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The electrical field (E-field) of the biventricular (BV) stimulation is important for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex.
The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
The modeling and simulation was carried out using the electromagnetic simulation software CST. Five multipolar left ventricular (LV) electrodes, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modelled. A selection were integrated into the heart rhythm model (Schalk, Offenburg) for the electrical field simulation. The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
The BV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode with a pulse width of 0.5 ms each. The far-field potential at the RA electrode tip was 32.86 mV and 185.97 mV at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal ablation electrode. The temperature at the catheter tip was 103.87 °C after 5 s ablation time and 37.61 °C at a distance of 2 mm inside the myocardium. After 15 s, the temperature was 118.42 °C and 42.13 °C.
Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF and could be used to optimize the CRT and AF ablation.
Das normalhörende auditorische System ist in der Lage, interaurale Zeit- bzw. Phasendifferenzen zur verbesserten Signaldetektion im Störgeräusch zu nutzen. Dieses Phänomen wird häufig als binaurale Entmaskierung bezeichnet und ist sowohl bei einfachen Signalen wie Sinustönen, als auch bei Sprachsignalen im Störgeräusch wirksam. Vorangegangene Studien haben gezeigt, dass binaurale Entmaskierung eingeschränkt auch bei bilateralen CI-Trägern beobachtbar ist (Zirn et al., 2016).
Aktuelle Ergebnisse zeigen, dass die binaurale Entmaskierung sensitiv gegenüber der bilateralen CI-Anpassung ist. So lässt sich der Effekt durch tonotopen Abgleich und Herausstellen eines apikalen Feinstrukturkanals modulieren. Steigerungen der binauralen Entmaskierung um bis zu 1,5 dB sind auf diese Weise gegenüber der konventionellen CI-Anpassung möglich. Allerdings variiert der Einfluss der CI-Anpassung interindividuell erheblich.
Die drei großen Hersteller von Cochlea-Implantat (CI)-Systemen ermöglichen es klinischen Audiologen, die Mikrofoneigenschaften der meisten CI-Sprachprozessoren zu prüfen. Dazu können bei diesen Sprachprozessoren Monitorkopfhörer angeschlossen und das/die Mikrofon(e) inklusive eines Teils der Signalvorverarbeitung abgehört werden. Präzise Angaben dazu, mit welchen Stimuli, bei welchem Pegel und nach welchem Kriterium diese Prüfung stattfinden soll, machen die CI-Hersteller nicht. Auf Basis dieser Prüfung soll der Audiologe dann über die Funktion der Mikrofone und damit darüber entscheiden, ob der betreffende Sprachprozessor an den Hersteller eingeschickt wird oder nicht.
Zur Objektivierung der CI-Sprachprozessor-Mikrofon-Prüfung haben wir eine Testbox entwickelt, mit der alle abhörbaren aktuellen CI-Sprachprozessoren der drei großen Hersteller geprüft werden können. Die Box wurde im 3D-Druck-Verfahren hergestellt. Der zu prüfende Sprachprozessor wird in die Messbox eingehängt und über einen darin verbauten Lautsprecher mit definierten Prüfsignalen (Sinustöne unterschiedlicher Frequenz) beschallt. Das Mikrofonsignal wird über das Kabel der Monitorkopfhörer herausgeführt und mit einer Shifting- and Scaling-Schaltung in einen Spannungsbereich transformiert, der für die AD-Wandlung mit einem Mikrokontroller (ATmega1280 verbaut auf einem Arduino Mega) geeignet ist. Derselbe Mikrokontroller übernimmt über einen eigens gebauten DA-Wandler die Ausgabe der Sinustöne über den Lautsprecher. Signalaufnahme und –wiedergabe erfolgen mit jeweils 38,5 kHz Samplingrate. Der für jede Frequenz über mehrere Perioden des Prüfsignals ermittelte Effektivwert wird mit dem Effektivwert, der mit einem neuwertigen Referenzprozessor für diese Frequenz gemessen wurde, verglichen. Die Messergebnisse werden graphisch auf einem Display ausgegeben.
