Comparative Analysis for Cancellation of Baseline- Fluctuation in Emg Signal

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Electromyography (EMG) is an electrodiagnostic technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG is performed using an instrument called an Electromyograph, to produce a record called an Electromyogram. An EMG signal is a record of the stress/pressure in muscles which is measured by analysing the electrical potential generated by muscle cells when these cells are electrically or neurologically activated. These signals can be analyzed to detect medical abnormalities, activation level, or recruitment order, or to analyze the biomechanics of human or animal movement. EMG is a very sensitive and needs high actuations for proper diagnostic results but generally this is degraded by noise. There are various sources of noise which hinder the proper recording of EMG but the fluctuations in the baseline is the most alarming issue which is required to be cancelled appropriately for accurate diagnosis.The present work focus on the various quantitative techniques and their comparative study for elimination of noise present in EMG signal. Presenting these techniques through simulated EMG signal results gives their advantages and disadvantages in terms of both visual inspection and merit figures.For the removal of BLF we use three methods namely: Statistical Method, Moving Averaging Method and Digital Filter Design Method. For recording the EMG signals we have used concentric needle electrode.The only purpose of this work is to reduce BLF noise in EMG signal and present a comparison between the outputs obtained by using the listed three sequential techniques.