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i-manager's Journal on Digital Signal Processing (JDP)

Current Issue Vol. 11 Issue 2

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Volume 4 Issue 2 April - June 2016

Research Paper

Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques

K. Purushotham Prasad* , B. Anuradha**

* Research Scholar, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

** Professor, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

Prasad,P.K., and Anuradha.B. (2016). Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques. i-manager’s Journal on Digital Signal Processing, 4(2), 1-7. https://doi.org/10.26634/jdp.4.2.5991

Abstract

The electrocardiogram (ECG) signal is a graphical recording of the electrical potentials generated in association with heart activity, which is one of the many important physiological signals commonly used in clinical practice. The wellbeing and status of a fetus can be accessed from a fetal ECG signal. Detecting and analysing the fetal ECG is the primary objective of electronic fetal monitoring. This paper presents a method to separate fetal ECG signals from the maternal abdomen. The method is general and is able to separate the fetal ECG signals using any number of recording electrodes, including the difficult case of single channel. This approach is based on some simple mathematical model using convolution matrix and with the help of maternal ECG, the fetal ECG signals can be extracted from the maternal abdomen. Further, the fetal ECG signals are passed through wavelets and adaptive filter to reduce the noise in the fetal ECG. The results show that the proposed method has a promising performance.

References

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[9]. EC Karvounis, C Papaloukas, DI Fotiadis, and LK Michalis, (2004). “Fetal Heart Rate Extraction from Composite Maternal ECG Using Complex Continuous Wavelet Transform”. Computers in Cardiology, Vol. 31, pp. 737-740.

[10]. F. Mochimaru, Y. Fujimoto and Y. Ishikawa, (2002). “Detecting the Fetal Electrocardiogram by Wavelet Theor y-Based Methods”. Progress in Biomedical Research, Vol. 7, No. 3.

[11]. Peters M., Crowe J., Piéri J., (2001). “Fetal Monitoring the Fetal Heart Non-Invasively: A Review of Methods”. J. Perinat. Med., Vol. 29, pp. 408-16.

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Research Paper

An Approach of ECG Analysis for Diagnosis of Heart Diseases

Ekta Gajendra* , Jitendra Kumar**

* PG Scholar, Department of Communication Engineering, SSTC (SSGI), Bhilai, (C.G), India.

** Assistant Professor, Department of Electronics and Instrumentation, SSTC (SSGI), Bhilai, (C.G), India.

Gajendra,E., and Kumar,J. (2016). An Approach of ECG Analysis for Diagnosis of Heart Diseases. i-manager’s Journal on Digital Signal Processing, 4(2), 8-16. https://doi.org/10.26634/jdp.4.2.5993

Abstract

In Today's World, heart problems are the major health concern people are facing. In order to prolong life, one must be fit and should keep a check on their health. Cardiac Arrhythmia is one such heart condition, which can be diagnosed from the persons ECG (Electrocardiogram). ECG is the graphical representation of the heart's electrical activity. Any change in the waveform of the ECG depicts change in the functioning of it, which can be used as a diagnostic measure. ECG Classification is done in 3 stages, first is de-noising of the ECG signal, in the second step, the authors perform feature Extraction and finally Classifies it. The authors use FIR Filter for signal de-noising and then, they have tried to do the analysis using DOM (Difference Operation Method) for feature extraction and LDA (Linear Discriminant Analysis) for the classification of ECG signal to predict if he/she is vulnerable to any such heart condition or not. On using the above named methods the authors achieve an accuracy of 98.077% and a sensitivity of 98.009%.

References

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[16]. Khan, T.T., Sultana, N., Reza, R.B., and Mostafa, R. (2015). “ECG Feature Extraction in Temporal Domain and Detection of Various Heart Conditions”. ICEEICT, pp. 1-6.

[17]. Sahoo, S.K., Subudhi, A.K., Kanungo, B., and Sabut, S.K. (2015). “Feature Extraction of ECG Signal based on Wavelet Transform for Arrhythmia Detection”. IEEE, pp. 1-5.

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[19]. Saminu, S., Özkurt, N., and Karaye, I.A. (2014). “Wavelet Feature Extraction for ECG Beat Classification”. IEEE 6^th International Conference on Adaptive Science and Technology (ICAST), pp. 1-6.

