With advances in portable and wearable devices, it should be possible to analyze and
interpret the collected biosignals from those devices to tailor a psychological intervention to …

Background and aim Anxiety disorder is common; early diagnosis is crucial for
management. Anxiety can induce physiological changes in the brain and heart. We aimed to …

Remote Photoplethysmography (rPPG) is a fast, effective, inexpensive and convenient
method for collecting biometric data as it enables vital signs estimation using face videos …

In this letter, the Fourier–Bessel domain adaptive wavelet transform (FBDAWT) is proposed
for the automated detection of anxiety stages using the single-channel wearable …

BACKGROUND: Physiological signals, such as skin conductance, heart rate, and
temperature, provide valuable insight into the physiological responses of students to stress …

To comprehend the intricate interplay between the frontal regions of the brain, anxiety, and
their connection with individual personality traits holds promising potential for develo** …

The resilience of machine learning models for anxiety detection through wearable
technology was explored. The effectiveness of feature-based and end-to-end machine …

This study quantitatively evaluated whether and how machine learning (ML) models built by
data from controlled conditions can fit real-world conditions. This study focused on feature …

The increasing occurrence of Hypertension highlights the need for advanced predictive tools
in healthcare. This research proposes a novel approach that combines machine and deep …

Photoplethysmography (PPG)-based foundation models are gaining traction due to the
widespread use of PPG in biosignal monitoring and their potential to generalize across …