Validating the Comparison Framework for the Finite Dimensions Model of Concentric Ring Electrodes Using Human Electrocardiogram Data

[EN] While progress has been made in design optimization of concentric ring electrodes maximizing the accuracy of the surface Laplacian estimation, it was based exclusively on the negligible dimensions model of the electrode. Recent proof of concept of the new finite dimensions model that adds the radius of the central disc and the widths of concentric rings to the previously included number of rings and inter-ring distances provides an opportunity for more comprehensive design optimization. In this study, the aforementioned proof of concept was developed into a framework allowing direct comparison of any two concentric ring electrodes of the same size and with the same number of rings. The proposed framework is illustrated on constant and linearly increasing inter-ring distances tripolar concentric ring electrode configurations and validated on electrocardiograms from 20 human volunteers. In particular, ratios of truncation term coefficients between the two electrode configurations were used to demonstrate the similarity between the negligible and the finite dimension models analytically (p = 0.077). Laplacian estimates based on the two models were calculated on electrocardiogram data for emulation of linearly increasing inter-ring distances tripolar concentric ring electrode. The difference between the estimates was not statistically significant (p >> 0.05) which is consistent with the analytic result.This research was funded by the National Science Foundation (NSF) Division of Human Resource Development (HRD) Tribal Colleges and Universities Program (TCUP), grants number 1622481 and 1914787 to Oleksandr Makeyev. The authors would like to thank Rafael Rodriguez de Sanabria for his help with the human ECG data collection and Eduardo Garcia-Breijo for his help with the CRE implementation.Makeyev, O.; Musngi, M.; Moore, L.; Ye Lin, Y.; Prats-Boluda, G.; Garcia-Casado, J. (2019). Validating the Comparison Framework for the Finite Dimensions Model of Concentric Ring Electrodes Using Human Electrocardiogram Data. Applied Sciences. 9(20):1-14. https://doi.org/10.3390/app9204279S114920Bradshaw, L. A., Richards, W. O., & Wikswo, J. P. (2001). Volume conductor effects on the spatial resolution of magnetic fields and electric potentials from gastrointestinal electrical activity. Medical and Biological Engineering and Computing, 39(1), 35-43. doi:10.1007/bf02345264Besio, W. G., Hongbao Cao, & Peng Zhou. (2008). Application of Tripolar Concentric Electrodes and Prefeature Selection Algorithm for Brain–Computer Interface. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 16(2), 191-194. doi:10.1109/tnsre.2007.916303Farina, D., & Cescon, C. (2001). Concentric-ring electrode systems for noninvasive detection of single motor unit activity. IEEE Transactions on Biomedical Engineering, 48(11), 1326-1334. doi:10.1109/10.959328McFarland, D. 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Journal of Computational Physics, 95(2), 477-496. doi:10.1016/0021-9991(91)90286-tBesio, G., Koka, K., Aakula, R., & Weizhong Dai. (2006). Tri-polar concentric ring electrode development for Laplacian electroencephalography. IEEE Transactions on Biomedical Engineering, 53(5), 926-933. doi:10.1109/tbme.2005.863887Besio, W., Aakula, R., Koka, K., & Dai, W. (2006). Development of a Tri-polar Concentric Ring Electrode for Acquiring Accurate Laplacian Body Surface Potentials. Annals of Biomedical Engineering, 34(3), 426-435. doi:10.1007/s10439-005-9054-8Wang, K., Parekh, U., Pailla, T., Garudadri, H., Gilja, V., & Ng, T. N. (2017). Stretchable Dry Electrodes with Concentric Ring Geometry for Enhancing Spatial Resolution in Electrophysiology. Advanced Healthcare Materials, 6(19), 1700552. doi:10.1002/adhm.201700552Lidón-Roger, J., Prats-Boluda, G., Ye-Lin, Y., Garcia-Casado, J., & Garcia-Breijo, E. (2018). Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology. Sensors, 18(1), 300. doi:10.3390/s18010300Besio, W. G., Martinez-Juarez, I. E., Makeyev, O., Gaitanis, J. N., Blum, A. S., Fisher, R. S., & Medvedev, A. V. (2014). High-Frequency Oscillations Recorded on the Scalp of Patients With Epilepsy Using Tripolar Concentric Ring Electrodes. IEEE Journal of Translational Engineering in Health and Medicine, 2, 1-11. doi:10.1109/jtehm.2014.2332994Boudria, Y., Feltane, A., & Besio, W. (2014). Significant improvement in one-dimensional cursor control using Laplacian electroencephalography over electroencephalography. Journal of Neural Engineering, 11(3), 035014. doi:10.1088/1741-2560/11/3/035014Garcia-Casado, J., Zena-Gimenez, V., Prats-Boluda, G., & Ye-Lin, Y. (2013). Enhancement of Non-Invasive Recording of Electroenterogram by Means of a Flexible Array of Concentric Ring Electrodes. Annals of