Publications at the Chair
Brandebusemeyer, C., Schimmer, T., Arnrich, B. (2025). Wearables to measure developer experience at work. In IEEE/ACM 47th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP), (pp. 23-33).
Brandebusemeyer, C. (2025). Interactions with Generative AI: Wearables to Measure Developer Experience and Productivity Objectively. In IEEE/ACM 47th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), (pp. 148-150).
Stolp, F., Brandebusemeyer, C., Hradilak, F., Kursawe, L., Menger, M., Sauerwald, F., Arnrich, B. (2025). Using CognitIDE to Capture Developers’ Cognitive Load via Physiological Activity During Everyday Software Development Tasks. In 2025 IEEE/ACM Second IDE Workshop (IDE), (pp. 46-51).
Uhlig, A., Brandebusemeyer, C., Stolp, F., Pour, H. H., & Arnrich, B. (2025). Examining Software Developers’ Cognitive Load During Daily Activities with Wearables. In Student Conference Proceedings, 1(1), (pp. 1936-1936).
Anders, C., Moontaha, S., Real, S., Stolp, F., & Arnrich, B. (2025). Multi-Modality Improves Cognitive Load Classification Of Naturalistic Tasks Under Varying Signal Quality. In Proceedings of the 19th EAI International Conference on Pervasive Computing Technologies for Healthcare. (In proceedings)
Anders, C., Moontaha, S., Real, S., & Arnrich, B. (2024). Unobtrusive measurement of cognitive load and physiological signals in uncontrolled environments. Scientific Data, 11(1), 1000. https://doi.org/10.1038/s41597-024-03738-7
Moontaha, S., Arnrich, B., & Galka, A. (2023). State Space Modeling of Event Count Time Series. Entropy, 25(10), 1372. https://doi.org/10.3390/e25101372
Kappattanavar, A. M., Hecker, P., Moontaha, S., Steckhan, N., & Arnrich, B. (2023). Food Choices after Cognitive Load: An Affective Computing Approach. Sensors, 23(14), 6597. https://doi.org/10.3390/s23146597
Moontaha, S., Schumann, F. E. F., & Arnrich, B. (2023). Online learning for wearable eeg-based emotion classification. Sensors, 23(5), 2387. https://doi.org/10.3390/s23052387
Moontaha, S., Kappattanavar, A. M., Hecker, P., & Arnrich, B. (2023). Wearable EEG-Based Cognitive Load Classification by Personalized and Generalized Model Using Brain Asymmetry. In HEALTHINF (pp. 41-51). https://doi.org/10.5220/0011628300003414
Hecker, P., Kappattanavar, A. M., Schmitt, M., Moontaha, S., Wagner, J., Eyben, F., ... & Arnrich, B. (2022, December). Quantifying cognitive load from voice using transformer-based models and a cross-dataset evaluation. In 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA) (pp. 337-344). IEEE. https://doi.org/10.1109/ICMLA55696.2022.00055
Anders, C., Moontaha, S., Arnrich, B.(2022, October). Towards Multi-Modal Recordings in Daily Life: A Baseline Assessment of an Experimental Framework. Pervasive Health and Smart Sensing at the Information Society. http://library.ijs.si/Stacks/Proceedings/InformationSociety/2022/IS2022_Volume-H%20-%20PHSS.pdf
Moontaha, S., Steckhan, N., Kappattanavar, A., Surges, R., & Arnrich, B. (2020, May). Self-prediction of seizures in drug resistance epilepsy using digital phenotyping: a concept study. In Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare (pp. 384-387). https://doi.org/10.1145/3421937.342194