysis. Generally baseline wander is one of the important artifact occurred in ECG signal extraction, this strongly affects the signal quality. In order to facilitate proper diagnosis these artifacts have to be removed. In this paper various non linear, non adaptive filtering techniques are presented for the removal of baseline wander removal from ECG signals. The performance characteristics of various filtering techniques are measured in terms of signal to noise ratio.
Nonlinear filtering in ECG Signal Enhancement  [PDF]
N. Siddiah,T.Srikanth,Y. Satish Kumar
International Journal of Computer Science and Communication Networks , 2012,
Abstract: High resolution ECG signals are needed in measuring cardiac abnormalities analysis. Generally baseline wander is one of the important artifact occurred in ECG signal extraction, this strongly affects the signal quality. In order to facilitate proper diagnosis these artifacts have to be removed. In this paper various non linear, non adaptive filtering techniques are presented for the removal of baseline wander removal from ECG signals. The performance characteristics of various filtering techniques are measured in terms of signal to noise ratio.
On the Implementation of FIR Filter with Various Windows for Enhancement of ECG signal
K.D. CHINCHKHEDE,,GOVIND SHARAN YADAV,,S.R HIREKHAN,,D.R SOLANKE
International Journal of Engineering Science and Technology , 2011,
Abstract: Digital filters plays very significant role in the analysis of the low frequency components in ECG signal. Numbers of biomedical signals are of low frequency, the removal of baseline wander and power line interference is a very important step in the pre-processing stage of ECG. This paper deals with the study of FIR filtering of ECG signals under noisy condition. The performance of FIR filter is evaluated on several ECGs, by artificially adding white Gaussian noises to raw ECG recordings, and studying the SNR and morphology of the filter outputs. Power spectral density and spectrogram analysis reveals the further details of ECG. The correlation analysis at various noise (SNR) levels 1 to 50 dB clearly indicate that the FIR filter efficiently enhances raw ECG signal at 20dB or higher levels of noise. We find FIR filter with Kaiser window works excellent as compared to the Gaussian, Blackman and Blackman-Harris window based FIR filter.
Adaptive Match-Filtering: A Biomedical Application to Identify T-Wave Alternans  [PDF]
Laura Burattini, Giovanni Ottaviano, Francesco Di Nardo, Sandro Fioretti
Natural Science (NS) , 2014, DOI: 10.4236/ns.2014.610071
Abstract: T-wave alternans (TWA), consisting in an alternation of the electrocardiographic (ECG) repolarization segment (T-wave), is a promising index of the risk of sudden cardiac death. By definition, it is characterized by a frequency component, termed fTWA, that matches half heart rate. The heart-rate adaptive match filter (AMF) based method is a technique for automatic TWA identification from the digital ECG. Aim of the present study was to provide a complete technical description of the filter able to explain its methodological principles. The AMF is usually realized as a 6th order Butterworth filter with a narrow (0.12 Hz) passing band centered in fTWA. It is applied in a bidirectional fashion, so that final filtering order is 12. While extracting the TWA component, the AMF simultaneously filters out every ECG component including noise and artefacts, and thus results are very robust. Goodness of the technique was tested using 8 synthetic ECG tracings corrupted by typical noisy factors, such as white random noise, baseline wanderings, heart-rate variability, and others. Six ECG tracings were affected by 100 μV TWA, whereas two were not. Results indicate that the AMF-based method is able to prevent false-positive and false-negative detections and, thus, represents a useful tool for a reliable TWA identification.


Extending the Concept of Analog Butterworth Filter for Fractional Order Systems  [PDF]
Anish Acharya,Saptarshi Das,Indranil Pan,Shantanu Das
Computer Science , 2012, DOI: 10.1016/j.sigpro.2013.07.012
Abstract: This paper proposes the design of Fractional Order (FO) Butterworth filter in complex w-plane (w=sq; q being any real number) considering the presence of under-damped, hyper-damped, ultra-damped poles. This is the first attempt to design such fractional Butterworth filters in complex w-plane instead of complex s-plane, as conventionally done for integer order filters. Firstly, the concept of fractional derivatives and w-plane stability of linear fractional order systems are discussed. Detailed mathematical formulation for the design of fractional Butterworth-like filter (FBWF) in w-plane is then presented. Simulation examples are given along with a practical example to design the FO Butterworth filter with given specifications in frequency domain to show the practicability of the proposed formulation.
