Human Activity Recognition (HAR) has become one of the leading research topics of the last
decade. As sensing technologies have matured and their economic costs have declined, a …

The automatic, sensor-based assessment of human activities is highly relevant for
production and logistics, to optimise the economics and ergonomics of these processes …

Researchers face the challenge of defining subject selection criteria when training
algorithms for human activity recognition tasks. The ongoing uncertainty revolves around …

When creating multi-channel time-series datasets for Human Activity Recognition (HAR),
researchers are faced with the issue of subject selection criteria. It is unknown what physical …

Human activity recognition evolves around classifying and analyzing workers' actions
quantitatively using convolutional neural networks on the time-series data provided by …

Zusammenfassung Mit Silicon Economy wird das kommende föderale Plattformen-
Ökosystem einer durchgängig digitalisierten und datengetriebenen Logistik beschrieben …

Neural networks trained on human motion data have various industrial and daily living
applications, such as activity recognition, gesture recognition, and gait-based biometrics …

Human-technology collaboration relies on verbal and non-verbal communication. Machines
must be able to detect and understand the movements of humans to facilitate non-verbal …

In a social networked industry, the focus is on collaboration between humans and
technology. Communication is the basic prerequisite for synergetic collaboration between all …

Heart Rate (HR) measurement is one of the most effective ways to determine whether a
person is stressed or not. The analysis of a series of HR measurements can help determine …