Abstract— The main aim of our paper is to give a way to
cancel noise in biomedical signals like ECG which are
non-stationary.ECG is the recording of the electric
conductivity of the heart and is used in investigation of
many heart diseases. In the recording process, the noise
through various sources take account in the corruption
of the ECG signal. The main sources of noise are motion
artifacts, muscle contraction, respiration, electrode
contact, and power line interference. Noise generated by
these sources is non-stationary. Since doctors are
interested in the peaks of the ECG but because of the
non-stationary noise they face hindrances in getting the
information signal. An appropriate filtering technique is
required to extract the information signal from a noisy
environment. Fixed coefficient FIR filters cannot be used
in this case, because the statistics of the signal are not
known. Adaptive filtration is the best possible solution.
It’s a simple but powerful filtering technique that
works on the recursive algorithm. The algorithms are used
to update the filter coefficients in such a way that the
noise is canceled out from the signal and a noise-free signal is recovered.

Keywords: Adaptive filters, Adaptive
algorithms, LMS, NLMS, RLS, ECG

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Credits:

Nabeel Ahmed1, MansoorKhan2, Yasir Ali Khan3,
Muhammad Ali Raza4,Saleem Khalid5, Muhammad Safder Shafi6
1COMSATS Institute of InformationTechnology (CIIT),
Islamabad, PAKISTAN