Biomedical Engineering, 42(3), 651-660. doi:10.1007/s10439-013-0935-yZena-Giménez, V., Garcia-Casado, J., Ye-Lin, Y., Garcia-Breijo, E., & Prats-Boluda, G. (2018). A Flexible Multiring Concentric Electrode for Non-Invasive Identification of Intestinal Slow Waves. Sensors, 18(2), 396. doi:10.3390/s18020396Ye-Lin, Y., Alberola-Rubio, J., Prats-boluda, G., Perales, A., Desantes, D., & Garcia-Casado, J. (2014). Feasibility and Analysis of Bipolar Concentric Recording of Electrohysterogram with Flexible Active Electrode. Annals of Biomedical Engineering, 43(4), 968-976. doi:10.1007/s10439-014-1130-5Prats-Boluda, G., Ye-Lin, Y., Pradas-Novella, F., Garcia-Breijo, E., & Garcia-Casado, J. (2018). Textile Concentric Ring Electrodes: Influence of Position and Electrode Size on Cardiac Activity Monitoring. Journal of Sensors, 2018, 1-9. doi:10.1155/2018/7290867Wang, Y.-C., Chang, C.-F., Lin, H.-C., Lin, K.-S., Lin, K.-T., Hung, C.-M., & Lin, T.-M. (2010). Functional characterisation of a complex mutation in the α(1,4)galactosyltransferase gene in Taiwanese individuals with p phenotype. Transfusion Medicine, 21(2), 84-89. doi:10.1111/j.1365-3148.2010.01055.xMakeyev, O., Ding, Q., & Besio, W. G. (2016). Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes. Measurement, 80, 44-52. doi:10.1016/j.measurement.2015.11.017Makeyev, O., & Besio, W. (2016). Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes. Sensors, 16(6), 858. doi:10.3390/s16060858Makeyev, O. (2018). Solving the general inter-ring distances optimization problem for concentric ring electrodes to improve Laplacian estimation. BioMedical Engineering OnLine, 17(1). doi:10.1186/s12938-018-0549-6Ye-Lin, Y., Bueno-Barrachina, J. M., Prats-boluda, G., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2017). Wireless sensor node for non-invasive high precision electrocardiographic signal acquisition based on a multi-ring electrode. Measurement, 97, 195-202. doi:10.1016/j.measurement.2016.11.009Besio, W., & Chen, T. (2007). Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping. Physiological Measurement, 28(5), 515-529. doi:10.1088/0967-3334/28/5/006Hamilton, P. S., & Tompkins, W. J. (1986). Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database. IEEE Transactions on Biomedical Engineering, BME-33(12), 1157-1165. doi:10.1109/tbme.1986.325695Prats-Boluda, G., Ye-Lin, Y., Bueno-Barrachina, J., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2016). Towards the clinical use of concentric electrodes in ECG recordings: influence of ring dimensions and electrode position. Measurement Science and Technology, 27(2), 025705. doi:10.1088/0957-0233/27/2/025705Mittal, S., Movsowitz, C., & Steinberg, J. S. (2011). Ambulatory External Electrocardiographic Monitoring. Journal of the American College of Cardiology, 58(17), 1741-1749. doi:10.1016/j.jacc.2011.07.026Garcia-Casado, J., Ye-Lin, Y., Prats-Boluda, G., & Makeyev, O. (2019). Evaluation of Bipolar, Tripolar, and Quadripolar Laplacian Estimates of Electrocardiogram via Concentric Ring Electrodes. Sensors, 19(17), 3780. doi:10.3390/s19173780Xu, Y., Luo, M., Li, T., & Song, G. (2017). ECG Signal De-noising and Baseline Wander Correction Based on CEEMDAN and Wavelet Threshold. Sensors, 17(12), 2754. doi:10.3390/s17122754Ortigueira, M. D., Laleg-Kirati, T.-M., & Machado, J. A. T. (2014). Riesz potential versus fractional Laplacian. Journal of Statistical Mechanics: Theory and Experiment, 2014(9), P09032. doi:10.1088/1742-5468/2014/09/p0903

Evaluation of Bipolar, Tripolar, and Quadripolar Laplacian Estimates of Electrocardiogram via Concentric Ring Electrodes

[EN] Surface Laplacian estimates via concentric ring electrodes (CREs) have proven to enhance spatial resolution compared to conventional disc electrodes, which is of great importance for P-wave analysis. In this study, Laplacian estimates for traditional bipolar configuration (BC), two tripolar configurations with linearly decreasing and increasing inter-ring distances (TCLDIRD and TCLIIRD, respectively), and quadripolar configuration (QC) were obtained from cardiac recordings with pentapolar CREs placed at CMV1 and CMV2 positions. Normalized P-wave amplitude (NAP) was computed to assess the contrast to study atrial activity. Signals were of good quality (20-30 dB). Atrial activity was more emphasized at CMV1 (NAP similar or equal to 0.19-0.24) compared to CMV2 (NAP similar or equal to 0.08-0.10). Enhanced spatial resolution of TCLIIRD and QC resulted in higher NAP values than BC and TCLDIRD. Comparison with simultaneous standard 12-lead ECG proved that Laplacian estimates at CMV1 outperformed all the limb and chest standard leads in the contrast to study P-waves. Clinical recordings with CRE at this position could allow more detailed observation of atrial activity and facilitate the diagnosis of associated pathologies. Furthermore, such recordings would not require additional electrodes on limbs and could be performed wirelessly, so it should also be suitable for ambulatory monitoring, for example, using cardiac Holter monitors.This research was funded by the National Science Foundation (NSF) Division of Human Resource Development (HRD) Tribal Colleges and Universities Program (TCUP), grants number 1622481 and 1914787 to O.M.Garcia-Casado, J.; Ye Lin, Y.; Prats-Boluda, G.; Makeyev, O. (2019). Evaluation of Bipolar, Tripolar, and Quadripolar Laplacian Estimates of Electrocardiogram via Concentric Ring Electrodes. Sensors. 