Deutsch Intern
Institute for Clinical Epidemiology and Biometry

Dr. Robin Kraft

Dr. Robin Kraft

Am Schwarzenberg 15, Haus A15

Kurzer Lebenslauf

2020-2021 und seit 2024 Wissenschaftlicher Mitarbeiter am Institut für Klinische Epidemiologie und Biometrie, Universität Würzburg
2017-2023 Wissenschaftlicher Mitarbeiter am Institut für Datenbanken und Informationssysteme, Universität Ulm
2015-2017 Studium M.Sc. Medieninformatik, Schwerpunkte Informationssysteme & Mobile Application Engineering, Universität Ulm
2011-2015 Studium B.Sc. Medieninformatik, Universität Ulm

Wissenschaftliche Schwerpunkte

  • Mobile Crowdsensing (MCS)
  • Ecological Momentary Assessment (EMA)
  • eHealth & mHealth
  • Smart Sensing

Ausgewählte Publikationen der letzten Jahre

2024[ to top ]
  • 1.
    Idrees AR, Beierle F, Mutter A, Kraft R, Garatva P, Baumeister H, Reichert M, Pryss R. Engagement analysis of a persuasive-design-optimized eHealth intervention through machine learning. Sci Rep. 2024;14(1):21427.
  • 1.
    Kraft R, Reichert M, Pryss R. Mobile Crowdsensing in Ecological Momentary Assessment mHealth Studies: A Systematic Review and Analysis. Sensors (Basel). 2024;24(2).
  • 1.
    Idrees AR, Kraft R, Mutter A, Baumeister H, Reichert M, Pryss R. Persuasive technologies design for mental and behavioral health platforms: A scoping literature review. PLOS Digit Health. 2024;3(5):e0000498.
2023[ to top ]
  • 1.
    Breitmayer M, Stach M, Kraft R, Allgaier J, Reichert M, Schlee W, Probst T, Langguth B, Pryss R. Predicting the presence of tinnitus using ecological momentary assessments. Scientific Reports [Internet]. 2023;13(1):8989. Available from: https://doi.org/10.1038/s41598-023-36172-7
  • 1.
    Idrees AR, Kraft R, Winter M, Küchler AM, Baumeister H, Reilly R, Reichert M, Pryss R. Exploring the usability of an internet-based intervention and its providing eHealth platform in an eye-tracking study. J Ambient Intell Humaniz Comput. 2023;14(7):9621-36.
2022[ to top ]
  • 1.
    Shahania S, Unnikrishnan V, Pryss R, Kraft R, Schobel J, Hannemann R, Schlee W, Spiliopoulou M. Predicting Ecological Momentary Assessments in an App for Tinnitus by Learning From Each User’s Stream With a Contextual Multi-Armed Bandit. Frontiers in Neuroscience. 2022;16:836834.
  • 1.
    Kraft R, Reichert M, Pryss R. Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices. Sensors [Internet]. 2022;22(1):170. Available from: https://www.mdpi.com/1424-8220/22/1/170
  • 1.
    Idrees AR, Kraft R, Pryss R, Reichert M, Nguyen T, Stenzel L, Baumeister H. Backend Concept of the eSano eHealth Platform for Internet- and Mobile-based Interventions. In: 2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). 2022. pp. 88-93.
  • 1.
    Kraft R, Hofmann F, Reichert M, Pryss R. Dealing With Inaccurate Sensor Data in the Context of Mobile Crowdsensing and mHealth. IEEE J Biomed Health Inform. 2022;26(11):5439-4.
2021[ to top ]
  • 1.
    Shahania S, Unnikrishnan V, Pryss R, Kraft R, Schobel J, Hannemann R, Schlee W, Spiliopoulou M. User-centric vs whole-stream learning for EMA prediction. In: 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS). 2021. pp. 307-12.
  • 1.
    Kraft R, Idrees AR, Stenzel L, Nguyen T, Reichert M, Pryss R, Baumeister H. eSano – An eHealth Platform for Internet- and Mobile-based Interventions. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 2021. pp. 1997-2002.
  • 1.
    Idrees AR, Kraft R, Pryss R, Reichert M, Baumeister H. Literature-based requirements analysis review of persuasive systems design for mental health applications. Procedia Computer Science [Internet]. 2021;191:143-50. Available from: https://www.sciencedirect.com/science/article/pii/S1877050921014137
  • 1.
    Prakash S, Unnikrishnan V, Pryss R, Kraft R, Schobel J, Hannemann R, Langguth B, Schlee W, Spiliopoulou M. Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users. Entropy [Internet]. 2021;23(12):1695. Available from: https://www.mdpi.com/1099-4300/23/12/1695
2020[ to top ]
  • 1.
    Kraft R, Birk F, Reichert M, Deshpande A, Schlee W, Langguth B, Baumeister H, Probst T, Spiliopoulou M, Pryss R. Efficient Processing of Geospatial mHealth Data Using a Scalable Crowdsensing Platform. Sensors [Internet]. 2020;20(12):3456. Available from: https://www.mdpi.com/1424-8220/20/12/3456
  • 1.
    Unnikrishnan V, Schleicher M, Shah Y, Jamaludeen N, Pryss R, Schobel J, Kraft R, Schlee W, Spiliopoulou M. The Effect of Non-Personalised Tips on the Continued Use of Self-Monitoring mHealth Applications. Brain Sciences [Internet]. 2020;10(12):924. Available from: https://www.mdpi.com/2076-3425/10/12/924
  • 1.
    Stach M, Kraft R, Probst T, Messner EM, Terhorst Y, Baumeister H, Schickler M, Reichert M, Sander LB, Pryss R. Mobile Health App Database - A Repository for Quality Ratings of mHealth Apps. In: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). 2020. pp. 427-32.
  • 1.
    Kraft R, Schlee W, Stach M, Reichert M, Langguth B, Baumeister H, Probst T, Hannemann R, Pryss R. Combining Mobile Crowdsensing and Ecological Momentary Assessments in the Healthcare Domain. Frontiers in Neuroscience [Internet]. 2020;14. Available from: https://www.frontiersin.org/articles/10.3389/fnins.2020.00164