TY - CHAP A1 - Ortmann, Steffen T1 - Definition and Configuration of Reliable Event Detection for Heterogeneous WSN Y1 - 2010 ER - TY - GEN A1 - Maaser, Michael A1 - Ortmann, Steffen T1 - Remote Medical Treatment at Home Using the Using the Java Mobile Sensor API Y1 - 2010 ER - TY - GEN A1 - Ortmann, Steffen A1 - Maaser, Michael A1 - Langendörfer, Peter T1 - Self-Adapting Event Configuration in Ubiquitous Wireless Sensor Networks Y1 - 2010 ER - TY - GEN A1 - Ortmann, Steffen A1 - Maaser, Michael A1 - Parandian, Baback A1 - Schulz, Martin T1 - Telemedizinisch assistierte ambulante Betreuung von Patienten Y1 - 2011 ER - TY - GEN A1 - Ortmann, Steffen A1 - Maaser, Michael A1 - Langendörfer, Peter T1 - Adaptive Pruning of Event Decision Trees for Energy Efficient Collaboration in Event Driven WSN Y1 - 2009 ER - TY - CHAP A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - Enhancing Reliability of Sensor Networks by Fine Tuning Their Event Observation Behavior Y1 - 2008 ER - TY - CHAP A1 - Maaser, Michael A1 - Ortmann, Steffen T1 - Providing Granted Rights with Anonymous Certificates Y1 - 2008 ER - TY - JOUR A1 - Ortmann, Steffen A1 - Langendörfer, Peter A1 - Maaser, Michael T1 - Adaptive Pervasive Systems to Multiuser Privacy Requirements Y1 - 2008 ER - TY - CHAP A1 - Maaser, Michael A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - The Privacy Advocate: Assertion of Privacy by Personalised Contracts Y1 - 2008 ER - TY - GEN A1 - Maaser, Michael A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - NEPP: Negotiation Enhancements for Privacy Policies Y1 - 2006 ER - TY - GEN A1 - Ortmann, Steffen A1 - Langendörfer, Peter A1 - Maaser, Michael T1 - A Self-Configuring Privacy Management Architecture for Pervasive Systems Y1 - 2007 ER - TY - CHAP A1 - Maaser, Michael A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - The Privacy Advocate (PrivAd): A Framework for Negotiating Individualized Privacy Contracts Y1 - 2007 ER - TY - GEN A1 - Ortmann, Steffen A1 - Langendörfer, Peter A1 - Maaser, Michael T1 - Enhancing Privacy by Applying Information Flow Modelling in Pervasive Systems Y1 - 2007 ER - TY - RPRT A1 - Ortmann, Steffen A1 - Maaser, Michael A1 - Maye, Oliver T1 - Spezifikation der Middleware Architektur Y1 - 2011 ER - TY - RPRT A1 - Wolosz, K. A1 - Ortmann, Steffen T1 - Implementation of an Adapter Board and Hardware Drivers for Connecting a Wireless Sensor Node to a Common Body Scale Y1 - 2011 ER - TY - THES A1 - Ortmann, Steffen T1 - Definition and configuration of reliable event detection for application in wireless sensor networks Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:co1-opus-19602 SN - 978-3-832-29445-8 PB - Shaker CY - Aachen ER - TY - BOOK A1 - Ortmann, Steffen T1 - Entwicklung eines Informationsfluss-Modells für ubiquitäre Systeme Y1 - 2011 SN - 978-3-639-36824-6 PB - Saarbrücken : VDM-Verl. Müller ER - TY - CHAP A1 - Ortmann, Steffen A1 - Maaser, Michael A1 - Langendörfer, Peter T1 - High Level Definition of Event-based Applications for Pervasive Systems Y1 - 2012 ER - TY - CHAP A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - Social Networking and Privacy, a Contradiction? Y1 - 2012 ER - TY - GEN A1 - Ortmann, Steffen A1 - Langendörfer, Peter A1 - Kornemann, Stephan T1 - WiSec 2011 Demo: Demonstrating Self-Contained on-node Counter Measures for Various Jamming Attacks in WSN Y1 - 2011 ER - TY - CHAP A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - A Telemedicine System for Improved Rehabilitation of Stroke Patients Y1 - 2011 ER - TY - GEN A1 - Ortmann, Steffen A1 - Maaser, Michael T1 - Enabling Secure and Privacy-Aware Mobile Sensing and e-Health Applications on Everybodys Smartphone Y1 - 2011 ER - TY - CHAP A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - The Impact of Social Networks on User Privacy - What Social Networks Really Learn about their Users Y1 - 2011 ER - TY - GEN A1 - Haddadi Esfahani, Ali A1 - Dyka, Zoya A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - Impact of Data Preparation in Freezing of Gait Detection using Feature-Less Recurrent Neural Network T2 - IEEE Access Y1 - 2021 U6 - https://doi.org/10.1109/ACCESS.2021.3117543 SN - 2169-3536 IS - 9 SP - 138120 EP - 138131 ER - TY - GEN A1 - Pidvalnyi, Illia A1 - Kostenko, Anna A1 - Sudakov, Oleksandr A1 - Isaev, Dmytro A1 - Maximyuk, Oleksandr A1 - Krishtal, Oleg A1 - Iegorova, Olena A1 - Kabin, Ievgen A1 - Dyka, Zoya A1 - Ortmann, Steffen A1 - Langendörfer, Peter T1 - Classification of epileptic seizures by simple machine learning techniques : application to animals’ electroencephalography signals T2 - IEEE access N2 - Detection and prediction of the onset of seizures are among the most challenging problems in epilepsy diagnostics and treatment. Small electronic devices capable of doing that will improve the quality of life for epilepsy patients while also open new opportunities for pharmacological intervention. This paper presents a novel approach using machine learning techniques to detect seizures onset using intracranial electroencephalography (EEG) signals. The proposed approach was tested on intracranial EEG data recorded in rats with pilocarpine model of temporal lobe epilepsy. A principal component analysis was applied for feature selection before using a support vector machine for the detection of seizures. Hjorth’s parameters and Daubechies discrete wavelet transform coefficients were found to be the most informative features of EEG data. We found that the support vector machine approach had a classification sensitivity of 90% and a specificity of 74% for detecting ictal episodes. Changing the epoch parameter from one to twenty-one seconds results in changing the redistribution of principal components’ values to 10% but does not affect the classification result. Support vector machines are accessible and convenient methods for classification that have achieved promising classification quality, and are rather lightweight compared to other machine learning methods. So we suggest their future use in mobile devices for early epileptic seizure and preictal episode detection. KW - Epilepsy KW - Single-channel intracranial encephalographic data KW - PCA KW - SVM KW - Automated system KW - Rats Y1 - 2025 U6 - https://doi.org/10.1109/ACCESS.2025.3527866 SN - 2169-3536 VL - 13 SP - 8951 EP - 8962 PB - Institute of Electrical and Electronics Engineers (IEEE) CY - Piscataway, NJ ER -