Digital filter design for electrophysiological data--a practical approach.
By Andreas Widmann, Erich Schröger, Burkhard Maess. Journal of Neuroscience Methods, 2015
659 citations recorded by the source corpus.
Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience
View Paper: https://www.semanticscholar.org/paper/27971b6c30851ea1046a2504a50cbec37459e78d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cardiology and Cardiovascular Medicine
In Cognitive Neuroscience
- Michael W. Tangermann
- Christian Andreas Kothe
- Irene Winkler
- K. Müller
- Stefan Debener
- T. Mullen
- Alexandre Gramfort
- Miad Faezipour
Citations in the corpus
- Sleep Stage Classification Using EEG Signal Analysis: A Comprehensive Survey and New Investigation (2016, methodology): “It is considered very efficient when high throughput and sharp cutoffs are required, whereas FIR filters are desirable in adaptive signal processing because of their stability during adaptation [128,134].”
- Analysing concurrent transcranial magnetic stimulation and electroencephalographic data: A review and introduction to the open‐source TESA software (2017, neutral): “As mentioned previously, filtering can have unintended consequences on event-related potentials (e.g. TMS-evoked potentials) and should be used with caution (Acunzo et al., 2012; Tanner et al., 2015; VanRullen, 2011; Widmann et al., 2014; Widmann and Schröger, 2012).”
- On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP (2015, background): “Filtering may distort the shape of ERP components, including peak amplitudes and onset latencies [18], but can improve classification performance [19], [20].”
- Autoreject: Automated artifact rejection for MEG and EEG data (2016, background): “Frequency filtering (Widmann et al., 2015) can often suppress many low frequency artifacts, but turns out to be insufficient for broadband artifacts.”
- The PREP pipeline: standardized preprocessing for large-scale EEG analysis (2015, background): “These concerns and a series of articles about the perils of filtering for ERP processing (Vanrullen, 2011; Acunzo et al., 2012; Rousselet, 2012; Widmann and Schröger, 2012; Widmann et al., 2014; Tanner et al., 2015) caused us to re-evaluate the approach.”