Automatic sleep stage mymargin classification is of great importance to measure sleep
quality. In this paper, we propose a novel attention-based deep learning architecture called …

Smart mobile devices are being widely used to identify and track human behaviors in simple
and complex daily activities. The evolution of wearable sensing technologies pertaining to …

Wearable technology has advanced significantly and is now used in various entertainment
and business contexts. Authentication methods could be trustworthy, transparent, and non …

Combining domain knowledge (DK) and machine learning is a recent research stream to
overcome multiple issues like limited explainability, lack of data, and insufficient robustness …

Over the past few decades, researchers have attempted to simplify and accelerate the
process of sleep stage classification through various approaches; however, only a few such …

With a rapidly aging population, the health problems of older individuals have attracted
increasing attention. Elderly people are exposed to more health risks, and their behavior can …

Wearable sensor-based human activity recognition (HAR) is the study that deals with sensor
data to understand human movement and behavior. In a HAR model, feature extraction is …

Although the importance of sleep is increasingly recognized, the lack of general and
transferable algorithms hinders scalable sleep assessment in healthy persons and those …

Smart and connected health (SCH) accelerates the development and integration of
information science and engineering approaches to support the digital transformation of …

The expeditious propagation of Internet of Things (IoT) technologies implanted in different
smart devices, such as smartphones and smartwatches have a ubiquitous consequence on …