19(17):1-11. https://doi.org/10.3390/s19173780S1111917Roth, G. A., Johnson, C., Abajobir, A., Abd-Allah, F., Abera, S. F., Abyu, G., … Alam, K. (2017). Global, Regional, and National Burden of Cardiovascular Diseases for 10 Causes, 1990 to 2015. Journal of the American College of Cardiology, 70(1), 1-25. doi:10.1016/j.jacc.2017.04.052Lopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T., & Murray, C. J. (2006). Global and regional burden of disease and risk factors, 2001: systematic analysis of population health data. The Lancet, 367(9524), 1747-1757. doi:10.1016/s0140-6736(06)68770-9Bhatnagar, P., Wickramasinghe, K., Wilkins, E., & Townsend, N. (2016). Trends in the epidemiology of cardiovascular disease in the UK. Heart, 102(24), 1945-1952. doi:10.1136/heartjnl-2016-309573https://healthmetrics.heart.org/cardiovascular-disease-a-costly-burden/Leal, J., Luengo-Fernández, R., Gray, A., Petersen, S., & Rayner, M. (2006). Economic burden of cardiovascular diseases in the enlarged European Union. European Heart Journal, 27(13), 1610-1619. doi:10.1093/eurheartj/ehi733Wang, Y., Cuculich, P. S., Zhang, J., Desouza, K. A., Vijayakumar, R., Chen, J., … Rudy, Y. (2011). Noninvasive Electroanatomic Mapping of Human Ventricular Arrhythmias with Electrocardiographic Imaging. Science Translational Medicine, 3(98), 98ra84-98ra84. doi:10.1126/scitranslmed.3002152SippensGroenewegen, A., Peeters, H. A. P., Jessurun, E. R., Linnenbank, A. C., Robles de Medina, E. O., Lesh, M. D., & van Hemel, N. M. (1998). Body Surface Mapping During Pacing at Multiple Sites in the Human Atrium. Circulation, 97(4), 369-380. doi:10.1161/01.cir.97.4.369Kornreich, F., MacLeod, R. S., & Lux, R. L. (2008). Supplemented standard 12-lead electrocardiogram for optimal diagnosis and reconstruction of significant body surface map patterns. Journal of Electrocardiology, 41(3), 251-256. doi:10.1016/j.jelectrocard.2008.02.011Fereniec, M., Stix, G., Kania, M., Mroczka, T., & Maniewski, R. (2013). An Analysis of the U-Wave and Its Relation to the T-Wave in Body Surface Potential Maps for Healthy Subjects and MI Patients. Annals of Noninvasive Electrocardiology, 19(2), 145-156. doi:10.1111/anec.12110Lian, J., Li, G., Cheng, J., Avitall, B., & He, B. (2002). Body surface Laplacian mapping of atrial depolarization in healthy human subjects. Medical & Biological Engineering & Computing, 40(6), 650-659. doi:10.1007/bf02345304Wu, D., Tsai, H. C., & He, B. (1999). On the Estimation of the Laplacian Electrocardiogram during Ventricular Activation. Annals of Biomedical Engineering, 27(6), 731-745. doi:10.1114/1.224He, B., & Cohen, R. J. (1992). Body surface Laplacian mapping of cardiac electrical activity. The American Journal of Cardiology, 70(20), 1617-1620. doi:10.1016/0002-9149(92)90471-aHe, B., & Cohen, R. J. (1992). Body surface Laplacian ECG mapping. IEEE Transactions on Biomedical Engineering, 39(11), 1179-1191. doi:10.1109/10.168684He, B., & Cohen, R. J. (1995). Body Surface Laplacian Electrocardiographic Mapping−A Review. Critical Reviews in Biomedical Engineering, 23(5-6), 475-510. doi:10.1615/critrevbiomedeng.v23.i5-6.30UMETANI, K., OKAMOTO, Y., MASHIMA, S., ONO, K., HOSAKA, H., & HE, B. (1998). Body Surface Laplacian Mapping in Patients with Left or Right Ventricular Bundle Branch Block. Pacing and Clinical Electrophysiology, 21(11), 2043-2054. doi:10.1111/j.1540-8159.1998.tb01122.xBin He, Guanglin Li, & Jie Lian. (2002). A spline Laplacian ECG estimator in a realistic geometry volume conductor. IEEE Transactions on Biomedical Engineering, 49(2), 110-117. doi:10.1109/10.979350Besio, G., Koka, K., Aakula, R., & Weizhong Dai. (2006). Tri-polar concentric ring electrode development for Laplacian electroencephalography. IEEE Transactions on Biomedical Engineering, 53(5), 926-933. doi:10.1109/tbme.2005.863887Besio, W., Aakula, R., Koka, K., & Dai, W. (2006). Development of a Tri-polar Concentric Ring Electrode for Acquiring Accurate Laplacian Body Surface Potentials. Annals of Biomedical Engineering, 34(3), 426-435. doi:10.1007/s10439-005-9054-8Besio, W., & Chen, T. (2007). Tripolar Laplacian electrocardiogram and moment of activation isochronal mapping. Physiological Measurement, 28(5), 515-529. doi:10.1088/0967-3334/28/5/006Prats-Boluda, G., Garcia-Casado, J., Martinez-de-Juan, J. L., & Ye-Lin, Y. (2011). Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals. Medical Engineering & Physics, 33(4), 446-455. doi:10.1016/j.medengphy.2010.11.009Prats-Boluda, G., Ye-Lin, Y., Bueno-Barrachina, J., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2016). Towards the clinical use of concentric electrodes in ECG recordings: influence of ring dimensions and electrode position. Measurement Science and Technology, 27(2), 025705. doi:10.1088/0957-0233/27/2/025705Zena-Giménez, V., Garcia-Casado, J., Ye-Lin, Y., Garcia-Breijo, E., & Prats-Boluda, G. (2018). A Flexible Multiring Concentric Electrode for Non-Invasive Identification of Intestinal Slow Waves. Sensors, 18(2), 396. doi:10.3390/s18020396Ye-Lin, Y., Alberola-Rubio, J., Prats-boluda, G., Perales, A., Desantes, D., & Garcia-Casado, J. (2014). Feasibility and Analysis of Bipolar Concentric Recording of Electrohysterogram with Flexible Active Electrode. Annals of Biomedical Engineering, 43(4), 968-976. doi:10.1007/s10439-014-1130-5Wang, K., Parekh, U., Pailla, T., Garudadri, H., Gilja, V., & Ng, T. N. (2017). Stretchable Dry Electrodes with Concentric Ring Geometry for Enhancing Spatial Resolution in Electrophysiology. Advanced Healthcare Materials, 6(19), 1700552. doi:10.1002/adhm.201700552Lidón-Roger, J., Prats-Boluda, G., Ye-Lin, Y., Garcia-Casado, J., & Garcia-Breijo, E. (2018). Textile Concentric Ring Electrodes for ECG Recording Based on Screen-Printing Technology. Sensors, 18(1), 300. doi:10.3390/s18010300Makeyev, O., Ding, Q., & Besio, W. G. (2016). Improving the accuracy of Laplacian estimation with novel multipolar concentric ring electrodes. Measurement, 80, 44-52. doi:10.1016/j.measurement.2015.11.017Makeyev, O., & Besio, W. (2016). Improving the Accuracy of Laplacian Estimation with Novel Variable Inter-Ring Distances Concentric Ring Electrodes. Sensors, 16(6), 858. doi:10.3390/s16060858Makeyev, O. (2018). Solving the general inter-ring distances optimization problem for concentric ring electrodes to improve Laplacian estimation. BioMedical Engineering OnLine, 17(1). doi:10.1186/s12938-018-0549-6Ye-Lin, Y., Bueno-Barrachina, J. M., Prats-boluda, G., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2017). Wireless sensor node for non-invasive high precision electrocardiographic signal acquisition based on a multi-ring electrode. Measurement, 97, 195-202. doi:10.1016/j.measurement.2016.11.009Prats-Boluda, G., Ye-Lin, Y., Pradas-Novella, F., Garcia-Breijo, E., & Garcia-Casado, J. (2018). Textile Concentric Ring Electrodes: Influence of Position and Electrode Size on Cardiac Activity Monitoring. Journal of Sensors, 2018, 1-9. doi:10.1155/2018/7290867Huiskamp, G. (1991). Difference formulas for the surface Laplacian on a triangulated surface. Journal of Computational Physics, 95(2), 477-496. doi:10.1016/0021-9991(91)90286-tHamilton, P. S., & Tompkins, W. J. (1986). Quantitative Investigation of QRS Detection Rules Using the MIT/BIH Arrhythmia Database. IEEE Transactions on Biomedical Engineering, BME-33(12), 1157-1165. doi:10.1109/tbme.1986.325695Koka, K., & Besio, W. G. (2007). Improvement of spatial selectivity and decrease of mutual information of tri-polar concentric ring electrodes. Journal of Neuroscience Methods, 165(2), 216-222. doi:10.1016/j.jneumeth.2007.06.007Prats-Boluda, G., Ye-Lin, Y., Bueno Barrachina, J. M., Senent, E., Rodriguez de Sanabria, R., & Garcia-Casado, J. (2015). Development of a portable wireless system for bipolar concentric ECG recording. Measurement Science and Technology, 26(7), 075102. doi:10.1088/0957-0233/26/7/07510

Identification of atrial fibrillation drivers by means of concentric ring electrodes

The prevalence of atrial fibrillation (AF) has tripled in the last 50 years due to population aging. High-frequency (DFdriver) activated atrial regions lead the activation of the rest of the atria, disrupting the propagation wavefront. Fourier based spectral analysis of body surface potential maps have been proposed for DFdriver identification, although these approaches present serious drawbacks due to their limited spectral resolution for short AF epochs and the blurring effect of the volume conductor. Laplacian signals (BC-ECG) from bipolar concentric ring electrodes (CRE) have been shown to outperform the spatial resolution achieved with conventional unipolar recordings. Our aimed was to determine the best DFdriver estimator in endocardial electrograms and to assess the BC-ECG capacity of CRE to quantify AF activity non-invasively

Towards Individualized Transcranial Electric Stimulation Therapy through Computer Simulation

