3 papers
cs.LG2026
Take it Personally: The Limits of General SSL Representations for Real-Life PPG Emotion Detection
Dominika Kunc, Przemysław Kazienko, Stanisław Saganowski
While Self-Supervised Learning (SSL) effectively extracts general representations from noisy, unconstrained physiological signals such as photoplethysmography (PPG), its suitabilit…
eess.SP2026
Does the Heart Show Your Pain? Tackling the X-ITE Pain Challenge with Self-Supervised ECG Representation Learning
Dominika Kunc, Przemysław Kazienko, Stanisław Saganowski
Accurate recognition of pain using physiological signals remains a challenging problem due to pain's subjective nature and high inter-individual variability. In this study, we inve…
cs.LG2023
Scaling Representation Learning from Ubiquitous ECG with State-Space Models
Kleanthis Avramidis, Dominika Kunc, Bartosz Perz +5
Ubiquitous sensing from wearable devices in the wild holds promise for enhancing human well-being, from diagnosing clinical conditions and measuring stress to building adaptive hea…