Maximum and minimum activity in inpatient adolescents with Bipolar Disorders: Daily-Variability classification of actigraphy pattern with artificial intelligence.

ABSTRACT: Measures of daily activity may be objective markers to help differentiate adolescent bipolar disorder (BD). We used chart reviewed actigraphy data collected from 2014 to 2023, and AI methods to classify well-characterized inpatient adolescents diagnosed with BD-without-attention deficit/hyperactivity disorder (ADHD), BD-with-ADHD, ADHD-without-BD, and other diagnoses (OD). 389 inpatient adolescents (232 female, mean age 15.07), wore an actigraphy monitor for the duration of their inpatient stay (mean number of unique days = 13.04 days). Activity was characterized into four 60-min maximum and minimum daily activity bins, automatically identified using a novel Python script. Feature engineering further described time-serie

SUBMITTER: Vahedifard F 

PROVIDER: S-EPMC12199408 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature