28.10.2020 Discover the Secret of Sleep (Yan)
“Conventional manual sleep analysis is time-consuming, and therefore automatic sleep analysis becomes urgent to address the growing unmet needs for sleep research”, suggests M.Eng. Rui Yan in her dissertation.
Rui Yan’s dissertation presents a systematic exploration of the contribution of sleep signals to sleep analysis. It turns out that the diverse sleep signals complement and reinforce each other, and therefore linked analysis of multiple signals can promote accurate sleep analysis. Based on that, Yan develops an automatic sleep analysis tool that can handle several sleep signals without changing model parameters across tasks.
“The proposed automatic analysis tool facilitates sleep monitoring whether in clinical or in routine care. The strengthening monitoring of sleep health would promote personal wellbeing and even create economic and social benefits”, Yan tells.
Most existing studies are far too optimistic about their practical applications since their models usually require task-specific modifications, which makes them challenging to use for non-experts. Yan’s research presents insights on the construction of versatile models, thereby providing a direction for future research.
M.Eng. Rui Yan defends her doctoral dissertation in Software and Communications Engineering "Automatic Sleep Scoring Based on Multi-Modality Polysomnography Data" at the Ģֱ on Wednesday, October 28th, 2020 starting at 12. The event takes place online. Opponent Professor Li Hu (Chinese Academy of Sciences) and Custos Professor Timo Hämäläinen (Ģֱ). The doctoral dissertation is held in English.
The audience can follow the dissertation online.
Link to the Zoom Webinar (Zoom application or Google Chrome web browser recommended):
Phone number to which the audience can present possible additional questions at the end of the event (to the custos): +358 40 7726470
Further information
Rui Yan
ruiyanmodel@foxmail.com
+358 449536761
The dissertation is published in JYU dissertations, number 298, 60 p., Jyväskylä 2020, ISSN 2489-9003; ISBN 978-951-39-8329-1 (PDF). Link to the publication: .
Rui Yan completed the Bachelor of Engineering in 2013 at Hebei Agricultural University, Baoding, China. She received her M.Eng. in 2016 at Dalian University of Technology, Dalian, China. She has been doing PhD research and studied in the Faculty of Information Technology since 2017.