Background Mental stress and its consequent mental health disorders (MDs) constitute a
significant public health issue. With the advent of machine learning (ML), there is potential to …

This work introduces the design, architecture, implementation, and testing of a low-cost and
machine-learning-enabled device to be worn on the wrist. The suggested wearable device …

Stress is an increasingly prevalent mental health condition across the world. In Europe, for
example, stress is considered one of the most common health problems, and over USD 300 …

Brain stress monitoring has emerged as a critical research area for understanding and
managing stress and neurological health issues. This burgeoning field aims to provide …

Background: There are a wide range of potential adverse health effects, ranging from
headaches to cardiovascular disease, associated with long-term negative emotions and …

One of the many areas in which artificial intelligence (AI) techniques are used is the
development of systems for the recognition of vital emotions to control human health and …

Stress is subjective and is manifested differently from one person to another. Thus, the
performance of generic classification models that classify stress status is crude. Building a …

Support vector machines (SVMs) utilize hyper-parameters for classification. Model selection
(MS) is an essential step in the construction of the SVM classifier as it involves the …

We propose and study a data-driven method that can interpolate between a classical and a
modern approach to classification for a class of linear models. The class is the convex …