Dynamic Tracking of State Anxiety via Multi-Modal Data and Machine Learning

Dados Bibliográficos

ID15527319
AutoresYue Ding (0000-0002-4478-1262, Shanghai Mental Health Center), Jingjing Liu (0000-0002-8153-6653, Shanghai Mental Health Center), Xiaochen Zhang (0000-0002-9040-3406, Shanghai Mental Health Center), Zhi Yang (0000-0002-2341-5394, Shanghai Mental Health Center, autor correspondente)
Ano2022
Volume13
Páginas757961-757961
Data de publicação2022-03-02
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoFrontiers in Psychiatry (JOURNAL)
Identificadores do periódicoISSN: 1664-0640 • E-ISSN: 1664-0640
EditoraFrontiers Media (PUBLISHER • CH)
DOI10.3389/fpsyt.2022.757961
PMID35308879
OpenAlexW4214812082
IdiomaEN
Citações recebidas3
Referências citadas46

Anxiety induction is widely used in the investigations of the mechanism and treatment of state anxiety. State anxiety is accompanied by immediate psychological and physiological responses. However, the existing state anxiety measurement, such as the commonly used state anxiety subscale of the State-Trait Anxiety Inventory, mainly relies on questionnaires with low temporal resolution. This study aims to develop a tracking model of state anxiety with high temporal resolution. To capture the dynamic changes of state anxiety levels, we induced the participants' state anxiety through exposure to aversive pictures or the risk of electric shocks and simultaneously recorded multi-modal data, including dimensional emotion ratings, electrocardiogram, and galvanic skin response. Using the paired self-reported state anxiety levels and multi-modal measures, we trained and validated machine learning models to predict state anxiety based on psychological and physiological features extracted from the multi-modal data. The prediction model achieved a high correlation between the predicted and self-reported state anxiety levels. This quantitative model provides fine-grained and sensitive measures of state anxiety levels for future affective brain-computer interaction and anxiety modulation studies

Anxiety · Psychiatry · Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes · Clinical Psychology · Computer Science · EEG and Brain-Computer Interfaces · Mental Health Research Topics · Psychology