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[21]. Biswas, U., Das, A., Debnath, S., and Oishee, I., (2014). “ECG Signal Denoising by Using Least-Mean- Square and Normalised-Least-Mean-Square Algorithm Based Adaptive Filter”. 3^rd International Conference On Informatics, Electronics & Vision, pp. 1-6.

[22]. Zhang, N., Nie, Z., Luo, Y., Du, L., Wang, X., and Wang, L., (2014). “A Reconfigurable Overlapping FFT/IFFT Filter for ECG Signal De-noising”. International Symposium on Bioelectronics and Bioinformatics IEEE, pp. 1-4.

[23]. Biswas, U., and Maniruzzaman, M., (2014). “Removing Power Line Interference from ECG Signal Using Adaptive Filter and Notch Filter”. ICEEICT.

[24]. Hashim, F.R., Soraghan, J.J., Petropoulakis, L., and Daud, N.G.N., (2014). “EMG Cancellation from ECG Signals using Modified NLMS Adaptive Filters”. IEEE Conf. on Biomedical Engineering and Sciences (IECBES), pp. 735-739.

[25]. Gaikwad, K.M., and Chavan, M.S., (2014). “Removal of High Frequency Noise from ECG Signal Using Digital IIR Butterworth Filter”. GCWCN IEEE, pp. 121-124.

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[28]. Bhogeshwar, S.S., Soni, M.K., Bansal, D., (2014). “Design of Simulink Model to denoise ECG signal using various IIR & FIR filters”. ICROIT.

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Research Paper

A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB

Manjinder Kaur* , Sangeet Pal Kaur**

* PG Student, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

Kaur,M., and Kaur,S,P. (2016). A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB. i-manager’s Journal on Digital Signal Processing, 4(2), 17-23. https://doi.org/10.26634/jdp.4.2.5994

Abstract

This paper presents a new window for designing FIR low pass filter. While designing a FIR filter, there are two important parameters which must be taken care of which are transition width and ripples. Transition width should be as small as possible and ripples should be less both in pass band as well as stop band. There are different windows like Rectangular, Triangular, Hanning, Hamming, Blackman, etc., which are used for filter designing. The proposed window which is a modified form of Blackman window contains four cosine parameters and the simulation result shows that this window has better response when compared to Blackman Window.

References

[1]. Alan V. Oppenheim & Ronald W. Schafer, (1999). Discrete-Time Signal. Second Edition, Prentice-Hall, pp. 491-492.

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[4]. Zhenhe Sun, Wei Yu, Chen He, (2012). “FIR digital filter design and MATLABsimulation”. IEEE, International Conference on Measurement, Information and Control(MIC), pp. 677-680, May 18-20.

[5]. Sonika Gupta, Aman Panghal, (2012). “Performance Analysis of FIR Filter Design by Using Rectangular, Hanning and Hamming Windows methods”. International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 2, No. 6.

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[8]. Alia Ahmed Eleti and Amer R. Zerek, (2013). “FIR Digital Filter Design By Using Windows Method With MATLAB”. IEEE, th 14 international Conference on Sciences and Techniques of Automatic Control & Computer Engineering, Sousse, Tunisia, pp. 282-287, December 20- 22.

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Research Paper

Image Edge Preserving Filter with Impulse Noise Detection and Removal

Neelima* , Pankaj Mohindru, Pooja Mohindru*

* PG Scholar, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

-* Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

Neelima., Mohindru,P., and Mohindru,P. (2016). Image Edge Preserving Filter with Impulse Noise Detection and Removal. i-manager’s Journal on Digital Signal Processing, 4(2), 24-33. https://doi.org/10.26634/jdp.4.2.5995

Abstract

This paper illustrates a new non-linear image edge-preserving filter, used for the detection and elimination of immense frequency impulse noise from digital images. Schemed method subsists of two stages i.e., pixel position detection and filtering. Simulation analysis has been performed on distinct images and results have been demonstrated in comparison to some previously designed filters. The proposed scheme works in a satisfactory way even upon noise densities in a high range of 95% to 97% in both visual presentation and quantitative measures. This designed filter preserves the edges of images with high degree of accuracy. Performance parameters such as PSNR, MAE, RMSE, and SSIM are better than most of the schemes currently in use.

References

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Research Paper

Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP

Anuja Mishra* , Sharad Mohan Shrivastava**

* PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.

** Assistant Professor, Department of Electronics & Telecommunication, Shri Shankaracharya Technical Campus, Bhilai, India.

