2019.11.05

Development of a novel automated sleep stage scoring method ~Learning and Analyzing 4,200 biological signal records of mice~

Scientists including Dr. Hiroyuki Kitagawa, Dr. Kazumasa Horie, and Dr. Hiroaki Shiokawa at Center for Computational Sciences, University of Tsukuba and their collaborators at WPI-IIIS, Dr. Masashi Yanagisawa and Dr. Hiromasa Funato developed a novel automated sleep stage scoring method for mice named “MC-SleepNet”, which combines two types of deep neural networks. It is expected to enhance the efficiency and quality of sleep stage scoring and contribute to sleep research.

The article, “MC-SleepNet: Large-scale Sleep Stage Scoring in Mice by Deep Neural Networks” was published online in Scientific Reports on October 31, 2019.

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  • Development of a novel automated sleep stage scoring method ~Learning and Analyzing 4,200 biological signal records of mice~