Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …

Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

The vast proliferation of sensor devices and Internet of Things enables the applications of
sensor-based activity recognition. However, there exist substantial challenges that could …

Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …

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 …

Human activity recognition systems are developed as part of a framework to enable
continuous monitoring of human behaviours in the area of ambient assisted living, sports …

As smartphone penetration saturates, we are witnessing a new trend in personal mobile
devices-wearable mobile devices or simply wearables as it is often called. Wearables come …

Human activity recognition (HAR) tasks have traditionally been solved using engineered
features obtained by heuristic processes. Current research suggests that deep convolutional …

Abstract Body Sensor Networks (BSNs) have emerged as a revolutionary technology in
many application domains in health-care, fitness, smart cities, and many other compelling …