There has been an upsurge recently in investigating machine learning techniques for activity
recognition (AR) problems as they have been very effective in extracting and learning …

Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …

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 …

Recognizing human activity plays a significant role in the advancements of human-
interaction applications in healthcare, personal fitness, and smart devices. Many papers …

Traditionally, the sliding window based activity recognition chain (ARC) has been
dominating practical applications, in which features are carefully optimized towards scenario …

Human activity recognition (AR) has begun to mature as a field, but for AR research to thrive,
large, diverse, high quality, AR data sets must be publically available and AR methodology …

Human activity recognition is a core problem in intelligent automation systems due to its far-
reaching applications including ubiquitous computing, health-care services, and smart …

Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …

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 …

This study aims to investigate the performance of Machine Learning (ML) techniques used in
Human Activity Recognition (HAR). Techniques considered are Naïve Bayes, Support …