Title
Unobtrusive assessment of motor patterns during sleep based on mattress indentation measurementsUnobtrusive assessment of motor patterns during sleep based on mattress indentation measurements
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Research group
Laboratory Experimental Medicine and Pediatrics (LEMP)
Publication type
article
Publication
New York :IEEE,
Subject
Biology
Human medicine
Computer. Automation
Source (journal)
IEEE transactions on information technology in biomedicine / IEEE Engineering in Medicine and Biology Society. - New York
Volume/pages
15(2011):5, p. 787-794
ISSN
1089-7771
ISI
000294670700013
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
This study investigates how integrated bed measurements can be used to assess motor patterns (movements and postures) during sleep. An algorithm has been developed that detects movements based on the time derivate of mattress surface indentation. After each movement, the algorithm recognizes the adopted sleep posture based on an image feature vector and an optimal separating hyperplane constructed with the theory of support vector machines. The developed algorithm has been tested on a dataset of 30 fully recorded nights in a sleep laboratory. Movement detection has been compared to actigraphy, whereas posture recognition has been validated with a manual posture scoring based on video frames and chest orientation. Results show a high sensitivity for movement detection (91.2%) and posture recognition (between 83.6% and 95.9%), indicating that mattress indentation provides an accurate and unobtrusive measure to assess motor patterns during sleep.
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