Differentiating acute from chronic insomnia with machine learning from actigraphy time series data

HIGHLIGHTS

• who: November and collaborators from the United School of Information Technology, Deakin University, Geelong, VIC, Australia, Centro de Ciencias de have published the research: Differentiating acute from chronic insomnia with machine learning from actigraphy time series data, in the Journal: (JOURNAL)
• what: Ultimately, the authors propose a new automatic model to differentiate between AI and CI. The authors demonstrate the observed changes in CI patterns of actigraphy recordings are smaller compared to patterns for individuals with AI and more similar to bed partners and healthy controls. The first data set has 49 adults (age: 18 . . .
  

   

  

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