ABSTRACT Advanced processing of lung sound (LS) recording is a significant means to separate heart sounds (HS) and combined low frequency noise from instruments (NI), with saving its characteristics. This paper proposes a new method of LS filtering which separates HS and NI simultaneously. It focuses on the application of least mean squares (LMS) algorithm with adaptive noise cancelling (ANC) technique. The second step of the new method is to modulate the reference input r1(n) of LMS-ANC to acquiesce combining HS and NI signals. The obtained signal is removed from primary signal (original lung sound recording-LS). The original signal is recorded from subjects and derived HS from it and it is modified by a band pass filter. NI is simulated by generating approximately periodic white gaussian noise (WGN) signal. The LMS-ANC designed algorithm is controlled in order to determine the optimum values of the order L and the coefficient convergence μ. The output results are measured using power special density (PSD), which has shown the effectiveness of our suggested method. The result also has shown visual difference PSD (to) normal and abnormal LS recording. The results show that the method is a good technique for heart sound and noise reduction from lung sounds recordings simultaneously with saving LS characteristics.
Cite this paper
Al-Naggar, N. (2013) A new method of lung sounds filtering using modulated least mean square—Adaptive noise cancellation. Journal of Biomedical Science and Engineering, 6, 869-876. doi: 10.4236/jbise.2013.69106.
 Gao, J., Hu, J. and Tung, W.-W. (2011) Facilitating joint chaos and fractal analysis of biosignals through nonlinear adaptive filtering. PLoS One, 1, e24331.
 Sathesh, K. and Muniraj, N.J.R. (2012) Survey on separation of heart sounds from lung sounds by adaptive filtering. International Journal of Microsystems Technology and its Applications (IJMTA), 1, 1-10.
 Pradeep, K.J. and Anant, K.G. (2011) Heart sound separating from lung sound using Lab VIE. IJCST, 2, 418-425.
 Thato, T. and Saeid, S. (2007) Separation of heart sound signal from lung sound signal by adaptive line enhancement. Proceedings of 15th European Signal Processing Conference (EUSIPCO), Poznan, 3-7 September 2007, 1231-1235.
 Schuttler, F., Penzel, T. and Wichert, P.V. (1997) Digital recording and computer-based analysis of lung sounds. Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Amsterdam, 31 October-3 November 1996, 2301-2302.
 Thato, T. (2008) Digital signal processing algorithms and techniques for the enhancement of lung sound measurements. Ph.D. Thesis, Loughborough University, Loughborough.
 Potdar, R.M., Anup, M., Vinni, S. and Tripti, R. (2012) Performance evaluation of different adaptive filtering algorithms for reduction of heart sound from lung sound. International Journal of Engineering and Advanced Technology (IJEAT), 1, 61-67.
 Gnitecki, J., Moussavi, Z. and Pasterkamp, H. (2003) Recursive least squares adaptive noise cancellation filtering for heart sound reduction in lung sounds recordings. Proceedings of the 25th Annual International Conference of the IEEE, Engineering in Medicine and Biology, 3, 2416-2419.
 Hadjileontiadis, L.J. and Panas, S.M. (1998) A waveletbased reduction of heart sound noise from lung sounds. International Journal of Medical Informatics, 52, 183-190. doi:10.1016/S1386-5056(98)00137-3
 Pourazad, M.T., Moussavi, Z. and Thomas, G. (2009) Heart sound cancellation from lung sound recordings using time-frequency filtering. IEEE Transactions on Biomedical Engineering, 44, 216-225.
 Gao, J.B., Sultan, H., Hu, J. and Tung, W.W. (2010) Denoising nonlinear time series by adaptive filtering and wavelet shrinkage: A comparison. IEEE Signal Processing Letters, 17, 237-240. doi:10.1109/LSP.2009.2037773
 Tung, W.W., Gao, J.B., Hu, J. and Yang, L. (2011) Recovering chaotic signals in heavy noise environments. Physical Review E, 83, 171-182.
 Yip, L. and Zhang, Y.T. (2001) Reduction of heart sounds from lung sounds recording by automated gain control and adaptive filtering techniques. Proceedings of the 23rd Annual International Conference of the IEEE, Engineering in Medicine and Biology Society, 3, 2154-2156.
 Sathesh, K. and Muniraj, N.J.R. (2012) Separation of heart sounds from lung sounds using LMS adaptive equalizer implementation in cadence tools. International Journal of Mechanic Systems Engineering (IJMSE), 2, 48-52.
 Abhishek, M. and Sinha, G.R. (2012) Denoising of PCG signal by using wavelet transforms. Advances in Computational Research, 4, 46-49.
 Flores-Tapia, D., Moussavi, Z. and Thomas, G. (2007) Heart sound cancellation based on multiscale products and linear prediction. IEEE Transactions on Biomedical Engineering, 54, 234-243.
 Ahlstrom, C., Liljefeldt, O., Hult, P. and Ask, P. (2005) Heart sound cancellation from lung sound recordings using recurrence time statistics and nonlinear prediction. IEEE Signal Processing Letters, 12, 812-815.
 Noman Al, N. (2012) Development of computerized recording channel of lung sound. Journal of Medical and Bioengineering (JOMB), 1, 52-55.
 Tsalaile, T., Naqvi, S., Nazarpour, K., Sanei, S. and Chambers, J. (2008) Blind source extraction of heart sound signals from lung sound recordings exploiting periodicity of the heart sound. IEEE ICASSP, 2008, 461-464.
 Karagiannis, A. and Constantinou, Ph. (2010) On the processing of white gaussiannoise biomedical signals with the empirical mode decomposition. Analysis of Biomedical Signals and Images, 20, 439-446.
 Garcés, L.E. (2007) Artifact removal from EEG signals using adaptive filters in cascade 1. Journal of Physics: Conference Series, 90, 012081.
 Lee, Y.J., Kim, P.U., Lee, G., Cho, J.H. and Kim, M.N. (2010) Single input ANC for suppression of breath sound. World Academy of Science, Engineering and Technology, 44, 1160-1162.