Investigating the Generalizability of Physiological Characteristics of Anxiety

arXiv:2402.15513v1 Announce Type: cross
Abstract: Recent works have demonstrated the effectiveness of machine learning (ML) techniques in detecting anxiety and stress using physiological signals, but it is unclear whether ML models are learning physiological features specific to stress. To address this ambiguity, we evaluated the generalizability of physiological features that have been shown to be correlated with anxiety and stress to high-arousal emotions. Specifically, we examine features extracted from electrocardiogram (ECG) and electrodermal (EDA) signals from the following three datasets: …

abstract anxiety arxiv cs.lg cs.mm eess.sp features machine machine learning ml models physics.med-ph stress type