Derzeit läuft eine erste Datenerhebung mit in der Klinik subjektiv auffällig gewordenen CI-Sprachprozessoren, die anschließend in der Messbox untersucht werden. So sollen realistische Schwellen für kritische Abweichungen von den Referenz-Effektivwerten ermittelt werden. Im weiteren Verlauf sollen dann Hit und False Alarm-Raten der subjektiven Prüfung bestimmt werden.
The growing complexity in RF front-ends, which support carrier aggregation and a growing number of frequency bands, leads to tightened nonlinearity requirements in all sub-components. The generation of third order intermodulation products (IMD3) are typical problems caused by the non-linearity of SAW devices. In the present work, we investigate temperature compensating (TC) SAW devices on Lithium Niobate-rot128YX. An accurate FEM simulation model [1] is employed, which allows to better understand the origin of nonlinearities in such acoustic devices.
Spectral analysis of signal averaging electrocardiography in atrial and ventricular tachyarrhythmias
(2017)
Background: Targeting complex fractionated atrial electrograms detected by automated algorithms during ablation of persistent atrial fibrillation has produced conflicting outcomes in previous electrophysiological studies. The aim of the investigation was to evaluate atrial and ventricular high frequency fractionated electrical signals with signal averaging technique.
Methods: Signal averaging electrocardiography (ECG) allows high resolution ECG technique to eliminate interference noise signals in the recorded ECG. The algorithm uses automatic ECG trigger function for signal averaged transthoracic, transesophageal and intracardiac ECG signals with novel LabVIEW software (National Instruments, Austin, Texas, USA). For spectral analysis we used fast fourier transformation in combination with spectro-temporal mapping and wavelet transformation for evaluation of detailed information about the frequency and intensity of high frequency atrial and ventricular signals.
Results: Spectral-temporal mapping and wavelet transformation of the signal averaged ECG allowed the evaluation of high frequency fractionated atrial signals in patients with atrial fibrillation and high frequency ventricular signals in patients with ventricular tachycardia. The analysis in the time domain evaluated fractionated atrial signals at the end of the signal averaged P-wave and fractionated ventricular signals at the end of the QRS complex. The analysis in the frequency domain evaluated high frequency fractionated atrial signals during the P-wave and high frequency fractionated ventricular signals during QRS complex. The combination of analysis in the time and frequency domain allowed the evaluation of fractionated signals during atrial and ventricular conduction.
Conclusions: Spectral analysis of signal averaging electrocardiography with novel LabVIEW software can utilized to evaluate atrial and ventricular conduction delays in patients with atrial fibrillation and ventricular tachycardia. Complex fractionated atrial electrograms may be useful parameters to evaluate electrical cardiac arrhythmogenic signals in atrial fibrillation ablation.
Background: Cardiac resynchronization therapy (CRT) with biventricular (BV) pacing is an established therapy for heart failure (HF) patients (P) with sinus rhythm, reduced left ventricular (LV) ejection fraction (EF) and electrical ventricular desynchronization. The aim of the study was to evaluate electrical interventricular delay (IVD) and left ventricular delay (LVD) in right ventricular (RV) pacemaker pacing before upgrading to CRT BV pacing.
Methods: HF P (n=11, age 69.0 ± 7.9 years, 1 female, 10 males) with DDD pacemaker (n=10), DDD defibrillator (n=1), RV pacing, New York Heart Association (NYHA) class 3.0 ± 0.2 and 24.5 ± 4.9 % LVEF were measured by surface ECG and transesophageal bipolar LV ECG before upgrading to CRT defibrillator (n=8) and CRT pacemaker (n=3). IVD was measured between onset of QRS in the surface ECG and onset of LV signal in the transesophageal ECG. LVD was measured between onset and offset of LV signal in the transesophageal ECG. CRT atrioventricular (AV) and BV pacing delay were optimized by impedance cardiography.