Mishra,A., and Shrivastava,S,M. (2016). Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP. i-manager’s Journal on Digital Signal Processing, 4(2), 34-42. https://doi.org/10.26634/jdp.4.2.5996

Abstract

Next-generation communication evolution towards 4G promises to meet the demands for ubiquitous communication. MIMO technology convolved with Optical fiber has become a mandatory requirement to achieve the goals of future communications. This paper describes the System design methodology for MIMO DSP platform. Software simulations provide flexibility, hence the authors simulate results using a software named “Optiwave's Optisystem”. The authors propose a transmission fiber for mode-division multiplexed transmission with multiple-input multiple-output (MIMO) digital signal processing supporting six spatial and polarisation modes. To increase the transmission capacity of fewmode fiber (FMF) drastically, Wavelength-Division Multiplexing Mode-Division Multiplexing (WDM-MDM), an optical MIMO technique, can be applied. With WDM-MDM, different mode groups, propagating in FMF are used to carry different information.

References

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i-manager's Journal on Digital Signal Processing (JDP)

Current Issue Vol. 11 Issue 2

Most Read

Most Cited

Volume 4 Issue 2 April - June 2016

Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques

K. Purushotham Prasad* , B. Anuradha**

* Research Scholar, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India. ** Professor, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

Prasad,P.K., and Anuradha.B. (2016). Fetal ECG Extraction Using Wavelet and Adaptive Filtering Techniques. i-manager’s Journal on Digital Signal Processing, 4(2), 1-7. https://doi.org/10.26634/jdp.4.2.5991

Abstract

References

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An Approach of ECG Analysis for Diagnosis of Heart Diseases

Ekta Gajendra* , Jitendra Kumar**

* PG Scholar, Department of Communication Engineering, SSTC (SSGI), Bhilai, (C.G), India. ** Assistant Professor, Department of Electronics and Instrumentation, SSTC (SSGI), Bhilai, (C.G), India.

Gajendra,E., and Kumar,J. (2016). An Approach of ECG Analysis for Diagnosis of Heart Diseases. i-manager’s Journal on Digital Signal Processing, 4(2), 8-16. https://doi.org/10.26634/jdp.4.2.5993

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A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB

Manjinder Kaur* , Sangeet Pal Kaur**

* PG Student, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India. ** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

Kaur,M., and Kaur,S,P. (2016). A New Proposed Window for Designing FIR Low Pass Filter Using MATLAB. i-manager’s Journal on Digital Signal Processing, 4(2), 17-23. https://doi.org/10.26634/jdp.4.2.5994

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Image Edge Preserving Filter with Impulse Noise Detection and Removal

Neelima* , Pankaj Mohindru**, Pooja Mohindru***

* PG Scholar, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India. **-*** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

Neelima., Mohindru,P., and Mohindru,P. (2016). Image Edge Preserving Filter with Impulse Noise Detection and Removal. i-manager’s Journal on Digital Signal Processing, 4(2), 24-33. https://doi.org/10.26634/jdp.4.2.5995

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Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP

Anuja Mishra* , Sharad Mohan Shrivastava**

* PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India. ** Assistant Professor, Department of Electronics & Telecommunication, Shri Shankaracharya Technical Campus, Bhilai, India.

Mishra,A., and Shrivastava,S,M. (2016). Few-Mode Fibers Supporting 6 Spatial and Polarisation Modes for Mode-Division-Multiplexed Transmission with MIMO DSP. i-manager’s Journal on Digital Signal Processing, 4(2), 34-42. https://doi.org/10.26634/jdp.4.2.5996

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* Research Scholar, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

** Professor, Department of Electronics and Communication Engineering, S V University College of Engineering, Tirupati, India.

* PG Scholar, Department of Communication Engineering, SSTC (SSGI), Bhilai, (C.G), India.

** Assistant Professor, Department of Electronics and Instrumentation, SSTC (SSGI), Bhilai, (C.G), India.

* PG Student, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

** Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, India.

Neelima* , Pankaj Mohindru, Pooja Mohindru*

* PG Scholar, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

-* Assistant Professor, Department of Electronics and Communication Engineering, Punjabi University, Patiala, Punjab, India.

* PG Scholar, Department of Communication Engineering, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.

** Assistant Professor, Department of Electronics & Telecommunication, Shri Shankaracharya Technical Campus, Bhilai, India.