JST Press Release:Classification of 16 Adult Sleep Patterns Based on Large-scale Sleep Analysis

A research group of The University of Tokyo led by Professor Hiroki Ueda (also a Riken team leader) and Machiko Katori, and Assistant Professor Shoi Shi (RIKEN) used ACCEL, an original machine learning algorithm developed by their research laboratory, to determine sleep and waking states based on arm acceleration and converted the acceleration data of approximately 100,000 people in the UK Biobank into sleep data, which was then analyzed in detail. They found that the sleep patterns of these 100,000 people could be classified into 16 different types.

Related Keywords

Japan ,Tokyo ,United Kingdom ,British ,Hiroki Ueda ,Machiko Katori ,University Of Tokyo ,Technology Agency ,Professor Hiroki Ueda ,Assistant Professor Shoi Shi ,Biological Timing Project ,Japan Science ,Uniform Manifold Approximation ,Density Based Spatial Clustering ,