Waveform estimation techniques for event-related bioelectric signals: a study of performance

Many bioelectric signals result from the electrical response of a physiological system to an impulse that can be internal (ECG signals) or external (evoked potentials). A comparative study of performance of seven waveform estimation techniques used for event-related signals that are time-locked to a stimulus is presented in this paper. Computer generate 1 signals and noise for several signal-to-noise ratios (SNRs) are used to make ensembles of simulated noisy waveforms. The performance of each technique is numerically investigated using the root-mean-squared error and two well known SNR estimators. The results show that an adaptive impulse correlated filter performs the best. It is capable of estimating the deterministic component of the signal and removes the noise uncorrelated with stimulus even if this noise is colored and without the need for prealignment.