Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …

The discovery of several machine learning and deep learning techniques has paved the
way to extend the reach of humans in various real-world applications. Classical machine …

Semisupervised human activity recognition (SemiHAR) has attracted attention in recent
years from various domains, such as digital health and ambient intelligence. Currently, it still …

Machine learning-based wearable human activity recognition (WHAR) models enable the
development of various smart and connected community applications such as sleep pattern …

[] An important task in the field of sensor technology is the efficient implementation of
adaptation procedures of measurements from one sensor to another sensor of identical …

Human-robot teams involve humans and robots collaborating to achieve tasks under various
environmental conditions. Successful teaming will require robots to adapt autonomously to a …

Sleep affects our bodily functions and is critical in promoting every individual's well-being.
To that end, sleep health monitoring research has gained interest recently, including …

An important task in the field of sensor technology is the efficient implementation of
adaptation procedures of measurements from one sensor to another sensor of identical …

Sleep is a critical aspect of an individual's physical and mental well-being. Hence a large
body of sleep monitoring solutions has been gaining popularity, including data-driven AI …

We explore the effect of auxiliary labels in improving the classification accuracy of wearable
sensor-based human activity recognition (HAR) systems, which are primarily trained with the …