Abstract Background and Objective: Researchers use wearable sensing data and machine
learning (ML) models to predict various health and behavioral outcomes. However, sensor …

Emotion research typically searches for consistency and specificity in physiological activity
across instances of an emotion category, such as anger or fear, yet studies to date have …

A firm concept of time is essential for establishing causality in a clinical setting. Review of
critical incidents and generation of study hypotheses require a robust understanding of the …

Cardiac arrhythmia disorder is known as one of the most common diseases in the world.
Today, this disease is considered as the leading cause of death in industrial and semi …

In response to challenging circumstances, the human body can experience marked levels of
anxiety and distress. To prevent stress-related complications, timely identification of stress …

The presence of stimuli and the consequent reactions undoubtedly reflect in experience-
related changes of physiological parameters, which can be monitored by wearable devices …

Recent wearable devices enable continuous and unobtrusive monitoring of human's
physiological parameters, like eg, electrodermal activity and heart rate, over long periods of …

Emotional granularity describes the ability to create emotional experiences that are precise
and context‐specific. Despite growing evidence of a link between emotional granularity and …

Biosignals have quite low signal-to-noise ratio and are often corrupted by different types of
artifacts and noises originated from both external and internal sources. The presence of …

Emotions are inherently complex–situated inside the brain while being influenced by
conditions inside the body and outside in the world–resulting in substantial variation in …