Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls.

Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls.

Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner physiological state expressed in behavior patterns. Alterations of motor activit...

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Bibliographic Details
Main Authors: Petter Jakobsen, Enrique Garcia-Ceja, Michael Riegler, Lena Antonsen Stabell, Tine Nordgreen, Jim Torresen, Ole Bernt Fasmer, Ketil Joachim Oedegaard
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0231995

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https://doi.org/10.1371/journal.pone.0231995

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