Research PapersNo Access

DCT-BASED VARIABLE STEP SIZE GRIFFITHS' LMS ALGORITHM FOR RANDOM NOISE CANCELLATION IN ECGs

VEENA N. HEGDE

Department of Instrumentation Technology, BMS College of Engineering, Bangalore, India

Search for more papers by this author

RAVISHANKAR DEEKSHIT

Department of Electrical Engineering, BMS College of Engineering, Bangalore, India

Search for more papers by this author

, and

P. S. SATYANARAYANA

Department of Electronics and Communication, BMS College of Engineering, Bangalore, India

Search for more papers by this author

https://doi.org/10.1142/S021951941250025XCited by:0 (Source: Crossref)

Abstract

This paper presents a new random noise cancellation technique for cancelling muscle artifact effects from ECG using ALE in the transformed domain. For this a transform domain variable step size griffith least mean square (TVGLMS) algorithm is proposed. The technique is based on the adaptation of the gradient of the error surface. The method frees both the step size and the gradient from observation noise and reduces the gradient mis-adjustment error. The sluggishness introduced due to the averaging of the gradient in the time domain is overcome by the transformed domain approach. The proposed algorithm uses a discrete cosine transform (DCT)-based signal decomposition due to its improved frequency resolution compared to a discrete Fourier transform (DFT). Furthermore, as the data used symmetrical, DCT usage results in low leakage (bias and variance). The performance of the proposed method has been tested on ECG signals combined with WGN, extracted from MIT database, and compared with several existing techniques like LMS, NLMS, and VGLMS.

Keywords:

