Automated sleep stage classification based on tracheal body sound and actigraphy
Abstract: The current gold standard for assessment of most sleep disorders is the in-laboratory polysomnography (PSG). This approach produces high costs and inconveniences for the patients. An accessible and simple preliminary screening method to diagnose the most common sleep disorders and to decide whether a PSG is necessary or not is therefore desirable. A minimalistic type-4 monitoring system which utilized tracheal body sound and actigraphy to accurately diagnose the obstructive sleep apnea syndrome was previously developed. To further improve the diagnostic ability of said system, this study aims to examine if it is possible to perform automated sleep staging utilizing body sound to extract cardiorespiratory features and actigraphy to extract movement features.A linear discriminant classifier based on those features was used for automated sleep staging using the type-4 sleep monitor. For validation 53 subjects underwent a full-night screening at Ulm University Hospital using the devel...
Abstract: Der aktuelle Goldstandard für die Beurteilung der meisten Schlafstörungen ist die Polysomnographie (PSG). Diese Methode der Diagnose ist mit hohen Kosten und Unannehmlichkeiten für die Patienten verbunden. Eine einfache Methode der Diagnose der häufigsten Schlafstörungen ist daher wünschenswert. Hierzu wurde ein minimalistischer Typ-4-Schlafmonitor, welcher Körperschall und Aktigraphie zur Diagnose des obstruktiven Schlafapnoe-Syndroms einsetzt, entwickelt. Um die Diagnosefähigkeit dieses Systems zu erweitern, soll in dieser Studie untersucht werden, ob der Schlafmonitor automatisiert Schlafstadien klassifizieren kann. Hierbei wird Körperschall verwendet, um kardiorespiratorische Merkmale zu extrahieren, und Aktigraphie, um Bewegungsmerkmale zu extrahieren.Ein auf diesen Merkmalen basierender linearer Diskriminanzklassifizierer wurde für die automatisierte Klassifizierung von Schlafstadien mit dem vorgestellten Typ-4-Schlafmonitor verwendet. Zur Validierung wurden 53 Probanden am ...
- Weitere Titel
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Automatische Schlafstadienklassifizierung basierend auf Körperschall und Aktigraphie
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Automated sleep stage classification based on tracheal body sound and actigraphy ; volume:17 ; day:22 ; month:02 ; year:2019
GMS german medical science / Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften ; 17 (22.02.2019)
- Klassifikation
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Medizin, Gesundheit
- Urheber
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Kalkbrenner, Christoph
Brucher, Rainer
Kesztyüs, Tibor
Eichenlaub, Manuel
Rottbauer, Wolfgang
Scharnbeck, Dominik
- DOI
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10.3205/000268
- URN
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urn:nbn:de:0183-0002680
- Rechteinformation
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Open Access; Open Access; Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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14.08.2025, 10:44 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Kalkbrenner, Christoph
- Brucher, Rainer
- Kesztyüs, Tibor
- Eichenlaub, Manuel
- Rottbauer, Wolfgang
- Scharnbeck, Dominik
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