This paper surveys the current research directions of activity recognition using inertial
sensors, with potential application in healthcare, wellbeing and sports. The analysis of …

Human Activity Recognition provides valuable contextual information for wellbeing,
healthcare, and sport applications. Over the past decades, many machine learning …

This work introduces an open benchmark dataset to investigate inertial sensor displacement
effects in activity recognition. While sensor position displacements such as rotations and …

The analysis and evaluation of human movement is a growing research area within the field
of sports monitoring. This analysis can help support the enhancement of an athlete's …

Activity/gesture recognition using wearable motion sensors, also known as inertial
measurement units (IMUs), provides an important context for many ubiquitous sensing …

Activity recognition plays an essential role in bridging the gap between the low-level sensor
data and the high-level applications in ambient-assisted living systems. With the aim to …

This paper presents the development of a Human Activity Recognition (HAR) system that
uses a network of nine inertial measurement units situated in different body parts. Every unit …

Activity Recognition has gained a lot of interest in recent years due to its potential and
usefulness for context-aware wearable computing. However, most approaches for activity …

Due to an increased popularity of assistive healthcare technologies activity recognition has
become one of the most widely studied problems in technology-driven assistive healthcare …

Motion analysis technologies have been widely used to monitor the potential for injury and
enhance athlete performance. However, most of these technologies are expensive, can only …