Biomedical Filters: ECG and EEG Signal Filtering

Biomedical Filters: ECG and EEG Signal Filtering Biomedical signals, like electrocardiograms (ECG) and electroencephalograms (EEG), are usually low-frequency, low-amplitude signals that are susceptible to noise contamination. Muscle activity (EMG), patient movement (tremors, respiration), inadequate electrode contact, and ambient electromagnetic noise are examples of common interferences. [1] [2] . Filtering is essential to attenuate these artifacts and reveal the true cardiac or neural waveform. Filters work by selectively passing desired frequency bands while attenuating unwanted frequencies. For example, analog filters use continuous-time circuits (capacitors, inductors, op-amps) with transfer functions  in the Laplace domain [3] , whereas digital filters operate on sampled data using H(z) in the z-domain. In ECG/EEG processing, analog filtering is often applied in the front end for tasks like antialiasing and baseline drift removal, followed by digital filtering for prec...