Using multiple machine learning methods, the group of Kenichi FUKUI extracted sleep-related environmental sounds with high accuracy, mapping them to a two-dimensional plane according to their characteristics. By associating these sounds with individual sleep patterns such as bruxism, body movement or snoring, it is concluded that technologies can be developed which lead to high-quality sleep, using, e. g., a mobile phone to control lighting and air-conditioner appropriately.
JST news release, March 24, 2017
Osaka University team develops personalized sleep control based on AI