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Differences in sleep patterns among healthy sleepers and patients after stroke


Sleep deprivation, whether from disorder or lifestyle, whether acute or chronic, poses a significant risk in daytime cognitive performance, excessive somnolence, impaired attention or decreased level of motor abilities. Ischemic stroke resulting in cerebral lesions is a well-known acute disorder that leaves affected patients strongly vulnerable to sleep disturbances that often lead to the above-mentioned cognitive and attentional impairments. In this paper, we analyzed and compared sleep patterns of healthy sleepers and patients after stroke. To overcome the well-known limits of the standardized sleep scoring into several discrete sleep stages we employed the recently proposed probabilistic sleep model that represents the sleep process as a continuum in terms of a set of probability curves. The probability curves were considered to represent a form of functional data, and microstructure along with time dynamics of the curves were studied using functional principal components analysis and clustering. Although our study represents a preliminary attempt to separate the two groups of subjects, we were able to identify several physiologically separate sleep patterns and we also identified sleep microstate patterns being a potential source allowing the discrimination of healthy subjects and stroke patients.

Keywords:
sleep patterns, stroke, probabilistic sleep model, functional principal components analysis


Autoři: Bui Thi Mai Phuong;  Roman Rosipal
Působiště autorů: Slovak Academy of Sciences, Bratislava, Slovak Republic ;  Department of Theoretical Methods, Institute of Measurement Science
Vyšlo v časopise: Lékař a technika - Clinician and Technology No. 4, 2014, 44, 15-20
Kategorie: Původní práce

Souhrn

Sleep deprivation, whether from disorder or lifestyle, whether acute or chronic, poses a significant risk in daytime cognitive performance, excessive somnolence, impaired attention or decreased level of motor abilities. Ischemic stroke resulting in cerebral lesions is a well-known acute disorder that leaves affected patients strongly vulnerable to sleep disturbances that often lead to the above-mentioned cognitive and attentional impairments. In this paper, we analyzed and compared sleep patterns of healthy sleepers and patients after stroke. To overcome the well-known limits of the standardized sleep scoring into several discrete sleep stages we employed the recently proposed probabilistic sleep model that represents the sleep process as a continuum in terms of a set of probability curves. The probability curves were considered to represent a form of functional data, and microstructure along with time dynamics of the curves were studied using functional principal components analysis and clustering. Although our study represents a preliminary attempt to separate the two groups of subjects, we were able to identify several physiologically separate sleep patterns and we also identified sleep microstate patterns being a potential source allowing the discrimination of healthy subjects and stroke patients.

Keywords:
sleep patterns, stroke, probabilistic sleep model, functional principal components analysis


Zdroje

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