Speakers
-
Marco Giurgiu (KIT), Irina Timm (KIT), Robin Olfermann (University of Bochum): Towards prompting meaningful movement moments to enhance mood: A personalized AI approach based on wearables data
-
Simon Woll (KIT) & Gergely Biri (FZI, Karlsruhe): Structured Machine Learning Approach for Affective State Prediction using Wearable Technology
-
Andreas Schwerdtfeger (University of Graz, Austria): Detecting real-time reductions (and increases) of heart rate variability independent of bodily movement to trigger just in time adaptive interventions: Promises and pitfalls
-
Eco de Geus (VU Amsterdam): Separating physiology from psychology in ambulatory assessed data from wearables
-
Mathias Mehl (University of Arizona): SocialBit: Towards an automatic, realtime,wearable-based assessment of minute-level social connection
-
Markus Knoch (movisens) & Lisa Hartnagel (KIT): Machine learning-based real-time audioclassification in EMA research: technical developments and insights from a pilot study
-
Jule Pohlhausen (Uni Oldenburg): Towards Privacy-Preserving Conversation Analysis in Everyday Life
-
Michael Beigl (Karlsruhe Institute of Technology): Wearable Computing on the Ears
-
Vera Ludwig (University of Dresden) & Ebner-Priemer (KIT): Towards an automated prediction system in bipolar disorders15.30-16.20: Janik Fechtelpeter (CIMH): Computational Models for EMA forecasting and EMI personalization
-
Josh Smyth (Ohio State): From Smart Digital Phenotyping to Real-TimeIntervention: A Conceptual Framework of Opportunity and Challenge