Human activity recognition (HAR) applications have received much attention due to their
necessary implementations in various domains, including Industry 5.0 applications such as …

Deep convolutional neural networks (CNNs) achieve state-of-the-art performance in
wearable human activity recognition (HAR), which has become a new research trend in …

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 …

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 …

Due to the wide application of human activity recognition (HAR) in sports and health, a large
number of HAR models based on deep learning have been proposed. However, many …

Abstract Human Activity Recognition (HAR) is an essential area of pervasive computing
deployed in numerous fields. In order to seamlessly capture human activities, various inertial …

Recent advances in sensor based human activity recognition (HAR) have exploited deep
hybrid networks to improve the performance. These hybrid models combine Convolutional …

Human activity recognition (HAR) can be exploited to great benefits in many applications,
including elder care, health care, rehabilitation, entertainment, and monitoring. Many …

Recently, deep learning, which are able to extract automatically features from data, has
achieved state-of-the-art performance across a variety of sensor based human activity …

Human activity recognition (HAR) is a promising research issue in ubiquitous and wearable
computing. However, there are some problems existing in traditional methods: 1) They treat …