Bibliography
Conference Paper (international conference)
Dynamic Bayesian Networks for the Classification of Sleep Stages
,
: Proceedings of the 11th Workshop on Uncertainty Processing (WUPES’18), p. 205-215 , Eds: Kratochvíl Václav, Vejnarová Jiřina
: Workshop on Uncertainty Processing (WUPES’18), (Třeboň, CZ, 20180606)
: GA16-12010S, GA ČR, GA17-08182S, GA ČR
: Dynamic Bayesian Network, Sleep Analysis
: http://library.utia.cas.cz/separaty/2018/MTR/vomlel-0490307.pdf
(eng): Human sleep is traditionally classified into five (or six) stages. The manual classification is time consuming since it requires knowledge of an extensive set of rules from manuals and experienced experts. Therefore automatic classification methods appear useful for this task. In this paper we extend the approach based on Hidden Markov Models by relating certain features not only to the current time slice but also to the previous one. Dynamic Bayesian Networks that results from this generalization are thus capable of modeling features related to state transitions. Experiments on real data revealed that in this way we are able to increase the prediction accuracy.
: JD
: 10201