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In Advanced healthcare materials

Underneath the ear skin there are rich vascular network and sensory nerve branches. Hence, the three-dimensional (3D) mapping of auricular electrophysiological signals could provide new biomedical perspectives. However, it is still extremely challenging for current sensing techniques to cover the entire ultra-curved auricle. Here, we report a 3D graphene-based ear-conformable sensing device with embedded and distributed 3D electrodes for full-auricle physiological monitoring. As a proof-of-concept, spatiotemporal auricular electrical skin resistance (AESR) mapping was demonstrated for the first time, and human subject-specific AESR distributions were observed. From the data of more than 30 ears (both right and left ears), the auricular region-specific AESR changes after cycling exercise were observed in 98% of the tests and were clustered into 4 groups via machine learning based data analyses. Correlations of AESR with heart rate and blood pressure were also studied. This 3D electronic platform and AESR-based biometrical findings show promising biomedical applications. This article is protected by copyright. All rights reserved.

Huang Qingyun, Wu Cong, Hou Senlin, Yao Kuanming, Sun Hui, Wang Yufan, Chen Yikai, Law Junhui, Yang Mingxiao, Chan Ho-Yin, Roy Vellaisamy A L, Zhao Yuliang, Wang Dong, Song Enming, Yu Xinge, Lao Lixing, Sun Yu, Li Wen Jung


Full-auricle electrophysiological monitoring, graphene-based 3D electrodes, human biometric clusters, machine learning, personalized healthcare sensor