9 papers
EgoHRV: Continuous Heart Rate Variability Estimation from Egocentric Systems for Autonomic Response and Skill Assessment
Berken Utku Demirel, Christian Holz
Egocentric vision systems capture human behavior from visible cues, but overlook physiological indicators of autonomic states such as stress, engagement, and attention. Heart rate…
FW-NKF: Frequency-Weighted Neural Kalman Filters
Adnan Harun Dogan, Berken Utku Demirel, Christian Holz
Robust state estimation is central to robotic autonomy, yet classical Kalman filters struggle with frequency-dependent disturbances and model mismatch such as sensor vibrations, el…
Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
Berken Utku Demirel, Christian Holz
Self-supervised learning (SSL) has emerged as a powerful paradigm for learning representations without labeled data. Most SSL approaches rely on strong, well-established, handcraft…
Temporal Cardiovascular Dynamics for Improved PPG-Based Heart Rate Estimation
Berken Utku Demirel, Christian Holz
The oscillations of the human heart rate are inherently complex and non-linear -- they are best described by mathematical chaos, and they present a challenge when applied to the pr…
Beyond Subjectivity: Continuous Cybersickness Detection Using EEG-based Multitaper Spectrum Estimation
Berken Utku Demirel, Adnan Harun Dogan, Juliete Rossie +2
Virtual reality (VR) presents immersive opportunities across many applications, yet the inherent risk of developing cybersickness during interaction can severely reduce enjoyment a…
Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning
Berken Utku Demirel, Christian Holz
Deep learning models lack shift invariance, making them sensitive to input shifts that cause changes in output. While recent techniques seek to address this for images, our finding…