Signal processing in prolonged EEG recordings during intensive care

Mark van Gils; Annelise Rosenfalck; Steven White; Pamela Prior; John Grade; Lotfi Senhadji; Carsten Thomsen; Robert Ghosh; Richard Langford; Jensen Kjeld

doi:10.1109/51.637118

Signal processing in prolonged EEG recordings during intensive care

Mark van Gils, Annelise Rosenfalck, Steven White, Pamela Prior, John Grade, Lotfi Senhadji, Carsten Thomsen, Robert Ghosh, Richard Langford, Jensen Kjeld

Research output: Contribution to journal › Article

33 Citations (Scopus)

Abstract

Methods for analyzing and displaying EEG signals are discussed. The increasing availability and affordability of powerful computer equipment makes possible the use of ever more sophisticated signal processing techniques, which extract relevant (but not readily discernible) information from long-term EEG recordings and can easily identify important features in the EEG. Whether these techniques are actually taken up in clinical practice is heavily dependent on how well they match clinical requirements. This article concentrates on requirements set in the context of long-term recordings in the ICU that demand the ability to process short-term discrete events as well as long-term trend information. A huge range of potentially useful signal processing techniques exists. This article illustrates the value of some of these techniques for ICU signals using the EEG recordings collected during the IMPROVE project

Original language	English
Pages (from-to)	56-63
Journal	IEEE Engineering in Medicine and Biology Magazine
Volume	16
Issue number	6
DOIs	https://doi.org/10.1109/51.637118
Publication status	Published - 1997
MoE publication type	A1 Journal article-refereed

Fingerprint

Cite this

van Gils, M., Rosenfalck, A., White, S., Prior, P., Grade, J., Senhadji, L., Thomsen, C., Ghosh, R., Langford, R., & Kjeld, J. (1997). Signal processing in prolonged EEG recordings during intensive care. IEEE Engineering in Medicine and Biology Magazine, 16(6), 56-63. https://doi.org/10.1109/51.637118

@article{69b4b78ea68c4c9e9086fdda4ea34cb1,

title = "Signal processing in prolonged EEG recordings during intensive care",

abstract = "Methods for analyzing and displaying EEG signals are discussed. The increasing availability and affordability of powerful computer equipment makes possible the use of ever more sophisticated signal processing techniques, which extract relevant (but not readily discernible) information from long-term EEG recordings and can easily identify important features in the EEG. Whether these techniques are actually taken up in clinical practice is heavily dependent on how well they match clinical requirements. This article concentrates on requirements set in the context of long-term recordings in the ICU that demand the ability to process short-term discrete events as well as long-term trend information. A huge range of potentially useful signal processing techniques exists. This article illustrates the value of some of these techniques for ICU signals using the EEG recordings collected during the IMPROVE project ",

author = "{van Gils}, Mark and Annelise Rosenfalck and Steven White and Pamela Prior and John Grade and Lotfi Senhadji and Carsten Thomsen and Robert Ghosh and Richard Langford and Jensen Kjeld",

note = "Project code: T5SU000254",

year = "1997",

doi = "10.1109/51.637118",

language = "English",

volume = "16",

pages = "56--63",

journal = "IEEE Pulse",

issn = "2154-2287",

publisher = "IEEE Institute of Electrical and Electronic Engineers ",

number = "6",

}

Signal processing in prolonged EEG recordings during intensive care. / van Gils, Mark; Rosenfalck, Annelise; White, Steven; Prior, Pamela; Grade, John; Senhadji, Lotfi; Thomsen, Carsten; Ghosh, Robert; Langford, Richard; Kjeld, Jensen.

In: IEEE Engineering in Medicine and Biology Magazine, Vol. 16, No. 6, 1997, p. 56-63.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Signal processing in prolonged EEG recordings during intensive care

AU - van Gils, Mark

AU - Rosenfalck, Annelise

AU - White, Steven

AU - Prior, Pamela

AU - Grade, John

AU - Senhadji, Lotfi

AU - Thomsen, Carsten

AU - Ghosh, Robert

AU - Langford, Richard

AU - Kjeld, Jensen

N1 - Project code: T5SU000254

PY - 1997

Y1 - 1997

N2 - Methods for analyzing and displaying EEG signals are discussed. The increasing availability and affordability of powerful computer equipment makes possible the use of ever more sophisticated signal processing techniques, which extract relevant (but not readily discernible) information from long-term EEG recordings and can easily identify important features in the EEG. Whether these techniques are actually taken up in clinical practice is heavily dependent on how well they match clinical requirements. This article concentrates on requirements set in the context of long-term recordings in the ICU that demand the ability to process short-term discrete events as well as long-term trend information. A huge range of potentially useful signal processing techniques exists. This article illustrates the value of some of these techniques for ICU signals using the EEG recordings collected during the IMPROVE project

AB - Methods for analyzing and displaying EEG signals are discussed. The increasing availability and affordability of powerful computer equipment makes possible the use of ever more sophisticated signal processing techniques, which extract relevant (but not readily discernible) information from long-term EEG recordings and can easily identify important features in the EEG. Whether these techniques are actually taken up in clinical practice is heavily dependent on how well they match clinical requirements. This article concentrates on requirements set in the context of long-term recordings in the ICU that demand the ability to process short-term discrete events as well as long-term trend information. A huge range of potentially useful signal processing techniques exists. This article illustrates the value of some of these techniques for ICU signals using the EEG recordings collected during the IMPROVE project

U2 - 10.1109/51.637118

DO - 10.1109/51.637118

M3 - Article

VL - 16

SP - 56

EP - 63

JO - IEEE Pulse

JF - IEEE Pulse

SN - 2154-2287

IS - 6

ER -

Access to Document

10.1109/51.637118