Title Yavuz, S., Grashof, R., Nitsche, T., Breil, B., and Naroska, E. (2025). Development of a pro-adaptive wrist-worn wearable device for Parkinson disease symptoms: Concept and initial approach, Abstracts of the 2025 Joint Annual Conference of the Austrian (ÖGBMT), German (VDE DGBMT) and Swiss (SSBE) Societies for Biomedical Engineering Biomedical Engineering / Biomedizinische Technik, vol. 70, no. s1, 2025, pp. 1-374.
DOI: https://doi.org/10.1515/bmt-2025-1001
Title Grashof, R., Yavuz, S., Gräbel, J. and Breil, B. (2025). Interviews zur nutzerorientierten Entwicklung pro-adaptiver kognitiver Assistenzsysteme: Bedürfnisse von Alzheimer-Patienten. 70. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)
Abstract: grashof2025_gmds_abstract.pdf
Poster: grashof2025_gmds_poster.pdf
Title Grashof R, Lipprandt M, Breil B. Cognitive assistive technologies for degenerative diseases and related evaluation methods: A scoping review. GMS Med Inform Biom Epidemiol. 2025;21:Doc09.
DOI: https://doi.org/10.3205/mibe000281
Abstract Assistive technologies (ATs) are crucial for people with degenerative diseases that affect cognitive functions. To date, no comprehensive review has systematically examined these technologies and their evaluation methods. To outline the current state of research, we conducted a scoping review on cognitive ATs that provide direct assistance.
Title Krause, A. F. *, Kannen, K. *, Büscher, S., Ressel, C. & Wild-Wall, N. (2025). Pro-adaptive Cognitive Assistive Technology: Concept and Application in Reading Support for ADHD. In International Conference on Extended Reality (pp. xx-xx). Springer Lecture Notes in Computer Science. (in press).
(*) These authors contributed equally to this work.
Title Buschmeier, H., Hassan, T., & Kopp, S. (2024, November). Multimodal Co-Construction of Explanations with XAI Workshop. In Proceedings of the 26th International Conference on Multimodal Interaction (pp. 698-699).
Abstract The ICMI 2024 workshop on “Multimodal Co-Construction of Explanations with XAI” bridges the fields of Explainable Artificial Intelligence (XAI) and Multimodal Interaction, focusing on the recent perspective that effective AI explanations should be dynamically co-constructed through interactive, social processes involving both the explainer and the explainee.
Title Yavuz, S. (2024). Development of a 2-4 double arbiter PUF design on FPGA with enhanced performance.
Abstract Implementation of delay-based Physical Unclonable Functions (PUFs) on FPGAs poses significant challenges due to high requirements, such as the generation of unique and reliable keys. These requirements must be fulfilled, especially when using PUFs in security applications, otherwise security cannot be guaranteed. In addition, it must be ensured that physical disturbances such as fluctuations in the ambient temperature do not have a major impact on the performance of the PUF and therefore on security.
Title Yavuz, S., Daniel, K., & Naroska, E. (2024). Vulnerabilities and challenges in the development of PUF-based authentication protocols on FPGAs: A brief review.
Abstract The security of IoT (Internet of Things) devices and the protection of sensitive information processed by these devices such as personal data, sensor values, process-related information is an important and difficult challenge. A major task in IoT communication is secure identification of devices. Unfortunately, traditional cryptographic methods are often not suitable for IoT devices due to their limited hardware resources.
Title Stolarz, M., Romeo, M., Mitrevski, A., & Plöger, P. G. (2024, August). Deep Learning-Based Adaptation of Robot Behaviour for Assistive Robotics. In 2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN) (pp. 110-117). IEEE.
Abstract Robot behaviour models in socially assistive robotics are typically trained using high-level features, such as a user’s engagement, such that inaccuracies in the feature extraction can have a significant effect on a robot’s subsequent performance.
Title Gjoreski, M., Hassan, T., Vered, M., Houben, S., & Kopp, S. (2024, October). XAI for U: Explainable AI for Ubiquitous, Pervasive and Wearable Computing. In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 992-995).
Abstract The workshop XAI for U aims to address the critical need for transparency in Artificial Intelligence (AI) systems that integrate into our daily lives through mobile systems, wearables, and smart environments.
Title Schneider, J., Cheruvalath, S. S., & Hassan, T. (2024, October). Time for an Explanation: A Mini-Review of Explainable Physio-Behavioural Time-Series Classification. In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 885-889).
Abstract Time-series classification is seeing growing importance as device proliferation has lead to the collection of an abundance of sensor data. Although black-box models, whose internal workings are difficult to understand, are a common choice for this task, their use in safety-critical domains has raised calls for greater transparency.
