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Development of wearable point-of-care medical devices faces many challenges. Besides technological and clinical issues, demands on robustness, miniaturization, and user interface design are of paramount importance. However, a systematic assessment of these non-functional but essential requirements is often impossible within the first product cycle. Later, surveys on user satisfaction with existing devices and user demands can offer significant input for device re-development and improvement. In this paper, we present a survey on satisfaction with and demands for a wearable medical device for percutaneous auricular vagus nerve stimulation (pVNS). We analyzed 36 responses from patients treated with pVNS and five responses from experienced physicians in order to devise a future concept of pVNS. Main shortcomings of a current pVNS device were identified to be lacking water resistance and mechanical robustness, both impairing daily activities. Painful sensation during pVNS application, unwanted side effects like skin irritations and strongly varying perception of the stimulation were reported. Results urge for more patient self-governance and an (automatic) adjustment of the stimulation to the current physiological state of the patient. Attained results support a strategic approach for future developments of pVNS towards personalized health care.

An accurate detection of anatomical structures in electrical impedance tomography (EIT) is still at an early stage. Aorta detection in EIT is of special interest, since it would favor non-invasive assessment of hemodynamic processes in the body. Here, diverse EIT reconstruction parameters of the GREIT algorithm were systematically evaluated to detect the aorta after saline bolus injection in apnea. True aorta position and size were taken from computed tomography (CT). A comparison with CT showed that the smallest error for aorta displacement was attained for noise figure nf = 0.7, weighting radius rw = 0.15, and target size ts = 0.01. The spatial extension of the aorta was most precise for nf = 0.7, rw = 0.25, and ts = 0.07. Detection accuracy (F1-score) was highest with nf = 0.6, rw = 0.15, and ts = 0.04. This work provides algorithm-related evidence for potentially accurate aorta detection in EIT after injection of a saline bolus.