Filtering of neurophysiologic signals.


Journal

Handbook of clinical neurology
ISSN: 0072-9752
Titre abrégé: Handb Clin Neurol
Pays: Netherlands
ID NLM: 0166161

Informations de publication

Date de publication:
2019
Historique:
entrez: 7 7 2019
pubmed: 7 7 2019
medline: 31 12 2019
Statut: ppublish

Résumé

Clinical neurophysiologic signals cover a broad range of frequencies. Filters help to emphasize waveforms that are of clinical or research interest and to mold their frequency characteristics to suit the purpose of the investigation. Some frequency content is obvious and well known, such as the alpha rhythm (8-11Hz) or spindles (12-14Hz) in the EEG. Other frequencies are not initially discriminable from background activity and require filtering in order to examine them, such as high-frequency oscillations (80-500Hz) in EEG and brainstem auditory evoked potentials (100-3000Hz). Often used to mitigate the effects of background noise or artifact, filters can be used specifically to attenuate unwanted frequencies, such as mains interference (50 or 60Hz) and electrode offset potential (<0.1Hz). For digital instrumentation, an antialiasing filter (below Nyquist) is always needed prior to sampling by the analog-to-digital converter. Once the signals are in the digital realm, sophisticated filtering operations can be carried out post hoc; but in order not to be misled, the neurophysiologist must always bear in mind the effect of filtering on the physiological waveform.

Identifiants

pubmed: 31277873
pii: B978-0-444-64032-1.00004-7
doi: 10.1016/B978-0-444-64032-1.00004-7
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

51-65

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

Richard C Burgess (RC)

Department of Neurology, Cleveland Clinic Foundation, Cleveland, OH, United States. Electronic address: burgesr@ccf.org.

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Classifications MeSH