Abstract: Biomedical signals are those signals which are generated by the physiological activities of the body, which can be measured & monitored continuously and is an interdisciplinary subject. These signals take on one of the forms of chemical or electrical or acoustics, it can be in the form of continuous or discrete form. It is of utmost importance to study these signals which helps us to know the conditions of the human body. There are different types of biomedical signals, to name a few are Electroencephalogram (ECG), Electroencephalogram (EEG), Electromyography (EMG), Magnetoencephalogram (MEG), Mechanomyogram (MMG) & Electrooculography (EOG) which measure the electrical activities of a particular organ in the human body. Evoked Potentials (EP) or Event Related Potentials (EVP) is the potential developed in the body due to the application of external stimulus.. The stimulus can be visual or auditory or sensual accordingly they are called Visual Evoked Potential (VEP), Auditory Evoked Potential (AEP) & Somato Sensory Evoked Potential (SEP). These evoked potentials are embedded in the EEG signals and have very low amplitude. Extraction of visual evoked potentials (VEPs) from the human brain is generally very difficult due to its poor signal-to-noise ratio (SNR) property. Wavelet transform technique of estimation improves the SNR by a large amount in almost one sweep of EvokedPotential EP. The two different wavelet transforms such as Bi – Orthogonal wavelet transform and this wavelet transform has been used to improve the SNR. SNR comparison is made with the conventional ensemble averaging technique, where this technique requires more number of sweeps to improve the SNR. Comparison is made to understand the best Bi – Orthogonal wavelet transform for estimating the EP signal. In this paper, Visual Evoked Potential signals have been considered for the analysis.
Keywords: Bi – Orthogonal, Evoked Potential, Ensemble Averaging, SNR.