Transkranielle Elektrostimulation (tES) beschreibt eine Gruppe von Hirnstimulationstechniken, die einen schwachen elektrischen Strom über zwei nicht-invasiv am Kopf angebrachten Elektroden applizieren. Handelt es sich dabei um einen Gleichstrom, spricht man von transkranieller Gleichstromstimulation, auch tDCS abgekürzt. Die allgemeine Zielstellung aller Hirnstimulationstechniken ist Hirnfunktion durch ein Verstärken oder Dämpfen von Hirnaktivität zu beeinflussen. Unter den Stimulationstechniken wird die transkranielle Gleichstromstimulation als ein adjuvantes Werkzeug zur Unterstützung der mikroskopischen Reorganisation des Gehirnes in Folge von Lernprozessen und besonders der Rehabilitationstherapie nach einem Schlaganfall untersucht. Aktuelle Herausforderungen dieser Forschung sind eine hohe Variabilität im erreichten Stimulationseffekt zwischen den Probanden sowie ein unvollständiges Verständnis des Zusammenspiels der der Stimulation zugrundeliegenden Mechanismen. Als Schlüsselkomponente für das Verständnis der Stimulationsmechanismen wird das zwischen den Elektroden im Kopf des Probanden aufgebaute elektrische Feld erachtet. Einem grundlegenden Konzept folgend wird angenommen, dass Hirnareale, die einer größeren elektrischen Feldstärke ausgesetzt sind, ebenso einen höheren Stimulationseffekt erfahren. Damit kommt der Positionierung der Elektroden eine entscheidende Rolle für die Stimulation zu. Allerdings verteilt sich das elektrische Feld wegen des heterogenen elektrischen Leitfähigkeitsprofil des menschlichen Kopfes nicht uniform im Gehirn der Probanden. Außerdem ist das Verteilungsmuster auf Grund anatomischer Unterschiede zwischen den Probanden verschieden. Die triviale Abschätzung der Ausbreitung des elektrischen Feldes anhand der bloßen Position der Stimulationselektroden ist daher nicht ausreichend genau für eine zielgerichtete Stimulation. Computerbasierte, biophysikalische Simulationen der transkraniellen Elektrostimulation ermöglichen die individuelle Approximation des Verteilungsmusters des elektrischen Feldes in Probanden basierend auf deren medizinischen Bildgebungsdaten. Sie werden daher zunehmend verwendet, um tDCS-Anwendungen zu planen und verifizieren, und stellen ein wesentliches Hilfswerkzeug auf dem Weg zu individualisierter Schlaganfall-Rehabilitationstherapie dar. Softwaresysteme, die den dahinterstehenden individualisierten Verarbeitungsprozess erleichtern und für ein breites Feld an Forschern zugänglich machen, wurden in den vergangenen Jahren für den Anwendungsfall in gesunden Erwachsenen entwickelt. Jedoch bleibt die Simulation von Patienten mit krankhaftem Hirngewebe und strukturzerstörenden Läsionen eine nicht-triviale Aufgabe. Daher befasst sich das hier vorgestellte Projekt mit dem Aufbau und der praktischen Anwendung eines Arbeitsablaufes zur Simulation transkranieller Elektrostimulation. Dabei stand die Anforderung im Vordergrund medizinische Bildgebungsdaten insbesondere neurologischer Patienten mit krankhaft verändertem Hirngewebe verarbeiten zu können. Der grundlegende Arbeitsablauf zur Simulation wurde zunächst für gesunde Erwachsene entworfen und validiert. Dies umfasste die Zusammenstellung medizinischer Bildverarbeitungsalgorithmen zu einer umfangreichen Verarbeitungskette, um elektrisch relevante Strukturen in den Magnetresonanztomographiebildern des Kopfes und des Oberkörpers der Probanden zu identifizieren und zu extrahieren. Die identifizierten Strukturen mussten in Computermodelle überführt werden und das zugrundeliegende, physikalische Problem der elektrischen Volumenleitung in biologischen Geweben mit Hilfe numerischer Simulation gelöst werden. Im Verlauf des normalen Alterns ist das Gehirn strukturellen Veränderungen unterworfen, unter denen ein Verlust des Hirnvolumens sowie die Ausbildung mikroskopischer Veränderungen seiner Nervenfaserstruktur die Bedeutendsten sind. In einem zweiten Schritt wurde der Arbeitsablauf daher erweitert, um diese Phänomene des normalen Alterns zu berücksichtigen. Die vordergründige Herausforderung in diesem Teilprojekt war die biophysikalische Modellierung der veränderten Hirnmikrostruktur, da die resultierenden Veränderungen im Leitfähigkeitsprofil des Gehirns bisher noch nicht in der Literatur quantifiziert wurden. Die Erweiterung des Simulationsablauf zeichnete sich vorrangig dadurch aus, dass mit unsicheren elektrischen Leitfähigkeitswerten gearbeitet werden konnte. Damit war es möglich den Einfluss der ungenau bestimmbaren elektrischen Leitfähigkeit der verschiedenen biologischen Strukturen des menschlichen Kopfes auf das elektrische Feld zu ermitteln. In einer Simulationsstudie, in der Bilddaten von 88 Probanden einflossen, wurde die Auswirkung der veränderten Hirnfaserstruktur auf das elektrische Feld dann systematisch untersucht. Es wurde festgestellt, dass sich diese Gewebsveränderungen hochgradig lokal und im Allgemeinen gering auswirken. Schließlich wurden in einem dritten Schritt Simulationen für Schlaganfallpatienten durchgeführt. Ihre großen, strukturzerstörenden Läsionen wurden dabei mit einem höheren Detailgrad als in