Key result
An adaptive impulse correlated filter (AICF) for event-related bioelectric signals was shown to be equivalent to exponentially weighted averaging and was applied to real ECG and evoked potentials.
Why the study?
Does an adaptive impulse correlated filter improve signal-to-noise ratio compared to standard averaging techniques in event-related bioelectric signals?
Population
Real high-resolution ECG signals and time-varying somatosensory evoked potentials
Comparison
Adaptive impulse correlated filter using the LMS… vs Ensemble averaging and moving window averaging…
Design
Other
Authors
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AICF may enhance noise removal in time-locked ECG and evoked potentials; leaves open prospective validation before clinical adoption.
Does an adaptive impulse correlated filter improve signal-to-noise ratio compared to standard averaging techniques in event-related bioelectric signals?
The adaptive impulse correlated filter provides an effective method for estimating the deterministic component of event-related bioelectric signals and removing uncorrelated noise.
Laguna et al. (1992) studied this question. Adaptive impulse correlated filter (AICF) vs. Ensemble averaging (EA) and moving window averaging (MWA) was evaluated on Signal-to-noise ratio improvement, convergence, and misadjustment error. An adaptive impulse correlated filter (AICF) for event-related bioelectric signals was shown to be equivalent to exponentially weighted averaging and was applied to real ECG and evoked potentials.
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