Abstract
This research is concerned with analyzing a real world problem: the detection of a sleep disorder called Obstructive Apnea Hypopnea Syndrome. The sleep apnea affects a significant number of adults, but children are affected as well. This study is focused on finding the apnea patterns using a well known time series representation method and several distance measures. In this preliminary work, the aim is twofold: on one hand, finding the most relevant features that characterize the apnea episodes; on the other hand, choosing the most promising distance measurements among patterns. The experiments were carried out at the Hospital Universitario de Burgos’s Sleep Laboratory with real subjects and with technicians monitoring the Conventional Polysomnography.
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Álvarez, M.L.A. et al. (2014). Hybrid Systems for Analyzing the Movements during a Temporary Breath Inability Episode. In: Polycarpou, M., de Carvalho, A.C.P.L.F., Pan, JS., Woźniak, M., Quintian, H., Corchado, E. (eds) Hybrid Artificial Intelligence Systems. HAIS 2014. Lecture Notes in Computer Science(), vol 8480. Springer, Cham. https://doi.org/10.1007/978-3-319-07617-1_48
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DOI: https://doi.org/10.1007/978-3-319-07617-1_48
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