References

A. E. Ashley , V. Raxval and K. V. Froelicher , Int. J. Bio-Electromag. 50 ( 2002 ) . Google Scholar
U. R. Acharya , C. M. Lim and P. Joseph , Int. J. Innov. Technol. Biol. Med. 23 , 333 ( 2002 ) . Web of Science, Google Scholar
U. R. Acharya , N. Kannathal and S. M. Krishnan , Int. J. Physiol. Meas. 25 , 1139 ( 2004 ) . Crossref, Web of Science, Google Scholar
U. R. Acharya et al. , Int. J. Innov. Technol. Biol. Med. (ITBMRBM) 26 , 133 ( 2005 ) . Web of Science, Google Scholar
K. C. Chua et al. , J. Med. Eng. Technol. 32 , 145 ( 2008 ) . Crossref, Google Scholar
M. Pagani et al. , Circulation 95 , 1441 ( 1997 ) . Crossref, Web of Science, Google Scholar
E. D. Carlos , A. Alireza and K. Alireza , IEEE. Trans. Biomed. Eng. 41 , 197 ( 1999 ) . Google Scholar
B. Widrowet al., Adaptive noise cancelling: Principles and applications, Proc. Ann. Int. Conf. IEEE63 (1975) pp. 1692–1716. Google Scholar
J.-W. Lee and G. K. Lee , Int. J. Control. Autom. Syst. 137 ( 2005 ) . Web of Science, Google Scholar
Richard J. Zeidler, Performance analysis of LMS prediction filters, Annu. Int. Conf. (1990) pp. 1784–1793. Google Scholar
R. H. Kwong and E. W. Johnson , IEEE. Trans. Signal. Process. 40 , 1633 ( 1992 ) . Crossref, Web of Science, Google Scholar
R. W. Harris , D. Chabries and F. Bishop , Int. J. Acoustics. Speech. Signal. Process. 309 ( 1986 ) . Crossref, Google Scholar
T. P. Pander, Design of adaptive filter with dynamic structure for ECG signal processing, 26th Annu. Int. Conf. IEEE EMBS (2004) pp. 137–142. Google Scholar
K. Iyer et al. , IEEE. Trans. Biomed. Eng. 33 , 1141 ( 1986 ) . Crossref, Web of Science, Google Scholar
L. Yip and Y. T. Zhang, Reduction of heart sounds from lung sounds recording by automated gain control and adaptive filtering techniques, Proc. 23rd Annu. Int. Conf. IEEE EMBS (2001) pp. 2154–2156. Google Scholar
S. Charleston and M. R. Azimi-Sadjadi , IEEE. Trans. Biomed. Eng. 43 , 421 ( 1996 ) . Crossref, Web of Science, Google Scholar
M. Kompis and E. Russi, Adaptive heart-noise reduction of lung sounds recorded by a single microphone, Proc. 14th Annu. Int. Conf. IEEE EMBS (2003) pp. 2416–2419. Google Scholar
J. Gnitecki, Z. Moussavi and H. Pasterkamp, Recursive least squares adaptive noise cancellation filtering for heart sound reduction in lung sounds recording, Proc. 25th Annu. Int. Conf. IEEE E MBS3 (2003) pp. 2416–2419. Google Scholar
L. J. Hadjileontiadis and S. M. Panas, Int. J. Med. Info. 52(3), 183 (1998). Crossref, Web of Science, Google Scholar
J. Okello et al. , IEEE. Int. Conf. Circuits. Syst. 5 , 170 ( 1998 ) . Google Scholar
S. Veena and S. V. Narasimhan , Int. J. Signal. Image. Video. Process. ( 2000 ) . Google Scholar
M. T. Pourazad , Z. Moussavi and G. Thomas , IEEE. Trans. Biomed. Eng. 44 , 216 ( 2006 ) . Google Scholar
M. T. Pourazad, Z. Moussavi and G. Thomas, Heart sound cancellation from lung sound recordings using adaptive threshold and 2D interpolation in time-frequency domain, Proc. 25th Annu. Int. Conf. IEEE EMBS (2003) pp. 2586–2589. Google Scholar
L. G. Griffiths , IEEE. Trans. Acoust. Speech. Signal. Process. 23 , 207 ( 1975 ) . Crossref, Google Scholar
J. R. Zeidler et al. , IEEE. Trans. Acoustics. Speech. Signal. Process. 26 , 240 ( 1978 ) . Crossref, Google Scholar
L. Griffiths , F. Smolka and L. Trembly , Int. J. Geophys. 42 , 742 ( 1977 ) . Google Scholar
D. Morgan and S. Craig , IEEE. Trans. Acoustics. Speech. Signal. Process. 23 , 207 ( 1976 ) . Google Scholar
S. Florian and N. J. Bershad, IEEE. Trans. Acoustics. Speech. Signal. Process. 36(7), (1998). Google Scholar
F. Beaufay, IEEE. Trans. Signal. Process. 43(2), (1995). Google Scholar
M. A. Shamma, Improving the speed and performance of adaptive equalizers via transform based adaptive filtering, Proc. 14th Int. Conf. Digital Signal Process2 (2002) pp. 1301–1304. Google Scholar
J. Zeidler, Proc. Annu. Int. Conf. IEEE. 78(12), 1784 (1990). Google Scholar
S. Haykin , Adaptive filter theory ( Prentice Hall , New York , 1986 ) . Google Scholar
J. Rickard and J. Zeidler , IEEE. Trans. Acoust. Speech. Signal. Process. 27 , 31 ( 1979 ) . Crossref, Google Scholar
D. I. Kim and P. De Wilde , Elsevier Signal Process 80 , 1629 ( 2000 ) . Crossref, Web of Science, Google Scholar
M. S. E. Abadil, S. Z. Moussavi and A. M. Far, Scientia. Iranica. 15(2), 195 (2008). Web of Science, Google Scholar
M. Z. U. Rahman, R. A. Shaik and D. V. R. K. Reddy, Int. J. Signal. Process. 3(5), (2009). Google Scholar
Vinay V, Roopashree V, Narasimhan SV, Shivamurti M, Active noise control using variable step-size Griffiths' LMS (VGLMS) algorithm on real-time platform, available at: http://nal-ir.nal.res.in/9219 . Google Scholar
Y.-H. Chen and H.-D. Fang, J. Acoust. Soc. Am. 91(6), (1992). Google Scholar
B. Gerdleet al., Modern Techniques in Neuroscience, eds. U. Windhorst and H. Johansson (Springer Verlag, Berlin) pp. 705–755. Google Scholar
D. I. Kim and P. De Wilde , Int. J. Signal. Processing. 80 , 1629 ( 2000 ) . Crossref, Web of Science, Google Scholar