Digital Health – PsychoSense

The Digital Health – PsychoSense research group aims to explore the potential of digital technologies in psychological research to better understand human psychology and behavior. Many psychological research areas still rely on “traditional” methods, such as laboratory protocols or the collection of self-reports or obtrusive, often invasive biomarkers which lack of digital solutions and might limit the advancements of these areas. Thus, our goal is to tackle this issue by working at the intersection of technology, health, and psychology. The research projects of our group include the development of mobile apps, wearable and contactless sensing paradigms, machine learning algorithms, or other digital platforms that can assist in the assessment, induction, or intervention of various psychological states. We also explore the use of virtual reality, biofeedback, and other novel technologies for enhancing emotional regulation, stress management, or cognitive performance.

In addition, we are strong advocates for open science and adopt a range of open science practices in our research. We want our research to be reproduced, built upon, and used in final applications. Thus, we develop and publish open-source software frameworks (for example, have a look here, here, or here) that enable other researchers to actually use our work to facilitate and advance their own research. Additionally, we also make our datasets and corresponding analyses available, aiming to help promote scientific rigor, reduce the risk of bias, and enable others to build on our group’s work. By embracing the principles of open science, our research group is contributing to a broader movement within the scientific community that seeks to promote greater transparency and accountability in research, while also promoting collaboration and innovation in scientific research.

Group Head

Group Members

Students

If you are interested in writing a Bachelor’s or Master’s thesis in our group, please check the lab’s Student Theses and Jobs.

    • Annika Mücke
    • Benjamin Zenke
      stress+ – Development and Evaluation of a Web Application for Remote, Internet-based Induction of Acute Psychosocial Stress
    • Charlotte von Roznowski
      Decoding the Hidden Language of Stress: Analyzing Speech Patterns as a Tool for Stress Detection
    • Clark Bäker
      Improving the robustness of radar-based heart sound detection
    • Daniel Krauß
      Benchmarking of Sleep/Wake Detection Algorithms using Wearable Sensors and Machine Learning
    • Friederike Popp
      Towards frailty assessment in older adults: Investigation of sit-to-stand transfer detection using ear-worn sensors in real-world activities
    • Jana Reinwald
      Triggering an endocrine stress response in the Virtual Reality Stroop Room through social-evaluative stress
    • Leon Schmid
      Analyzing Acute Psychosocial Stress Responses: A Video-Based Motion Analysis Approach
    • Liv Herzer
    • Luca Abel
      Machine Learning-Based Detection of Acute Psychosocial Stress from Dynamic Movements
    • Michaela Hofmann
      Defensive freezing reaction: The effect of acute psychosocial stress on body movement and heart rate
    • Paula Kaiser
      Influence of Social-Evaluative Stress in the Virtual Reality Stroop Room
    • Philipp Dörfler
      Comparison of Algorithms for Respiratory Information Extraction from Wearable Sensors
    • Robert Schröter
      Improving the CARWatch Framework for Objective Cortisol Awakening Response Assessment
    • Sebastian Stühler
      Investigation of the Pre-Ejection Period as a Marker for Sympathetic Activity during Acute Psychosocial Stress
    • Simon Meske
      Improving the Robustness of Heart Rate Estimation from Continuous-Wave Radar Data using a Wavelet-based Approach and Deep Learning
    • Tobias Gessler
      OpenTSST – An Open Web Platform for Large-Scale, Video-Based Motion Analysis During Acute Psychosocial Stress
    • Ulla Sternemann
      Extraction of Pre-Ejection Period as Marker for Acute Psychosocial Stress from Wearable Sensors and Interferometry Radar
    • Veronika Koch
      Influence of Acute Psychosocial Stress on Body Posture and Movement
    • Victoria Müller
      Machine Learning-Based Detection of Acute Psychosocial Stress from Digital Biomarkers
    • Yasaman Moradi Fard

    Projects

    2026

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