An automatic emotion recognition system can serve as a fundamental framework for various
applications in daily life from monitoring emotional well-being to improving the quality of life …

Bioelectric signals are significant indicators of the state of health of the human body,
especially in sports monitoring, where athletes' fatigue state and performance need to be …

In medical simulation training two approaches are currently rather disjunct: realistic manikins
are used to teach physical skills and procedures and VR systems are used to train situation …

Mental illness, whether it is medically diagnosed or undiagnosed, affects a large proportion
of the population. It is one of the causes of extensive disability, and f not properly treated, it …

Background Accurate, objective pain assessment is required in the health care domain and
clinical settings for appropriate pain management. Automated, objective pain detection from …

A photoplethysmography (PPG) is an uncomplicated and inexpensive optical technique
widely used in the healthcare domain to extract valuable health-related information, eg …

Currently, the Internet of Things (IoT) has gained attention for its capability for real-time
monitoring. The advancement in sensor and wireless communication technology has led to …

Respiratory rate (RR) is a clinical sign representing ventilation. An abnormal change in RR
is often the first sign of health deterioration as the body attempts to maintain oxygen delivery …

We propose cross-modal attentive connections, a new dynamic and effective technique for
multimodal representation learning from wearable data. Our solution can be integrated into …

The article deals with the detection of stress using the electrodermal activity (EDA) signal
measured at the wrist. We present an approach for feature extraction from EDA. The …