The Actigraphy-Based Identification of Premorbid Latent Liability of Schizophrenia and Bipolar Disorder.

ABSTRACT: (1) Background and Goal: Several studies have investigated the association of sleep, diurnal patterns, and circadian rhythms with the presence and with the risk states of mental illnesses such as schizophrenia and bipolar disorder. The goal of our study was to examine actigraphic measures to identify features that can be extracted from them so that a machine learning model can detect premorbid latent liabilities for schizotypy and bipolarity. (2) Methods: Our team developed a small wrist-worn measurement device that collects and identifies actigraphic data based on an accelerometer. The sensors were used by carefully selected healthy participants who were divided into three groups: Control Group (C), Cyclothymia Factor Group (CFG), and Positive Schizotypy Factor Group (PSF). From the data

SUBMITTER: Nagy A 

PROVIDER: S-EPMC9863012 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature