T-Pattern detection in physiological signals during sleep
H.G. Helgason2, I. Hjálmarsson2, G.K. Jonsson1, M.S. Magnusson3,
S. Kristjánsson2
1Human Behavior
Laboratory, University of Iceland, Univerisy of Aberdeen & PatternVision,
Reykjavik, Iceland
2MedCare, Reykjavik, Iceland
3Human Behavior Laboratory, University of Iceland & PatternVision,
Reykjavik, Iceland
Sleep recordings consist of various physiological signals, such as EEG,
EMG, EKG, EOG, airflow, effort, and SpO2. Current analytical methods in
sleep focus on counting specific events that are determined by predefined
criteria and scoring rules. In addition, specific parasomnias are counted,
such as apneas, hypopneas, desaturations and snoring periods, as well
as periodic limb movement events to summarize the causes of sleep related
problems. Indices are calculated from these events, diagnosis and treatment
recommendations are given.
The main focus of our research is to search for physiologically based
sleep patterns that have not been de.ned in advance and to explore the
clinical application of the findings. We introduce a new approach, known
as T-pattern detection, to the analysis of polysomnography data. Sleep
research data was collected with Medcare Embla - Somnologica sleep diagnostic
system and analyzed with Theme
(PatternVision Ltd., Iceland).
The investigation highlights the potential for T-pattern analysis to
make a significant contribution to sleep research analysis. The data show
that specific temporal patterns can be identified within scored sleep
events. A high number of temporal patterns were detected in data from
patient and healthy subjects polysomnography reports. Results indicate
that the T-pattern detection algorithm discovered known sleep-patterns
in manually scored apnea-patient records, sleep patterns that indicate
some sort of sleep disorder. It also discovered unknown patterns that
occurred exclusively in certain patient groups. Highly significant patterns
were discovered in automatically scored data, based on new definitions,
where certain pattern types also occurred exclusively in certain patient
groups.
Paper presented
at Measuring Behavior 2005
, 5th International Conference on Methods and Techniques
in Behavioral Research, 30 August - 2 September 2005, Wageningen, The
Netherlands.
© 2005 Noldus
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