Actigraphy-based sleep/wake detection for insomniacs

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This paper presents an actigraphy-based approach for sleep/wake detection for insomniacs. Due to its relative unobtrusiveness, actigraphy is often used to estimate overnight sleep-wake patterns in clinical practice. However, its performance has been shown to be limited in subjects with sleep complaints such as insomniacs. Quantifying activity counts on 30-s epoch basis, as usually done in regular actigraphy, may lead to an underestimation of wake periods where the subject shows reduced body movements. We therefore propose a new actigraphic feature to characterize the ‘possibility’ of epochs being asleep (or awake) before or after its nearest epoch with a very high activity levels. It is expected to correctly identify some wake epochs when they are very close to the high activity epochs, although they can be motionless. A data set containing 25 insomnia subjects and a linear discriminant classifier were used to test our approach in this study. Leave-one-subject-out cross validation results show that combining the new and the traditional actigraphic features led to a markedly improved performance in sleep/wake detection compared to that using the traditional feature only, with an increase in Cohen’s kappa from 0.49 to 0.55.
Original languageEnglish
Title of host publication14th International Conference on Wearable and Implantable Body Sensor Networks (BSN'17), 9-12 May 2017, Eindhoven, The Netherlands
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)978-1-5090-6244-7
ISBN (Print)978-1-5090-6245-4
Publication statusPublished - 1 Jun 2017


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