Human activity recognition has attracted the attention of researchers around the world. This
is an interesting problem that can be addressed in different ways. Many approaches have …

Human activity recognition has gained importance in recent years due to its applications in
various fields such as health, security and surveillance, entertainment, and intelligent …

Decoding human activity accurately from wearable sensors can aid in applications related to
healthcare and context awareness. The present approaches in this domain use recurrent …

Recognizing human physical activities using wireless sensor networks has attracted
significant research interest due to its broad range of applications, such as healthcare …

Sensor-based human activity recognition (S-HAR) has become an important and high-
impact topic of research within human-centered computing. In the last decade, successful …

In this paper, we perform a systematic study about the on-body sensor positioning and data
acquisition details for Human Activity Recognition (HAR) systems. We build a testbed that …

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 (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …

The essential human gait parameters are briefly reviewed, followed by a detailed review of
the state of the art in deep learning for the human gait analysis. The modalities for capturing …

The use of deep learning (DL) for the analysis and diagnosis of biomedical and health care
problems has received unprecedented attention in the last decade. The technique has …