FIR cutoff frequency calculating for ECG signal noise removing using artificial neural network
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Adaptive filtering noisy transcranial Doppler signal by using artificial bee colony algorithm
Engineering Applications of Artificial Intelligence
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New generation of medical treatment has been supported by computerized processes. Signals recorded from the human body provide valuable information about the biological activities of body organs. The organs' characteristic topologies with temporal and spectral, properties, can be correlated with a normal or pathological function. In response to dynamic changes in the behavior of those organs, the signals exhibit time- varying, non-stationary responses. The signals are always contaminated by a drift and interference caused by several bioelectric phenomena, or by various types of noise, such as intrinsic noise from the recorder and noise from electrode-skin contact. In this paper we utilize Adaptive Filters for noise cancellation and analysis ECG signals. Keywords : Adaptive Filter, Noise Cancellation, ECG Signal, Matlab Program