TY - JOUR A1 - Langendörfer, Peter A1 - Maye, Oliver A1 - Dyka, Zoya A1 - Sorge, R. A1 - Winkler, R. A1 - Kraemer, Rolf T1 - Plasma - A Middleware for Location-Based Services: Design, Implementations and Lessons Learned Y1 - 2004 ER - TY - RPRT A1 - Dyka, Zoya A1 - Vater, Frank A1 - Maye, Oliver A1 - Langendörfer, Peter A1 - Kraemer, Rolf T1 - Efficient Implementations of Cryptographic Routines - A Review and Performance Analysis of Various Approaches Y1 - 2004 ER - TY - JOUR A1 - Piotrowski, Krzysztof A1 - Langendörfer, Peter A1 - Maye, Oliver A1 - Dyka, Zoya T1 - Protecting Privacy in E-Cash Schemes by Securing Hidden Identity Approaches against Stochastic Attacks Y1 - 2006 ER - TY - GEN A1 - Haddadi Esfahani, Ali A1 - Maye, Oliver A1 - Frohberg, Max A1 - Speh, Maria A1 - Jöbges, Michael A1 - Langendörfer, Peter T1 - Machine Learning based Real Time Detection of Freezing of Gait of Parkinson Patients Running on a Body Worn Device T2 - IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2023), 181 (2023) N2 - For those who have Parkinson's disease, one of the most incapacitating symptoms is Freezing of Gait (FOG). Gait impairment and disruptions limit everyday activities and reduce quality of daily life along with the increase in the risk of falling [1]. Thanks to recent advancement in embedded electronics and sensors as well as their adaptation in the wearable device market, low power devices are becoming more and more capable running neural networks. This enables researchers to implement complex models on wearable devices that capture and analyze sensor data to detect FOGin real-time. KW - Parkinson's disease KW - Wearable computers KW - Neural networks KW - Machine learning KW - Real-time systems Y1 - 2023 SN - 979-8-4007-0102-3 U6 - https://doi.org/10.1145/3580252.3589423 SN - 2832-2975 SP - 181 EP - 182 ER - TY - GEN A1 - Haddadi Esfahani, Ali A1 - Maye, Oliver A1 - Frohberg, Max A1 - Langendörfer, Peter T1 - Minimizing the latency of freezing of gait detection on wearable devices T2 - Vorträge : iCCC2024 - iCampµs Cottbus Conference 2024-05-14 - 2024-05-16 Cottbus Y1 - 2024 U6 - https://doi.org/10.5162/iCCC2024/2.2 SP - 49 EP - 52 PB - AMA Service GmbH CY - Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany ER - TY - GEN A1 - Esfahani, Ali Haddadi A1 - Maye, Oliver A1 - Frohberg, Max A1 - Speh, Maria A1 - Jöbges, Micheal A1 - Langendörfer, Peter T1 - Real time detection of Freezing of Gait of Parkinson patients based on machine learning running on a body worn device T2 - Procedia Computer Science Y1 - 2024 U6 - https://doi.org/10.1016/j.procs.2024.06.160 SN - 1877-0509 VL - 239 SP - 177 EP - 184 PB - Elsevier BV ER -