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Titolo:
The meaning of character combination for the separation of EEG-data
Autore:
Schult, J; Querengasser, J; Breidbach, O; Scheidt, B; Erler, T;
Indirizzi:
Univ Jena, Dept Pediat, D-6900 Jena, Germany Univ Jena Jena Germany D-6900 iv Jena, Dept Pediat, D-6900 Jena, Germany Childrens Hosp Cottbus, Cottbus, Germany Childrens Hosp Cottbus Cottbus Germany s Hosp Cottbus, Cottbus, Germany Ernst Haeckel Haus, TheoLab, D-07745 Jena, Germany Ernst Haeckel Haus Jena Germany D-07745 , TheoLab, D-07745 Jena, Germany
Titolo Testata:
THEORY IN BIOSCIENCES
fascicolo: 2, volume: 120, anno: 2001,
pagine: 107 - 114
SICI:
1431-7613(200109)120:2<107:TMOCCF>2.0.ZU;2-T
Fonte:
ISI
Lingua:
ENG
Soggetto:
INFANT-DEATH-SYNDROME; PRETERM INFANTS; FULL-TERM; HIGH-RISK; NEUROPHYSIOLOGICAL ASSESSMENT; 3-YEAR-OLD CHILDREN; IDENTIFYING INFANTS; BRAIN DYSMATURITY; SCORING SYSTEM; SLEEP;
Keywords:
Sudden Infant Death Syndrome; neonate spontaneous; EEG; frequency band scoring; character interpretation;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Citazioni:
50
Recensione:
Indirizzi per estratti:
Indirizzo: Schult, J Ernst Haeckel Haus, TheoLab, Berggasse 7, D-07745 Jena, Germany Ernst Haeckel Haus Berggasse 7 Jena Germany D-07745 na, Germany
Citazione:
J. Schult et al., "The meaning of character combination for the separation of EEG-data", THEOR BIOSC, 120(2), 2001, pp. 107-114

Abstract

Summ. Standard EEG risk evaluation works on scoring systems that use different types of questionnaires. Here, an alternative for SIDS (Sudden Infant Death Syndrome) risk detection is presented that is based exclusively on EEG data which possibly could substitute the procedure of questioning the parents and allow a direct qualification of the physiological disposition of the individual neonate: Using EEG-characters an approved SIDS-case could be discriminated as well against the group of "healthy" infants as against the"high-risk-group". The results of this study may confirm the evidence thatthe EEG analysis can be a promising approach to predict an increased SIDS risk.

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Documento generato il 05/12/20 alle ore 02:08:25