DocumentCode :
139837
Title :
Ambulatory estimation of human circadian phase using models of varying complexity based on non-invasive signal modalities
Author :
Gil, Enrique A. ; Aubert, Xavier L. ; Beersma, Domien G. M.
Author_Institution :
Philips Res., Eindhoven, Netherlands
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
2278
Lastpage :
2281
Abstract :
In this work, we introduce a number of models for human circadian phase estimation in ambulatory conditions using various sensor modalities. Machine learning techniques have been applied to ambulatory recordings of wrist actigraphy, light exposure, electrocardiograms (ECG), and distal and proximal skin temperature to develop ARMAX models capturing the main signal dependencies on circadian phase and evaluating them versus melatonin onset times. The most accurate models extracted heart rate variability features from an ECG coupled with wrist activity information to produce phase estimations with prediction errors of ~30 minutes. Replacing the ECG features with skin temperature from the upper leg led to a slight degradation, while less accurate results, in the order of 1 hour, were obtained from wrist activity and light measurements. The trade-off between highest precision and least obtrusive configuration is discussed for applications to sleep and mood disorders caused by a misalignment of the internal phase with the external solar and social times.
Keywords :
biomedical measurement; circadian rhythms; electrocardiography; learning (artificial intelligence); medical disorders; medical signal processing; phase estimation; sleep; ARMAX models; ECG; ambulatory condition; ambulatory estimation; ambulatory recordings; distal skin temperature; electrocardiograms; heart rate variability; human circadian phase estimation; least obtrusive configuration; light exposure; light measurements; machine learning techniques; melatonin onset times; mood disorders; noninvasive signal modalities; proximal skin temperature; sleep disorders; wrist actigraphy; wrist activity information; Accuracy; Autoregressive processes; Electrocardiography; Heart rate variability; Mathematical model; Skin; Temperature measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6944074
Filename :
6944074
Link To Document :
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