bisherigen Arbeiten modelliert und physikalisch abermals mit unsicheren Leitfähigkeiten gearbeitet, was zu unsicheren elektrischen Feldabschätzungen führte. Es wurden individuell berechnete elektrische Felddaten mit der Hirnaktivierung von 18 Patienten in Verbindung gesetzt, unter Berücksichtigung der inhärenten Unsicherheit in der Bestimmung der elektrischen Felder. Das Ziel war zu ergründen, ob die Hirnstimulation einen positiven Einfluss auf die Hirnaktivität der Patienten im Kontext von Rehabilitationstherapie ausüben und so die Neuorganisierung des Gehirns nach einem Schlaganfall unterstützen kann. Während ein schwacher Zusammenhang hergestellt werden konnte, sind weitere Untersuchungen nötig, um diese Frage abschließend zu klären.:Kurzfassung Abstract Contents 1 Overview 2 Anatomical structures in magnetic resonance images 2 Anatomical structures in magnetic resonance images 2.1 Neuroanatomy 2.2 Magnetic resonance imaging 2.3 Segmentation of MR images 2.4 Image morphology 2.5 Summary 3 Magnetic resonance image processing pipeline 3.1 Introduction to human body modeling 3.2 Description of the processing pipeline 3.3 Intermediate and final outcomes in two subjects 3.4 Discussion, limitations & future work 3.5 Conclusion 4 Numerical simulation of transcranial electric stimulation 4.1 Electrostatic foundations 4.2 Discretization of electrostatic quantities 4.3 The numeric solution process 4.4 Spatial discretization by volume meshing 4.5 Summary 5 Simulation workflow 5.1 Overview of tES simulation pipelines 5.2 My implementation of a tES simulation workflow 5.3 Verification & application examples 5.4 Discussion & Conclusion 6 Transcranial direct current stimulation in the aging brain 6.1 Handling age-related brain changes in tES simulations 6.2 Procedure of the simulation study 6.3 Results of the uncertainty analysis 6.4 Findings, limitations and discussion 7 Transcranial direct current stimulation in stroke patients 7.1 Bridging the gap between simulated electric fields and brain activation in stroke patients 7.2 Methodology for relating simulated electric fields to functional MRI data 7.3 Evaluation of the simulation study and correlation analysis 7.4 Discussion & Conclusion 8 Outlooks for simulations of transcranial electric stimulation List of Figures List of Tables Glossary of Neuroscience Terms Glossary of Technical Terms BibliographyTranscranial electric current stimulation (tES) denotes a group of brain stimulation techniques that apply a weak electric current over two or more non-invasively, head-mounted electrodes. When employing a direct-current, this method is denoted transcranial direct current stimulation (tDCS). The general aim of all tES techniques is the modulation of brain function by an up- or downregulation of brain activity. Among these, transcranial direct current stimulation is investigated as an adjuvant tool to promote processes of the microscopic reorganization of the brain as a consequence of learning and, more specifically, rehabilitation therapy after a stroke. Current challenges of this research are a high variability in the achieved stimulation effects across subjects and an incomplete understanding of the interplay between its underlying mechanisms. A key component to understanding the stimulation mechanism is considered the electric field, which is exerted by the electrodes and distributes in the subjects' heads. A principle concept assumes that brain areas exposed to a higher electric field strength likewise experience a higher stimulation. This attributes the positioning of the electrodes a decisive role for the stimulation. However, the electric field distributes non-uniformly across subjects' brains due to the heterogeneous electrical conductivity profile of the human head. Moreover, the distribution pattern is variable between subjects due to their individual anatomy. A trivial estimation of the distribution of the electric field solely based on the position of the stimulating electrodes is, therefore, not precise enough for a well-targeted stimulation. Computer-based biophysical simulations of transcranial electric stimulation enable the individual approximation of the distribution pattern of the electric field in subjects based on their medical imaging data. They are, thus, increasingly employed for the planning and verification of tDCS applications and constitute an essential tool on the way to individualized stroke rehabilitation therapy. Software pipelines facilitating the underlying individualized processing for a wide range of researchers have been developed for use in healthy adults over the past years, but, to date, the simulation of patients with abnormal brain tissue and structure disrupting lesions remains a non-trivial task. Therefore, the presented project was dedicated to establishing and practically applying a tES simulation workflow. The