ECG Signal Smoothing Based on Combining Wavelet Denoising Levels
S.A. Chouakri,F. Bereksi-Reguig,S. Ahmaidi,O. Fokapu
Asian Journal of Information Technology , 2012,
Abstract: We present in this study an algorithm of smoothing real noisy ECG signal based on the classical wavelet denoising theory. The key idea of our proposed algorithm consists on generating a constructed denoised ECG signal by extracting and combining the delimited QRS complexes from the 2nd level wavelet denoising and the P and T waves from the 4th or 5th level wavelet denoising outputs. The used classical denoising algorithm utilizes the `VisuShrink` calculus rule and the `soft` thresholding strategy. On the other hand, the best suitable wavelet function and decomposition DWT level, for the denoising process, are determined by the means of the mean square error value. Two synthesis parameters have been utilized: the output SNR and the MSE values. We have applied our proposed algorithm to a set of MIT-BIH Arrhythmia Database ECG records added to a simulated 5dB and 0 dB SNR white Gaussian noise where it has been noticed an improvement of the input SNR (5 dB) to an output value of, generally, around 10 dB. To evaluate our algorithm, a comparative study was carried out referred to the low pass Butterworth filter and the 4th and 5th level classical wavelet denoising process. The obtained results demonstrate the superior performance of our proposed algorithm regarded to the tested filtering techniques where the output SNR remains in the most of cases less than 7 dB in the case of the input 5 dB WGN.
Suppression of Noise in ECG Signal Using Low pass IIR Filters
Mohandas Choudhary,,Ravindra Pratap Narwaria
International Journal of Electronics and Computer Science Engineering , 2012,
Abstract: In Diagnosing of ECG Signal, Signal acquisition must be noise free. Experienced physicians are able tomake an informed medical diagnosis on heart condition by observing the ECG signal. This paper deals the application of the digital IIR filter on the raw ECG signal. In this paper Butterworth, Chebyshev Type-I and Chebyshev Type-II filter are utilized. At the end all these filter types are compared. In this paper using 222txt ECG data set from MIT-BIH arrhythmia database.
Clinical assessment of the effect of digital filtering on the detection of ventricular late potentials
Benchimol-Barbosa, P.R.;Barbosa, E.C.;Bomfim, A.S.;Ginefra, P.;Nadal, J.;
Brazilian Journal of Medical and Biological Research , 2002, DOI: 10.1590/S0100-879X2002001100005
Abstract: ventricular late potentials are low-amplitude signals originating from damaged myocardium and detected on the body surface by ecg filtering and averaging. digital filters present in commercial equipment may interfere with the ability of arrhythmia stratification. we compared 40-hz bispec (bi) and classical 40- to 250-hz band-pass butterworth bidirectional (bd) filters in terms of impact on time domain variables and diagnostic properties. in a transverse retrospective age-adjusted case-control study, 221 subjects with sinus rhythm without bundle branch block were divided into three groups after signal-averaged ecg acquisition: gi (n = 40), clinically normal controls, gii (n = 158), subjects with coronary heart disease without sustained monomorphic ventricular tachycardia (smvt), and giii (n = 23), subjects with heart disease and documented smvt. conventional variables analyzed from vector magnitude data after averaging to 0.3 μv final noise were obtained by application of each filter to the averaged signal, and evaluated in pairs by numerical comparison and by diagnostic agreement assessment, using conventional and optimized thresholds of normality. significant differences were found between bi and bd variables in all groups, with diagnostic results showing significant disagreement between both filters [kappa value of 0.61 (p<0.05) for gii and 0.31 for giii (p = ns)]. sensitivity for smvt was lower with bi than with bd (65.2 vs 91.3%, respectively, p<0.05). filters provided significantly different numerical and diagnostic results and the bi filter showed only limited clinical application to risk stratification of ventricular arrhythmia.
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