Mapping of Spatiotemporal Auricular Electrophysiological Signals Reveals Human Biometric Clusters

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number2201404
Journal / PublicationAdvanced Healthcare Materials
Volume11
Issue number23
Online published11 Oct 2022
Publication statusPublished - 7 Dec 2022

Link(s)

Abstract

Underneath the ear skin there are rich vascular network and sensory nerve branches. Hence, the 3D mapping of auricular electrophysiological signals can provide new biomedical perspectives. However, it is still extremely challenging for current sensing techniques to cover the entire ultra-curved auricle. Here, a 3D graphene-based ear-conformable sensing device with embedded and distributed 3D electrodes for full-auricle physiological monitoring is reported. As a proof-of-concept, spatiotemporal auricular electrical skin resistance (AESR) mapping is demonstrated for the first time, and human subject-specific AESR distributions are observed. From the data of more than 30 ears (both right and left ears), the auricular region-specific AESR changes after cycling exercise are observed in 98% of the tests and are clustered into four groups via machine learning-based data analyses. Correlations of AESR with heart rate and blood pressure are also studied. This 3D electronic platform and AESR-based biometrical findings show promising biomedical applications.

Research Area(s)

  • full-auricle electrophysiological monitoring, graphene-based 3D electrodes, human biometric clusters, machine learning, personalized healthcare sensors

Citation Format(s)

Mapping of Spatiotemporal Auricular Electrophysiological Signals Reveals Human Biometric Clusters. / Huang, Qingyun; Wu, Cong; Hou, Senlin et al.

In: Advanced Healthcare Materials, Vol. 11, No. 23, 2201404, 07.12.2022.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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