processing of medical imaging data of neurological patients with abnormal brain tissue was a central requirement in this process. The basic simulation workflow was first designed and validated for the simulation of healthy adults. This comprised compiling medical image processing algorithms into a comprehensive workflow to identify and extract electrically relevant physiological structures of the human head and upper torso from magnetic resonance images. The identified structures had to be converted to computational models. The underlying physical problem of electric volume conduction in biological tissue was solved by means of numeric simulation. Over the course of normal aging, the brain is subjected to structural alterations, among which a loss of brain volume and the development of microscopic alterations of its fiber structure are the most relevant. In a second step, the workflow was, thus, extended to incorporate these phenomena of normal aging. The main challenge in this subproject was the biophysical modeling of the altered brain microstructure as the resulting alterations to the conductivity profile of the brain were so far not quantified in the literature. Therefore, the augmentation of the workflow most notably included the modeling of uncertain electrical properties. With this, the influence of the uncertain electrical conductivity of the biological structures of the human head on the electric field could be assessed. In a simulation study, including imaging data of 88 subjects, the influence of the altered brain fiber structure on the electric field was then systematically investigated. These tissue alterations were found to exhibit a highly localized and generally low impact. Finally, in a third step, tDCS simulations of stroke patients were conducted. Their large, structure-disrupting lesions were modeled in a more detailed manner than in previous stroke simulation studies, and they were physically, again, modeled by uncertain electrical conductivity resulting in uncertain electric field estimates. Individually simulated electric fields were related to the brain activation of 18 patients, considering the inherently uncertain electric field estimations. The goal was to clarify whether the stimulation exerts a positive influence on brain function in the context of rehabilitation therapy supporting brain reorganization following a stroke. While a weak correlation could be established, further investigation will be necessary to answer that research question.:Kurzfassung Abstract Contents 1 Overview 2 Anatomical structures in magnetic resonance images 2 Anatomical structures in magnetic resonance images 2.1 Neuroanatomy 2.2 Magnetic resonance imaging 2.3 Segmentation of MR images 2.4 Image morphology 2.5 Summary 3 Magnetic resonance image processing pipeline 3.1 Introduction to human body modeling 3.2 Description of the processing pipeline 3.3 Intermediate and final outcomes in two subjects 3.4 Discussion, limitations & future work 3.5 Conclusion 4 Numerical simulation of transcranial electric stimulation 4.1 Electrostatic foundations 4.2 Discretization of electrostatic quantities 4.3 The numeric solution process 4.4 Spatial discretization by volume meshing 4.5 Summary 5 Simulation workflow 5.1 Overview of tES simulation pipelines 5.2 My implementation of a tES simulation workflow 5.3 Verification & application examples 5.4 Discussion & Conclusion 6 Transcranial direct current stimulation in the aging brain 6.1 Handling age-related brain changes in tES simulations 6.2 Procedure of the simulation study 6.3 Results of the uncertainty analysis 6.4 Findings, limitations and discussion 7 Transcranial direct current stimulation in stroke patients 7.1 Bridging the gap between simulated electric fields and brain activation in stroke patients 7.2 Methodology for relating simulated electric fields to functional MRI data 7.3 Evaluation of the simulation study and correlation analysis 7.4 Discussion & Conclusion 8 Outlooks for simulations of transcranial electric stimulation List of Figures List of Tables Glossary of Neuroscience Terms Glossary of Technical Terms Bibliograph

New advances in vehicular technology and automotive engineering

