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Proceedings ArticleDOI

A filter bank architecture based on wavelet transform for ECG signal denoising

01 Sep 2017-

TL;DR: Results show that the proposed architecture requires less hardware, small area on the chip and lower cost compared to the previously designed architectures.
Abstract: One of the most important aspects of the electrocardiogram (ECG) signal processing is the removal of noises from the signals. In the present work a filter bank architecture based on wavelet transform is proposed for this purpose. Proposed design uses four levels of wavelet transform based filter bank for the ECG signals denoising. A digitized ECG signal is applied as an input to the four levels of wavelet transform based filter bank that separates the ECG signal from the noises. Obtained results show that the proposed architecture requires less hardware, small area on the chip and lower cost compared to the previously designed architectures.
Topics: Filter bank (64%), Wavelet transform (62%), Signal processing (53%)
Citations
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Journal ArticleDOI
01 Aug 2018-Isa Transactions
TL;DR: LZMA based ECG data compression technique is proposed, which achieves the highest signal to noise ratio, and lowest root mean square error, and is capable of distinguishing accurately between healthy, myocardial infarction, congestive heart failure and coronary artery disease patients.
Abstract: Heart rate monitoring and therapeutic devices include real-time sensing capabilities reflecting the state of the heart. Current circuitry can be interpreted as a cardiac electrical signal compression algorithm representing the time signal information into a single event description of the cardiac activity. It is observed that some detection techniques developed for ECG signal detection like artificial neural network, genetic algorithm, Hilbert transform, hidden Markov model are some sophisticated algorithms which provide suitable results but their implementation on a silicon chip is very complicated. Due to less complexity and high performance, wavelet transform based approaches are widely used. In this paper, after a thorough analysis of various wavelet transforms, it is found that Biorthogonal wavelet transform is best suited to detect ECG signal's QRS complex. The main steps involved in ECG detection process consist of de-noising and locating different ECG peaks using adaptive slope prediction thresholding. Furthermore, the significant challenges involved in the wireless transmission of ECG data are data conversion and power consumption. As medical regulatory boards demand a lossless compression technique, lossless compression technique with a high bit compression ratio is highly required. Furthermore, in this work, LZMA based ECG data compression technique is proposed. The proposed methodology achieves the highest signal to noise ratio, and lowest root mean square error. Also, the proposed ECG detection technique is capable of distinguishing accurately between healthy, myocardial infarction, congestive heart failure and coronary artery disease patients with a detection accuracy, sensitivity, specificity, and error of 99.92%, 99.94%, 99.92% and 0.0013, respectively. The use of LZMA data compression of ECG data achieves a high compression ratio of 18.84. The advantages and effectiveness of the proposed algorithm are verified by comparing with the existing methods.

38 citations


Journal ArticleDOI
TL;DR: A joint algorithm based on biorthogonal wavelet transform and run-length encoding (RLE) is proposed for QRS complex detection of the ECG signal and compressing the detected ECG data, which achieves the highest sensitivity and positive predictivity with the MIT-BIH arrhythmia database.
Abstract: Bradycardia can be modulated using the cardiac pacemaker, an implantable medical device which sets and balances the patient's cardiac health. The device has been widely used to detect and monitor the patient's heart rate. The data collected hence has the highest authenticity assurance and is convenient for further electric stimulation. In the pacemaker, ECG detector is one of the most important element. The device is available in its new digital form, which is more efficient and accurate in performance with the added advantage of economical power consumption platform. In this work, a joint algorithm based on biorthogonal wavelet transform and run-length encoding (RLE) is proposed for QRS complex detection of the ECG signal and compressing the detected ECG data. Biorthogonal wavelet transform of the input ECG signal is first calculated using a modified demand based filter bank architecture which consists of a series combination of three lowpass filters with a highpass filter. Lowpass and highpass filters are realized using a linear phase structure which reduces the hardware cost of the proposed design approximately by 50%. Then, the location of the R-peak is found by comparing the denoised ECG signal with the threshold value. The proposed R-peak detector achieves the highest sensitivity and positive predictivity of 99.75 and 99.98 respectively with the MIT-BIH arrhythmia database. Also, the proposed R-peak detector achieves a comparatively low data error rate (DER) of 0.002. The use of RLE for the compression of detected ECG data achieves a higher compression ratio (CR) of 17.1. To justify the effectiveness of the proposed algorithm, the results have been compared with the existing methods, like Huffman coding/simple predictor, Huffman coding/adaptive, and slope predictor/fixed length packaging.

22 citations


Cites background from "A filter bank architecture based on..."

  • ...However, the cascading of filters increases hardware complexity and power consumption in the circuit [33]....

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Book ChapterDOI
01 Jan 2019-
TL;DR: Dmey Wavelet Gaussian Filter (DWGF) have been proposed for removing Gaussian type of noise based on Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) performance measures and can be used for further analysis and detection of various skin diseases in Computer Aided Diagnostic System.
Abstract: Digital Image Processing initial step always starts with Image acquisition which is a start point for further analysis. Generally an analysis of skin lesion images is performed offline which increases the chances of having more disturbances in terms of noise, artifacts or air bubbles. Noise is one of the disturbing elements of this image acquisition which can lead to incorrect segmentation, analysis, or classification. In this paper, a new method Dmey Wavelet Gaussian Filter (DWGF) have been proposed for removing Gaussian type of noise based on Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) performance measures. Wavelet transformation filters, Low pass filters and proposed (DWGF) method have been tested on large data set of skin lesion images through quality measures in which low MSE (91.9083) and high PSNR (28.5313) proves to be better in DWGF. This method can be used for further analysis and detection of various skin diseases in Computer Aided Diagnostic System.

