Borazio, Marko ; Blanke, Ulf ; Laerhoven, Kristof Van (2010)
Characterizing Sleeping Trends from Postures.
Proceedings of the 14th IEEE International Symposium on Wearable Computers (ISWC 2010). Shanghai, China (07.11.2010-11.11.2010)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
We present an approach to model sleeping trends, using a light-weight setup to be deployed over longer time-spans and with a minimum of maintenance by the user. Instead of characterizing sleep with traditional signals such as EEG and EMG, we propose to use sensor data that is a lot weaker, but also less invasive and that can be deployed unobtrusively for longer periods. By recording wrist-worn accelerometer data during a 4-week-long study, we explore in this poster how sleeping trends can be characterized over long periods of time by using sleeping postures only.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2010 |
| Autor(en): | Borazio, Marko ; Blanke, Ulf ; Laerhoven, Kristof Van |
| Art des Eintrags: | Bibliographie |
| Titel: | Characterizing Sleeping Trends from Postures |
| Sprache: | Englisch |
| Publikationsjahr: | 2010 |
| Ort: | Seoul, South Korea |
| Verlag: | IEEE Press |
| Veranstaltungstitel: | Proceedings of the 14th IEEE International Symposium on Wearable Computers (ISWC 2010) |
| Veranstaltungsort: | Shanghai, China |
| Veranstaltungsdatum: | 07.11.2010-11.11.2010 |
| Kurzbeschreibung (Abstract): | We present an approach to model sleeping trends, using a light-weight setup to be deployed over longer time-spans and with a minimum of maintenance by the user. Instead of characterizing sleep with traditional signals such as EEG and EMG, we propose to use sensor data that is a lot weaker, but also less invasive and that can be deployed unobtrusively for longer periods. By recording wrist-worn accelerometer data during a 4-week-long study, we explore in this poster how sleeping trends can be characterized over long periods of time by using sleeping postures only. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Eingebettete Sensorsysteme |
| Hinterlegungsdatum: | 17 Jan 2012 09:54 |
| Letzte Änderung: | 05 Aug 2021 09:47 |
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