Paper Info
Title
Characterizing sleeping trends from postures
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.
Year
DOI
Venue
2010
10.1109/ISWC.2010.5665853
Wearable Computers
Keywords
Field
DocType
accelerometers,biomechanics,biomedical measurement,physiological models,sleep,postures,sleeping trends,wrist-worn accelerometer
Mathematical optimization,Management science,Mathematics
Conference
ISSN
ISBN
Citations 
1550-4816 E-ISBN : 978-1-4244-9045-5
978-1-4244-9045-5
2
PageRank 
References 
Authors
0.47
0
3
Name
Order
Citations
PageRank
Marko Borazio1797.39
Ulf Blanke269936.03
Van Laerhoven, K.313821.80