An automobile was seen as a simple accessory of luxury in the early years of the past century. Therefore, it was an expensive asset which none of the common citizen could afford. It was necessary to pass a long period and waiting for Henry Ford to establish the first plants with the series fabrication. This new industrial paradigm makes easy to the common American to acquire an automobile, either for running away or for working purposes. Since that date, the automotive research grown exponentially to the levels observed in the actuality. Now, the automobiles are indispensable goods; saying with other words, the automobile is a first necessity article in a wide number of aspects of living: for workers to allow them to move from their homes into their workplaces, for transportation of students, for allowing the domestic women in their home tasks, for ambulances to carry people with decease to the hospitals, for transportation of materials, and so on, the list don’t ends. The new goal pursued by the automotive industry is to provide electric vehicles at low cost and with high reliability. This commitment is justified by the oil’s peak extraction on 50s of this century and also by the necessity to reduce the emissions of CO2 to the atmosphere, as well as to reduce the needs of this even more valuable natural resource. In order to achieve this task and to improve the regular cars based on oil, the automotive industry is even more concerned on doing applied research on technology and on fundamental research of new materials. The most important idea to retain from the previous introduction is to clarify the minds of the potential readers for the direct and indirect penetration of the vehicles and the vehicular industry in the today’s life. In this sequence of ideas, this book tries not only to fill a gap by presenting fresh subjects related to the vehicular technology and to the automotive engineering but to provide guidelines for future research. This book account with valuable contributions from worldwide experts of automotive’s field. The amount and type of contributions were judiciously selected to cover a broad range of research. The reader can found the most recent and cutting-edge sources of information divided in four major groups: electronics (power, communications, optics, batteries, alternators and sensors), mechanics (suspension control, torque converters, deformation analysis, structural monitoring), materials (nanotechnology, nanocomposites, lubrificants, biodegradable, composites, structural monitoring) and manufacturing (supply chains). We are sure that you will enjoy this book and will profit with the technical and scientific contents. To finish, we are thankful to all of those who contributed to this book and who made it possible.info:eu-repo/semantics/publishedVersio

Improvement of the oxygen reduction cathodes of microbial fuel cells designed to treat municipal wastewater

Phd ThesisThe Microbial Fuel Cell is a technology for self-powered pollution remediation, receiving widespread academic interest only since the turn of the 21st century. The device centres on immobilised anaerobic microbes that oxidise organic pollutants in industrial or domestic wastewater and generate an electrical charge. To generate useful energy from this charge, oxygen is commonly used as an electron acceptor at a cathode to complete the cell. This oxygen reduction reaction (ORR) requires catalysis and is thought to produce H2O at pH7. High cost materials such as Platinum and energy in-efficient materials such as activated carbon are typically used to catalyse this reaction in MFC’s. The majority of ORR catalysis research is based in acid or alkali media. To facilitate MFC commercialisation the project aim was to enhance cathode performance by developing an active, selective, stable and low cost oxygen reduction catalyst. Presented within this thesis is a fundamental study of the enzyme mimic catalyst Iron Phthalocyanine (FePc). With the addition of a novel anion selective binder and membranes, the low cost cathodes are applied to laboratory scale single chamber MFC’s fed with primary clarifier influent wastewater. With use of a rotating ring disc electrode, the O2 reduction mechanism was found to produce OH- and the O2 adsorption step was not rate limiting. The mechanism with the lowest overpotential proceeds through an intermediary of strongly adsorbed peroxide. Unfortunately, partial release of this H2O2, ranging from 0.5 to 7%, caused catalyst de-stabilisation. The traditional approach of catalyst pyrolysis was found to be ineffective remedy, reducing the number of viable sites (by 96%) and overall activity. It was hypothesised that pH splitting from OH- production could be reduced with anion selective materials. A Quaternary-1,4-diazabicyclo-[2.2.2]-octane Polysulfone (QDPSU) anion exchange ionomer utilising a Dabco anion exchange group was implemented in thin films and MFC cathodes as a substitute for Nafion. A facile tafel slope of 25.4 mV per decade of current implied a decrease in the overall activation energy for ORR. Oxygen diffusivity was comparable with Nafion and in real wastewater the air cathodes producing an average of 34% more power in MFC’s. An impedance spectroscopy study identified a numerical way of quantifying the poisoning of anion exchange groups. The addition of ion selective membranes increased the resistance showing this process to be related to ion diffusion, thin membranes with quaternary ammonium produced the best results