Results: Interventricular and intraventricular desynchronization in RV pacemaker pacing were 228.2 ± 44.8 ms QRS duration, 86.5 ± 32.8ms IVD, 94.4 ± 23.8ms LVD, 2.6 ± 0.8 QRS-IVD-ratio with correlation between IVD and QRS-IVD-ratio (r=-0.668 P=0.0248) and 2.3 ± 0.7 QRS-LVD-ratio. The LVEF-IVD-ratio was 0.3 ± 0.1 with correlation between IVD and LVEF-IVD-ratio (r=-0.8063 P=0.00272) and with correlation between QRS duration and LVEF-IVD-ratio (r=-0.7251 P=0.01157). Optimal sensing and pacing AV delay were 128.3 ± 24.8 ms AV delay after atrial sensing (n=6) and 173.3 ± 40.4 ms AV delay after atrial pacing (n=3). Optimal BV pacing delay was -4.3 ± 11.3 ms between LV and RV pacing (n=7). During 30.4 ± 29.6 month CRT follow-up, the NYHA class improved from 3.1 ± 0.2 to 2.2 ± 0.3.
Conclusions: Transesophageal electrical IVD and LVD in RV pacemaker pacing may be additional useful ventricular desynchronization parameters to improve P selection for upgrading RV pacemaker pacing to CRT BV pacing.
Background: The electrical field (E-field) of the biventricular (BV) stimulation is essential for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex. 3D modeling allows the simulation of CRT and high frequency (HF) ablation.
Purpose: The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
Methods: The modeling and simulation was carried out using the electromagnetic simulation software. Five multipolar left ventricular (LV) electrodes, one epicardial LV electrode, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modeled. Different models of electrodes were integrated into a heart rhythm model for the electrical field simulation (fig.1). The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
Results: The RV and LV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode, each with a pulse width of 0.5 ms. The far-field potentials generated by the BV stimulations were perceived by the RA electrode. The far-field potential at the RA electrode tip was 32.86 mV. A far-field potential of 185.97 mV resulted at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal 8 mm ablation electrode. The temperature at the catheter tip was 103.87 ° C after 5 s ablation time, 44.17 ° C from the catheter tip in the myocardium and 37.61 ° C at a distance of 2 mm. After 10 s, the temperature at the three measuring points described above was 107.33 ° C, 50.87 ° C, 40.05 ° C and after 15 seconds 118.42 ° C, 55.75 ° C and 42.13 ° C.
Conclusions: Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF. The 3D simulation of the electrical field and temperature profile may be used to optimize the CRT and AF ablation.
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products (e.g., fuel cells, metal/air cells, electrolyzers) offer an additional observable, that is, the gas pressure. The dynamic coupling of current and/or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. This sensitivity can be exploited for model parameterization and validation. A general analysis of EPIS is presented, which shows the necessity of model-based interpretation of the complex EPIS shapes in the Nyquist plot (cf. Figure). We then present EPIS simulations for two different electrochemical cells: (1) a sodium/oxygen battery cell and (2) a hydrogen/air fuel cell. We use 1D or 2D electrochemical and transport models to simulate current excitation/pressure detection or pressure excitation/voltage detection. The results are compared to first EPIS experimental data available in literature [2,3].
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
The insufficient lifetime of lithium-ion batteries is one of the major cost driver for mobile applications. The battery pack in vehicles is one of the most expensive single components that practically must be excluded from premature replacement (i.e., before the life span of the other components end). Battery degradation is a complex physicochemical process that strongly depends on operating condition and environment. We present a simulation-based analysis of lithium-ion battery degradation during operation with a standard PHEV test cycle. We use detailed multiphysics (extended Newman-type) cell models that allow the assessment of local electrochemical potential, species and temperature distributions as driving forces for degradation, including solid electrolyte interphase (SEI) formation [1]. Fig. 1 shows an exemplary test cycle and the predicted resulting spatially-averaged SEI formation rate. We apply a time-upscaling approach to extrapolate the degradation analysis over long time scales, keeping physical accuracy while allowing end-of-life assessment [2]. Results are presented for lithium-ion battery cells with graphite/LFP chemistry. The behavior of these cells in terms of degradation propensity, performance, state of charge and other internal states is predicted during long-term cycling. State of health (SOH) is quantified as capacity fade and internal resistance increase as function of operation time.