Bioelectronic medicine has drawn immense attention in recent years. Specifically, vagally neuromodulation methods are associated with a large number of physiological processes and corresponding regulatory mechanisms. It has been shown that a constructive neuromodulatory intervention on the afferent pathway of the autonomic system of the human body has a potential therapeutic indication for a wide range of disorders, from chronic pain to metabolic, inflammatory, and to cardiovascular diseases.Auricular vagus nerve stimulation (aVNS) is a non- or minimal-invasive subtype of vagus nerve stimulation and is applied in the vagally innervated region cymba conchae (CC) region of the auricle. However, detailed anatomical information on the CC at the microstructural level, along with in-silico models which highlight the electrode-tissue interaction and allow us for the current optimization of the stimulation paradigms, is missing. The aVNS is mainly performed as an open-loop, with long-term potential therapeutic indications. Hence, stimulation parameters are empirically set, and a periodical readjustment procedure is necessary. Currently, aVNS is nonindividualized and applied regardless of the patient's physiological state. Hence, continuous monitoring of individual physiological parameters should serve as a basis to optimize the aVNS settings to achieve a specific therapeutic outcome.aVNS should work in concert with the autonomous system to provoke constructive intervention to mitigate the appeared imbalances in the system. The cardiovagal branch of the baroreflex as a part of the autonomous system is of high clinical relevance when detecting disturbance of the autonomic nervous system (ANS). The overall hysteretic behavior of the baroreflex is mainly assessed by the autonomous provocation through the blood pressure change in response to administrated vasoactive substances. Whilst those methods are costly, invasive, and do not reflect a pure physiological behavior due to their unknown intervention share, a natural, spontaneous blood pressure change due to respiration and orthostatic test reflects pure autonomous reflexes. In addition, existing methods do not present a solid and consistent cardiovagal hysteretic behavior of the baroreflex. Moreover, a compact dynamic cardiovascular and autonomous simulation is needed to deeply understand the cardiovagal baroreflex while providing potential key factors for in-silico aVNS optimization.For the first time, we employed high-resolution Episcopic imaging (HREM) to generate histologic volume data from donated human cadaver ears. Mirco-anatomical 3D vascular and nerve structures were reconstructed in several samples of the auricular cymba conchae. The feasibility of HREM to visualize anatomical structures was assessed in that diameters, occupied areas, volumes, and mutual distances between auricular arteries, nerves, and veins were registered. Moreover, a realistic and detailed 3D in-silico model of the auricle, including the skin, cartilage, fat, intradermal arteries, and nerves, is prepared and integrated into a head and neck model to have auricular vagus nerve extension and corresponding interconnections to the brain stem. This model should form the basis for future optimization of aVNS.The selected region of CC (3 × 5.5 mm) showed in its cross-sections (perpendicular to the skin surface) 21.7 ± 2.7 (mean ± standard deviation) arteries and 14.66 ± 2.74 nerve fibers. Identified nerve diameters were 33.66 ± 21.71 μm, and arteries had diameters in the range of 71.58 ± 80.70 μm. The respective occupied area showed a share of, on average, 2.71% and 0.3% for arteries and nerves, respectively, and similar volume occupancy for arteries and nerves. The intercentroid minimum distance between arteries and nerves was 274 ± 222 μm. The density of vessels and nerves around a point within CC on a given grid was assessed, showing that 50% of all vessels and nerves were found in a radial distance of 1.6–1.8 mm from any of these points, which is strategically relevant when using stimulation needles in the auricle for excitation of nerves.We propose a novel ellipse analysis to characterize hysteresis of the spontaneous respiration related cardiovagal baroreflex for the orthostatic and head-up-tilt test. Up and down sequences of pressure changes, as well as the working point of baroreflex, are considered. The EuroBaVar data set for supine and standing was employed. In addition, for the head-up-tilt (HUT), we performed our experiments with paced respiration at 0.1Hz. In the supine position, the ellipses are more elongated (by about 46%) and steeper (by about 4.3° as the median) than standing, indicating larger heart interval variability (70.7 versus 47.9 ms) and smaller blood pressure variability (5.8 versus 8.9 mmHg) in supine. The ellipses show a higher baroreflex sensitivity for supine (15.7 ms/mmHg as the median) than standing (7 ms/mmHg). The center of the ellipse moves from supine to standing, which describes the overall sigmoid shape of the baroreflex with the moving working point HUT test shows a nonlinear cardiovagal baroreflex from supine to 80° tilt.In-silico simulation of the cardiovascular system (CVS) was established in the time domain. The HUT test showed both neuro- and myogenic arms of the baroreflex. Hence, a reduction of 770ml/min for mean cardiac output, 15.2% for mean heart period, and an elevation of 77% for lower body resistance when the model is tilted from supine to 80° can be seen. However, optimization based on physiological data is needed to simulate the cardiovagal hysteresis properly.We developed a novel aVNS hardware for closed-loop application, which utilizes cardiorespiratory sensing using embedded sensors (and/or external sensors), processes and analyzes the acquired data in real-time, and directly governs the settings of aVNS. We show inlab setup that aVNS stimulation can be arbitrarily synchronized with respiratory and cardiac phases (as derived from respiration belt, electrocardiography and/or photo plethysmography) while mimicking baroreceptor-related afferent input along the vagus nerve projecting into the brain. Our designed system identified > 90% of all respiratory and cardiac cycles and activated stimulation at the target point with a precision of ± 100 ms despite the intrinsic respiratory and heart rate variability reducing the predictability.In this work, we presented an in-silico 3D model of CC on the micrometer scale based on HREM for aVNS optimization, along with aVN integrated within the head model. Moreover, we established an in-silico model of CVS and ANS for dynamic investigations. Our novel ellipse method reveals spontaneous cardiovagal hysteresis considering gain and set-point change during respiration. The developed aVNS stimulator offers a solid basis for future clinical research into closed-loop time-synchronized aVNS in favor of personalized therapy. Preliminary experiments on healthy humans were performed.In the future, an in-silico 3D model of the auricle should consider more samples and a larger area of investigation to account for interpersonal variations. The in-silico CVS model could simulate different disorders. The closed-loop aVNS provides a flexible framework for the personalization of the aVNS stimulator. Obviously, more experiments are needed on subjects with imbalanced health conditions to investigate the aVNS in different therapeutic settings.
