Graphene-based Distributed 3D Sensing Electrodes for Mapping Spatiotemporal Auricular Physiological Signals

TL;DR

This paper introduces a novel graphene-based 3D sensing device for full-auricle physiological mapping, enabling detailed spatiotemporal analysis of auricular signals with potential biomedical applications.

Contribution

It presents a new 3D conformable sensing platform with embedded electrodes and personalized molds, capable of comprehensive auricular signal mapping using a one-step 3D-printing process.

Findings

First 3D AESR contours generated for human subjects

Observed region-specific AESR changes after exercise in 98% of tests

Validated AESR correlations with heart rate and blood pressure

Abstract

Underneath the ear skin there are richly branching vascular and neural networks that ultimately connecting to our heart and brain. Hence, the three-dimensional (3D) mapping of auricular electrophysiological signals could provide a new perspective for biomedical studies such as diagnosis of cardiovascular diseases and neurological disorders. However, it is still extremely challenging for current sensing techniques to cover the entire ultra-curved auricle. Here, we report a graphene-based ear-conformable sensing device with embedded and distributed 3D electrodes which enable full-auricle physiological monitoring. The sensing device, which incorporates programable 3D electrode thread array and personalized auricular mold, has 3D-conformable sensing interfaces with curved auricular skin, and was developed using one-step multi-material 3D-printing process. As a proof-of-concept, spatiotemporal auricular electrical skin resistance (AESR) mapping was demonstrated. For the first time, 3D AESR contours were generated and human subject-specific AESR distributions among a population were observed. From the data of 17 volunteers, the auricular region-specific AESR changes after cycling exercise were observed in 98% of the tests and were validated via machine learning techniques. Correlations of AESR with heart rate and blood pressure were also studied using statistical analysis. This 3D electronic platform and AESR-based new biometrical findings show promising biomedical applications.