2 citations


References
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Book
01 Jan 1992-
TL;DR: Basic Concepts of Medical Instrumentation (W. Olson).
Abstract: Basic Concepts of Medical Instrumentation Basic Sensors and Principles Amplifiers and Signal Processing The Origin of Biopotentials Biopotential Electrodes Biopotential Amplifiers Blood Pressure and Sound Measurement of Flow and Volume of Blood Measurements of the Respiratory System Chemical Biosensors Clinical Laboratory Instrumentation Medical Imaging Systems Therapeutic and Prosthetic Devices Electrical Safety.

1,669 citations


"A filter bank architecture based on..." refers background in this paper

  • ...Some of these noises are power line interface, baseline drift, muscle contraction, motion artifacts, electrosurgical noise, instrumentation noise and electromyographic noises [6]....

    [...]


Journal ArticleDOI
G.M. Friesen1, T.C. Jannett, M.A. Jadallah, S.L. Yates  +2 moreInstitutions (1)
TL;DR: The noise sensitivities of nine different QRS detection algorithms were measured for a normal, single-channel, lead-II, synthesized ECG corrupted with five different types of synthesized noise: electromyographic interference, 60-Hz power line interference, baseline drift due to respiration, abrupt baseline shift, and a composite noise constructed from all of the other noise types.
Abstract: The noise sensitivities of nine different QRS detection algorithms were measured for a normal, single-channel, lead-II, synthesized ECG corrupted with five different types of synthesized noise: electromyographic interference, 60-Hz power line interference, baseline drift due to respiration, abrupt baseline shift, and a composite noise constructed from all of the other noise types. The percentage of QRS complexes detected, the number of false positives, and the detection delay were measured. None of the algorithms were able to detect all QRS complexes without any false positives for all of the noise types at the highest noise level. Algorithms based on amplitude and slope had the highest performance for EMG-corrupted ECG. An algorithm using a digital filter had the best performance for the composite-noise-corrupted data. >

1,034 citations


"A filter bank architecture based on..." refers background in this paper

  • ...Since, the ECG signal is corrupted by various types of noises [5], accurate detection of R wave with low computational complexity is a challenging problem....

    [...]


Journal ArticleDOI
TL;DR: AQRS complex detector based on the dyadic wavelet transform (D/sub y/WT) which is robust to time-varying QRS complex morphology and to noise is described which compared well with the standard techniques.
Abstract: In this paper, the authors describe a QRS complex detector based on the dyadic wavelet transform (D/sub y/WT) which is robust to time-varying QRS complex morphology and to noise. They design a spline wavelet that is suitable for QRS detection. The scales of this wavelet are chosen based on the spectral characteristics of the electrocardiogram (ECG) signal. They illustrate the performance of the D/sub y/WT-based QRS detector by considering problematic ECG signals from the American Heart Association (AHA) database. Seventy hours of data was considered. The authors also compare the performance of D/sub y/WT-based QRS detector with detectors based on Okada, Hamilton-Tompkins, and multiplication of the backward difference algorithms. From the comparison, results the authors observed that although no one algorithm exhibited superior performance in all situations, the D/sub y/WT-based detector compared well with the standard techniques. For multiform premature ventricular contractions, bigeminy, and couplets tapes, the D/sub y/WT-based detector exhibited excellent performance.

433 citations


"A filter bank architecture based on..." refers methods in this paper

  • ...Kadambe [15] proposed a wavelet transform based ECG signal denoising architecture which uses basic property of wavelet transform in which signal is passed through a recurrent series of low pass and high pass filters called wavelet tree as shown in Fig....

    [...]


Journal ArticleDOI
TL;DR: The power spectral analysis shows that the QRS complex could be separated from other interfering signals, and it is observed that a bandpass filter with a center frequency of 17 Hz and a Q of 5 yields the best signal-to-noise ratio.
Abstract: We present power spectral analysis of ECG waveforms as well as isolated QRS complexes and episodes of noise and artifact. The power spectral analysis shows that the QRS complex could be separated from other interfering signals. A bandpass filter that maximizes the signal (QRS complex)-to-noise (T-waves, 60 Hz, EMG, etc.) ratio would be of use in many ECG monitoring instruments. We calculate the coherence function and, from that, the signal-to-noise ratio. Upon carrying out this analysis on experimentaly obtained ECG data, we observe that a bandpass filter with a center frequency of 17 Hz and a Q of 5 yields the best signal-to-noise ratio.

416 citations


"A filter bank architecture based on..." refers methods in this paper

  • ...For this purpose, many denoising architectures have been proposed in last few years, such as digital filtering [7], Morphological transform [8], wavelet transform filter banks [9-12]....

    [...]


Journal ArticleDOI
13 Sep 2004-
Abstract: Low power consumption is crucial for medical implant devices. A single-chip, very-low-power interface IC used in implantable pacemaker systems is presented. It contains amplifiers, filters, ADCs, battery management system, voltage multipliers, high voltage pulse generators, programmable logic and timing control. A few circuit techniques are proposed to achieve nanopower circuit operations within submicron CMOS process. Subthreshold transistor designs and switched-capacitor circuits are widely used. The 200 k transistor IC occupies 49 mm/sup 2/, is fabricated in a 0.5-/spl mu/m two-poly three-metal multi-V/sub t/ process, and consumes 8 /spl mu/W.

330 citations


"A filter bank architecture based on..." refers background in this paper

  • ...The human heart consists of four major parts, the left atrium, the right atrium, the left ventricle and the right ventricle with the help of which blood is injected and purified and finally electrocardiogram (ECG) signal gets generated [3]....

    [...]


Performance
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No. of citations received by the Paper in previous years
YearCitations
20191
20182