The self-regulated recognition of human activities from time-series smartphone sensor data
is a growing research area in smart and intelligent health care. Deep learning (DL) …

Abstract Human Activity Recognition (HAR) is an eminent area of research due to its
extensive scope of applications in remote health monitoring, sports, smart home, and many …

In recent years, research investigations on recognizing human activities to assess the
physical and cognitive capability of humans have gained importance. This paper presents …

The aim of this study is to develop a human activity classification system based on a
wearable intelligent textile and machine learning techniques. Using the Relief-F feature …

In this paper, we present an approach for regression-based feature selection in human
activity recognition. Due to high dimensional features in human activity recognition, the …

A within-class subspace regularisation approach is proposed for eigenfeatures extraction
and regularisation in human activity recognition. In this approach, the within-class subspace …

Although biologically meaningful modules can often be detected by many existing
informatics tools, it is still hard to interpret or make use of the results towards in silico …

Context-aware framework is basic context-aware that utilizes contexts such as user with their
individual activities, location and time, which are hidden information derived from …

Feature extraction is an essential component in the design of human activity recognition
model. However, relying on extracted features alone for learning often makes the model a …