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Dmitry Kireev

Research Associate

University of Texas

USA

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Graphene based electronic tattoo technologies for complex electrophysiology

(FREE) Electronic Textiles and Intelligent Skin Patches: Hardware and Software 2022

1 December 2022

Online

TechBlick Platform

Monitoring complex health-related electrophysiological signals such as arterial blood pressure (BP) in ambulatory settings is essential for a proper understanding of health conditions, predominantly cardiovascular diseases. Moreover, continuous long-term monitoring of BP for patients with sleep apnea, stroke, or hypertension is essential to understand their health risk factors and build preventative care routines. While conventional ambulatory BP monitoring devices exist, they are uncomfortable, bulky, and intrusive. The common drawbacks of all these systems are their bulkiness and incompatibility with skin’s elastic properties, causing sensor’s displacement during usage, consequently requiring frequent system re-calibration.
In our work, we introduce a unique wearable BP monitoring technology that leverages atomically-thin and electrically conductive graphene electronic tattoos (GETs) as main building blocks. The GETs are placed over the radial and ulnar arteries on the wrist and subsequently used as current injection and voltage sensing electrodes, measuring arterial bioimpedance. In contrast to any other wearable system, the atomically thin, lightweight, and skin-conformable GETs do not apply any external tension onto the skin during the operation. Hence, they are able to perform long-term and nocturnal measurements without discomforting the subjects. Using bioimpedance modality allows us to disregard the tattoo-skin interface, which is typically 2-4 orders of magnitude larger compared to tissue impedance, and record only from the areas of interest. Employing a machine learning regression model on the recorded bioimpedance value, we yield effective beat-to-beat detection of diastolic and systolic BP values with grade-A accuracy. Besides BP, we show that the same Bio-Z signal can be post-processed to estimate person’s RR in an entirely wearable and non-invasive manner.

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