In this article, we introduce explainable methods to understand how Human Activity
Recognition (HAR) mobile systems perform based on the chosen validation strategies. Our …

Human activity recognition (HAR) is a line of research whose goal is to design and develop
automatic techniques for recognizing activities of daily living (ADLs) using signals from …

Abstract Human Activity Recognition (HAR) is typically modelled as a classification task
where sensor data associated with activity labels are used to train a classifier to recognise …

In this article, we study activity recognition in the context of sensor-rich environments. In
these environments, many different constraints arise at various levels during the data …

Due to wearables' popularity, human activity recognition (HAR) plays a significant role in
people's routines. Many deep learning (DL) approaches have studied HAR to classify …

Recognizing human activities and monitoring population behavior are fundamental needs of
our society. Population security, crowd surveillance, healthcare support and living …

Many researchers devote themselves to studying various aspects of Human Activity
Recognition (HAR), such as data analysis, signal processing, feature extraction, and …

Human Activity Recognition (HAR) using mobile sensor data has gained increasing
attention over the last few years, with a fast-growing number of reported applications. The …

In recent years, mainly due to the application of smartphones in this area, research in human
activity recognition (HAR) has shown a continuous and steady growth. Thanks to its wide …

Human activity recognition (HAR) algorithms today are designed and evaluated on data
collected in controlled settings, providing limited insights into their performance in real-world …