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Therapeutic applications of auricular vagus nerve stimulation (VNS) have drawn recent attention. Since the targeted stimulation process and parameters depend on the electrode-tissue interaction, the lack of structural anatomical information on innervation and vascularization of the auricle restrain the current optimization of stimulation paradigms. For the first time, we employed high-resolution episcopic imaging (HREM) to generate histologic volume data from donated human cadaver ears. Optimal parameters for specimen preparation were evaluated. Anatomical 3D vascular and nerve structures were reconstructed in one sample of an auricular cymba conchae (CC). 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. The selected region of CC (3 × 5.5 mm) showed in its cross-sections 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. Inter-centroid 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. HREM seems suitable for anatomical studies of the human ear. A 3D model of CC was established in the micrometer scale, which forms the basis for future optimization of the auricular VNS. Obviously, the presented single cadaver study needs to be validated by additional anatomical data on the innervation and vascularization of the auricle.

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Auricular vagus nerve stimulation (aVNS) is a novel neuromodulatory therapy used for treatment of various chronic systemic disorders. Currently, aVNS is non-individualized, disregarding the physiological state of the patient and therefore making it difficult to reach optimum therapeutic outcomes. A closed-loop aVNS system is required to avoid over-stimulation and under-stimulation of patients, leading to personalized and thus improved therapy. This can be achieved by continuous monitoring of individual physiological parameters that serve as a basis for the selection of optimal aVNS settings. In this work 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 settings of aVNS. We show in-lab 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. The developed system offers a solid basis for future clinical research into closed-loop aVNS in favour of personalized therapy.

Percutaneous auricular vagus nerve stimulation (pVNS) is a novel approach of treating cardiovascular and inflammatory diseases, as well as pain and neurological conditions. The treatment can be optimized by using biosignals as objective measures and feedback-control. One suitable biofeedback could be the use of pulse rate and pulse rate variability (PRV) derived from optical pulse plethysmography (PPG) instead of heart rate and heart rate variability (HRV) derived from electrocardiogram (ECG). For this purpose, a single-lead ECG on the thorax and a PPG on the earlobe were measured simultaneously on 10 healthy subjects for 420 s during three different respiratory phases. The data was analyzed and compared with scatterplots, the Pearson correlation coefficient and a Bland-Altman analysis. The outcomes show a very high correlation of heart rates from PPG and ECG (= 0.9663) and SDNN values (= 0.9791). Comparison of RMSSD values showed a high positive correlation (= 0.7963) but a mean overestimation of 10 ms in RMSSD values measured with the PPG. The results presented suggest that PRV could be and alternative biofeedback used in pVNS.