Clinical Characterization and Prediction of Bipolar Disorder Evolution.

Details

Serval ID
serval:BIB_4B004C84404E
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Clinical Characterization and Prediction of Bipolar Disorder Evolution.
Journal
Journal of clinical medicine
Author(s)
Kloucek P., von Gunten A., Fassassi S.
ISSN
2077-0383 (Print)
ISSN-L
2077-0383
Publication state
Published
Issued date
21/03/2025
Peer-reviewed
Oui
Volume
14
Number
7
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
Background: This paper addresses the possibility of replacing subjective evaluations of mental disorders with analytical tools based on large data provided by wearable sensors in combination with subsequent complexity mesoscale data projection using constitutive mathematical frameworks. Methods: The presented methods are based on the combination of a complexity/fractal approach and stochastic optimization, yielding Digital Mental Biomarkers (DMBs). Results: Analytic indexing can effectively augment the Young Mania Rating Scale, DSM-5 criteria, or structured interview diagnostics. The analytical approach allows us to carry out a prediction of mental disorder evolution as well as a subsequent probability characterization of BD episode progression over time. Conclusions: The presented analytical framework presents a semicontinuous diagnostic tool in the area of mental disorders, specifically applicable to bipolar disorder with corresponding manic episode indexing.
Keywords
Hurst exponent, actigraphy, bipolar disorder, fractal dimension, stochastic optimization
Pubmed
Web of science
Open Access
Yes
Create date
17/04/2025 15:34
Last modification date
17/05/2025 7:09
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