Real time ocular and facial muscle artifacts removal from EEG signals using LMS adaptive algorithm

The EEG signal is most useful for clinical diagnosis and in biomedical research. ElectroOculoGram (EOG), ElectroMyoGram (EMG) artifact are produced by eye movement and facial muscle movement respectively. An adaptive filtering method is proposed to remove these artifacts signals from EEG signals. Proposed method uses horizontal EOG (HEOG), vertical EOG (VEOG), and EMG signals as three reference digital filter inputs. The real-time artifact removal is implemented by multi-channel Least Mean Square algorithm. The resulting EEG signals display an accurate and artifact free feature.