Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 56-63 |
| Journal | IEEE Engineering in Medicine and Biology Magazine |
| Volume | 16 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1997 |
| MoE publication type | A1 Journal article-refereed |
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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 › Scientific › peer-review
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 -