@inproceedings{3ed8a6c8d4b345f38beee3cde876f3bf,
title = "Assessment of sleep/wake patterns using a non-contact biomotion sensor",
abstract = "We evaluate a contact-less continuous measuring system measuring respiration and activity patterns system for identifying sleep/wake patterns in adult humans. The system is based on the use of a novel non-contact biomotion sensor, and an automated signal analysis and classification system. The sleep/wake detection algorithm combines information from respiratory frequency, magnitude, and movement to assign 30 s epochs to either wake or sleep. Comparison to a standard polysomnogram system utilizing manual sleep stage classification indicates excellent results. It has been validated on overnight studies from 12 subjects. Wake state was correctly identified 69% and sleep with 88%. Due to its ease-of-use and good performance, the device is an excellent tool for long term monitoring of sleep patterns in the home environment in an ultraconvenient fashion.",
author = "{De Chazal}, Philip and Emer O'Hare and Niall Fox and Conor Heneghan",
year = "2008",
doi = "10.1109/IEMBS.2008.4649203",
language = "English",
isbn = "9781424418145",
publisher = "IEEE",
pages = "514--517",
booktitle = "Personalized Healthcare Through Technology: Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 20-24 August 2008, Vancouver, Canada",
note = "International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 20-08-2008",
}