A. Kramlich, J. Bohnert, and O. Dössel. Transmembrane voltages caused by magnetic fields - numerical study of schematic cell models. In Magnetic Particle Imaging: A Novel Spio Nanoparticle Imaging Technique, Springer-Verlag Berlin Heidelberg, pp. 337-342, 2012
Abstract:
Due to forthcoming use of MPI on humans there is an urgent need for a thorough research on possible adverse effects of this technique on patients health. However, the health impact of exposure to time-varying magnetic fields in a frequency range between 10 kHz and 100 MHz, such as the MPI drive field, are still poorly investigated.The current paper intends to give an overview on an in-silico approach to investigation of stimulating effects that could be caused by the MPI drive field. For this purpose, cell models of myocardiocyte, myocyte and neurocyte, as well as a suitable setup for the simulation of the exposure to time-varying magnetic fields have been developed. The evaluation of performed simulations was carried out on the basis of transmembrane voltage elevation and induced current densities.
Conference Contributions (2)
G. Lenis, A. Kramlich, T. Oesterlein, A. Luik, C. Schmitt, and O. Dössel. Development and Benchmarking of Activity Detection Algorithms for Intracardiac Electrograms Measured During Atrial Flutter. In Workshop Biosignal 2016. Innovation bei der Erfassung und Analyse bioelektrischer und bimagnetischer Signale, pp. 5-8, 2016
Catheter ablation has become a very efficient strategy to terminate sustained cardiac arrhythmias like atrial flutter (AFlut). Identification of the optimal ablation spot, however, often proves difficult when scar from previous ablations is present. Although the application of electro-anatomical mapping systems allows to record thousands of intracardiac electrograms (EGMs) from each atrium, state-of-the-art techniques provide limited options for automatic signal processing. Goal of the presented research was the development of an algorithm to detect EGMs that present double potentials (DPs), as these often indicate functional or anatomical lines of block for cardiac excitation. Using an annotated database, we developed several features based on the morphological descriptors of DPs. These were used to train a binary decision tree which was able to detect DPs with a correct rate of over 90%.
Student Theses (2)
A. Kramlich. Development and Benchmarking of Algorithms for the Characterization of Intracardiac Electrograms Measured during Atrial Flutter. Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT). Masterarbeit. 2016
Abstract:
Automatic signal processing of intracardiac electrograms (EGM) is an important step towards improvement of the diagnostic process and the treatment of atrial flutter. This thesis is concerned with two parts of the signal processing workflow: detection of activity within the recorded EGMs and classification of the EGMs (detection of EGMs with double potentials).For the purposes of the first objective a series of well-established activity detection algorithms as well as new algorithms developed as part of this work were implemented and tested. The five chosen algorithms were based on the NLEO, Hilbert transform, wavelet transform, matched filter and the so called voltage-based approach. The performance of each algorithm was evaluated using a database consisting of approximately 3,000 manually annotated EGMs. Some of the parameters of each algorithm with the strongest influence on the outcome were optimized with regard to the performance of the algorithm on the database. Finally, a comprehensive comparison of the performance results of the algorithms was conducted. With appropriate optimization of the parameters all of the five algorithms evaluated in this thesis performed with correct rates in the range of 91.093.3 %. Further improvements leading to correct rates up to 9495 % were discussed. For the accomplishment of the second objective a classifier for distinguishing between regular EGMs and EGMs with double potentials was developed. For this purpose a set of descriptors was introduced. As before the EGM database was used for the training and the cross-validation of the classifier. The descriptors proposed for the classification showed to be sufficient for an accurate detection of double potentials. The classifiers itself, however, relied on the results of activity detection, which is why the performance of the classifier depended on the accuracy of the underlying activity detection algorithm. The highest obtained correct rate for the classification was 90.9 %.
A. Kramlich. Simulation induzierter Wechselfelder am schematischen Zellmodell. Institut für Biomedizinische Technik, Karlsruher Institut für Technologie (KIT). Bachelorarbeit. 2011