Characterization of movements during restless sleep in children: a pilot study

Lamprecht, Marnie L., Terrill, Philip I., Parsley, Chloe L. and Bradley, Andrew P. (2014). Characterization of movements during restless sleep in children: a pilot study. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Chicago, United States, (274-277). 26-30 August 2014. doi:10.1109/EMBC.2014.6943582

Attached Files (Some files may be inaccessible until you login with your UQ eSpace credentials)
Name Description MIMEType Size Downloads

Author Lamprecht, Marnie L.
Terrill, Philip I.
Parsley, Chloe L.
Bradley, Andrew P.
Title of paper Characterization of movements during restless sleep in children: a pilot study
Conference name 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Conference location Chicago, United States
Conference dates 26-30 August 2014
Convener IEEE
Proceedings title 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Journal name 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014
Place of Publication Piscataway, NJ, United States
Publisher IEEE
Publication Year 2014
Sub-type Fully published paper
DOI 10.1109/EMBC.2014.6943582
Open Access Status
ISBN 9781424479290
Start page 274
End page 277
Total pages 4
Collection year 2015
Language eng
Abstract/Summary Actigraphy is effective at monitoring circadian rhythms, but often misidentifies periods of restless sleep (defined here as sleep periods with movement) as wake, and periods of quiet wake as sleep. This limitation restricts the effectiveness of actigraphy for investigating sleep disorders. Our objective in this study was to investigate a time-frequency representation of movement during sleep and wake which could ultimately aid in improving classification performance by reducing false wake detections. As a pilot study, we investigate the characteristics of manually labelled movements from six patients (aged 6–12 years, 3 male) during sleep and wake using the over complete discrete wavelet decomposition. The difference between the median wavelet coefficients were analyzed for 30 movement segments from six movement categories during sleep and wake. We found that, in general, the temporal location of high energy coefficients and the energy of the high frequency bands differed between movements during sleep and wake. This indicates that we are able to differentiate movement during sleep and wake with a time-frequency representation. This representation may improve the sleep and wake classification performance by identifying movements specific to sleep and wake. This will likely improve the poor specificity inherent in conventional actigraphy.
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online 2014.

 
Versions
Version Filter Type
Citation counts: Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Mon, 10 Nov 2014, 10:24:07 EST by Dr Philip Terrill on behalf of School of Information Technol and Elec Engineering