TY - JOUR
T1 - Mapping of Spatiotemporal Auricular Electrophysiological Signals Reveals Human Biometric Clusters
AU - Huang, Qingyun
AU - Wu, Cong
AU - Hou, Senlin
AU - Yao, Kuanming
AU - Sun, Hui
AU - Wang, Yufan
AU - Chen, Yikai
AU - Law, Junhui
AU - Yang, Mingxiao
AU - Chan, Ho yin
AU - Roy, Vellaisamy A.L.
AU - Zhao, Yuliang
AU - Wang, Dong
AU - Song, Enming
AU - Yu, Xinge
AU - Lao, Lixing
AU - Sun, Yu
AU - Li, Wen Jung
N1 - Publisher Copyright:
© 2022 The Authors. Advanced Healthcare Materials published by Wiley-VCH GmbH.
PY - 2022/12/7
Y1 - 2022/12/7
N2 - 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.
AB - 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.
KW - full-auricle electrophysiological monitoring
KW - graphene-based 3D electrodes
KW - human biometric clusters
KW - machine learning
KW - personalized healthcare sensors
UR - http://www.scopus.com/inward/record.url?scp=85141407113&partnerID=8YFLogxK
U2 - 10.1002/adhm.202201404
DO - 10.1002/adhm.202201404
M3 - Article
C2 - 36217916
AN - SCOPUS:85141407113
SN - 2192-2640
VL - 11
JO - Advanced Healthcare Materials
JF - Advanced Healthcare Materials
IS - 23
M1 - 2201404
ER -