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 …

Sensor-based activity recognition seeks the profound high-level knowledge about human
activities from multitudes of low-level sensor readings. Conventional pattern recognition …

The ubiquity of smartphones and the growth of computing resources, such as connectivity,
processing, portability, and power of sensing, have greatly changed people's lives. Today …

Photoplethysmography (PPG) is a common and practical technique to detect human activity
and other physiological parameters and is commonly implemented in wearable devices …

Abstract Human Activity Recognition (HAR) is a process of recognizing human activities
automatically based on streaming data obtained from various sensors, such as, inertial …

In recent years, there is a growing interest in Human Activity Recognition (HAR) systems
applied in healthcare. A HAR system is essentially made of a wearable device equipped …

Few-shot learning is a technique to learn a model with a very small amount of labeled
training data by transferring knowledge from relevant tasks. In this paper, a few-shot learning …

Deep learning models have recently attracted great interest as an effective solution to the
challenging problem of human activity recognition (HAR) and its widespread applications in …

Abstract Human Activity Recognition (HAR) has become one of the most important research
fields to achieve real-time monitoring of human activities for timely decision making in …

Abstract Human Activity Recognition (HAR) is an essential area of research related to the
ability of smartphones to retrieve information through embedded sensors and recognize the …