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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.
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.
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.
Practical bottlenecks associated with commercialization of Lithium-air cells include capacity limitation and low cycling efficiency. The origin of such losses can be traced to complex electrochemical side reactions and reactant mass transport losses[1]. The efforts to minimize such losses include exploration of various electrolytes with additives[2], and cell component geometry and material design. Given the wide range of options for such materials, it is almost impractical to experimentally setup and characterize all those cells. Consequently, modeling and simulation studies are efficient alternatives to analyze spatially and temporally resolved cell behavior for various combinations of materials[3]. In this study, with the help of a two-dimensional multi physics model, we have focused on the effect of electrode and electrolyte interaction (electrochemistry), choice of electrolyte (species transport), and electrode geometry (electrode design) on the performance of a lithium-air button cell. Figure1a shows the schematics of the 2D axisymmetric computational domain. A comparative analysis of five different electrolytes was performed while focusing on the 2D distribution of local current density and the concentration of electro-chemically active species in the cell, that is, O2and Li+. Using two different cathode configurations, namely, flooded electrode and gas diffusion electrode (GDE)[4] at different cathode thickness, the effect of cell geometry and electrolyte saturation on cell performance was explored. Further, a detailed discussion on electrode volume utilization (cf. Figure1b) is presented via changes in the active volume of cathode that produces 90% of the total current with the cell current density for different combinations of electrolyte saturations and cathode thickness.
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
Muli-scale thermos-electrochemical modelling of aging mechanisms in an LFP/graphite lithium-ion cell
(2017)