Automatic classification of human sleep recordings combining artifact identification and relevant features selection
Lukáš Zoubek · 2008
tel-00283929, version 1- 1 Jun 2008 Then, I would like to thank to Dr. Sylvie Charbonnier and Dr. Florian Chapotot for proposing such an interesting and challenging research project. I am grateful to them for expert assistance during realization of my thesis as well as for giving me invaluable experience both in personal life and my career. I am grateful to Dr. Sylvie Charbonnier for giving me the chance to make a research in prestigious GIPSA laboratory in Grenoble. Thank a lot for numerous discussions about my research and for guidance during my study. My deep thanks to my dear Lenka for being with me and for motivation and support during my study. Then, I would like to thank to whole my family for the support which gave me during this period of my life. Thanks to my friends and colleagues who were around me. Thank you for spending nice time in the Czech Republic as well as in France. Summary This thesis describes the research focused on development of an automatic system for classification of polysomnographic recordings into different sleep/wake stages.