Traditional standards employed for pain assessment have many limitations. One such
limitation is reliability linked to inter-observer variability. Therefore, there have been many …

The paper enhances deep-neural-network-based inference in sensing applications by
introducing a lightweight attention mechanism called the global attention module for multi …

We present a new data-driven model and algorithm to identify the perceived emotions of
individuals based on their walking styles. Given an RGB video of an individual walking, we …

Recently, noncontact monitoring of respiratory rate (RR) based on consumer-level cameras
has gained increasing attention. However, motion artifacts with large amplitudes usually …

While occlusal diseases-the main cause of tooth loss--significantly impact patients' teeth and
well-being, they are the most underdiagnosed dental diseases nowadays. Experiencing …

The EmoPain 2020 Challenge is the first international competition aimed at creating a
uniform platform for the comparison of multi-modal machine learning and multimedia …

Reliable data collection, transmission, and delivery on Internet of Things (IoT) systems is
crucial in order to provide high-quality intelligent services. However, sensor data delivery …

Protective behavior exhibited by people with chronic pain (CP) during physical activities is
very informative to understanding their physical and emotional states. Existing automatic …

In the field of body affect recognition, the majority of literature is based on experiments
performed on datasets where trained actors simulate emotional reactions. These acted and …

There is a growing body of studies on applying deep learning to biometrics analysis. Certain
circumstances, however, could impair the objective measures and accuracy of the proposed …