Sebastian Baron

PhD Student

PLUS Faculty of Natural and Life Sciences

Department of Psychology

Background

PhD candidate in Digital and Analytical Sciences with a research focus on machine learning for physiological time-series data, particularly sleep analysis using cardiac signals.

Research Interests

Sleep analysis & digital health
Physiological signal processing (PSG, especially ECG)
Deep learning for time-series data
Wearable sensing & low-cost health monitoring
Explainable AI

Publications

2025

Exploring the bidirectional within-subject relationship between sleep and affective wellbeing: Insights from an intensive longitudinal study: Justin Hachenberger, Maia ten Brink , Denny Kerkhoff, Sebastian Baron, Manuel Schabus, Sakari Lemola; International Journal of Clinical and Health Psychology

The role of objective sleep duration, continuity, and architecture for subjective sleep perception: Findings from an intensive longitudinal study using heart-rate variability to infer objective sleep indicators: Justin Hachenberger, Sebastian Baron, Manuel Schabus, Sakari Lemola; Sleep Medicine

2024

Generalisability of sleep stage classification based on interbeat intervals: validating three machine learning approaches on self-recorded test data: Stefan Kranzinger, Sebastian Baron, Christina Kranzinger, Dominik Heib, Christian Borgelt; Behaviormetrika

2023

From Pulses to Sleep Stages: Towards Optimized Sleep Classification Using Heart-Rate Variability: Pavlos I. Topalidis, Sebastian Baron, Dominik P. J. Heib, Esther-Sevil Eigl, Alexandra Hinterberger, Manuel Schabus; Sensors

The Virtual Sleep Lab—A Novel Method for Accurate Four-Class Sleep Staging Using Heart-Rate Variability from Low-Cost Wearables: Pavlos Topalidis, Dominik Philip Johannes Heib, Sebastian Baron, Esther-Sevil Eigl, Alexandra Hinterberger, Manuel Schabus; Sensors