Improper sitting positions are known as the primary reason for back pain and the emergence
of musculoskeletal disorders (MSDs) among individuals who spend prolonged time working …

Chronic pain is a prevalent condition where fear of movement and pain interfere with
everyday functioning. Yet, there is no open body movement dataset for people with chronic …

Self-supervised learning has shown value for uncovering informative movement features for
human activity recognition. However, there has been minimal exploration of this approach …

Chronic Low Back Pain (CLBP) afflicts millions globally, significantly impacting individuals'
well-being and imposing economic burdens on healthcare systems. Detecting protective …

Objectives. Research has pointed to two profiles of persons with fibromyalgia according to
differences in functionality, thus distinguishing between functional and dysfunctional …

This research presents a novel multimodal data fusion methodology for pain behavior
recognition, integrating statistical correlation analysis with human-centered insights. Our …

This paper presents the first application of spiking neural networks (SNNs) for the
classification of chronic lower back pain (CLBP) using the EmoPain dataset. Our work has …

The use of multiple raters to label datasets is an established practice in affective computing.
The principal goal is to reduce unwanted subjective bias in the labelling process …

Constrained by the lack of model interpretability and a deep understanding of human
movement in traditional movement recognition machine learning methods, this study …

WiFi sensing has been well explored for recognizing human activity types. However,
research is limited in the possibility of its use in identifying affective expressions such as …