NDLI: Statistical characterization of actigraphy data during sleep and wakefulness states

Content Provider	IEEE Xplore Digital Library
Author	Adamec, O. Domingues, A. Paiva, T. Sanches, J.M.
Copyright Year	2010
Description	Author affiliation: Centro de Electroencefalografia e Neurologia Clínica, Faculdade de Medicina da Universidade de Lisboa, Portugal (Paiva, T.) \|\| Institute for Systems and Robotics at the Instituto Superior Técnico, Lisbon, Portugal (Domingues, A.; Sanches, J.M.) \|\| Faculty of Electrical Engineering and Computer Science, Department of Measurement and Control, VSB Technical University of Ostrava, Czech Republic (Adamec, O.)
Abstract	Human activity can be measured with actimetry sensors used by the subjects in several locations such as the wrists or legs. Actigraphy data is used in different contexts such as sports training or tele-medicine monitoring. In the diagnosis of sleep disorders, the actimetry sensor, which is basically a 3D axis accelerometer, is used by the patient in the non dominant wrist typically during an entire week. In this paper the actigraphy data is described by a weighted mixture of two distributions where the weight evolves along the day according to the patient circadian cycle. Thus, one of the distributions is mainly associated with the wakefulness state while the other is associated with the sleep state. Actigraphy data, acquired from 20 healthy patients and manually segmented by trained technicians, is used to characterize the acceleration magnitude during sleep and wakefulness states. Several mixture combinations are tested and statistically validated with conformity measures. It is shown that both distributions can co-exist at a certain time with varying importance along the circadian cycle.
Starting Page	2342
Ending Page	2345
File Size	800712
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5627774
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sleep Histograms Wrist Rician channels Sensors Monitoring Gaussian distribution
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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