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  5. Enabling the Unconstrained Epidermal Pulse Wave Monitoring via Finger‐Touching

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Article
en
2021

Enabling the Unconstrained Epidermal Pulse Wave Monitoring via Finger‐Touching

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0 Files

en
2021
Vol 31 (32)
Vol. 31
DOI: 10.1002/adfm.202102378

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Xue Wang
Jun Yang
Keyu Meng
+8 more

Abstract

Abstract Unconstrained measurement of physiological signals including electrocardiograph, respiration, and temperature by sensors through incorporation into commonly used objects has sparked a notable revolution in healthcare monitoring. However, unconstrained precision epidermal pulse wave monitoring is rarely reported. Although the current flexible skin‐mounted sensors can capture pulse waves, they lack the capability to perceive tiny pulse pressure in an unconstrained manner. Herein, utilizing thin‐film materials and multilevel microstructure design, an ultrathin and flexible sensor (UFS) with the features of high flexibility, shape‐adaptability, and ultra‐broad‐range high pressure sensitivity is proposed for unconstrained precision pulse wave sensing. Given these compelling features, the UFS is mounted to the surfaces of commonly used objects and successfully detects the fingertip pulse wave even under an ultra‐broad‐range finger‐touching force. Key cardiovascular parameters are also extracted from the acquired fingertip pulse wave accurately. Furthermore, a proof‐of‐concept healthcare system, by combining the UFS and flexible devices (for example, flexible phones or E‐newspapers) is demonstrated, offering a great advancement in developing an all‐in‐one system for IoT‐based bio‐health monitoring at all times and places.

How to cite this publication

Xue Wang, Jun Yang, Keyu Meng, Qiang He, Gaoqiang Zhang, Zhihao Zhou, Xulong Tan, Zhiping Feng, Chenchen Sun, Jin Yang, Zhong Lin Wang (2021). Enabling the Unconstrained Epidermal Pulse Wave Monitoring via Finger‐Touching. , 31(32), DOI: https://doi.org/10.1002/adfm.202102378.

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Publication Details

Type

Article

Year

2021

Authors

11

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1002/adfm.202102378

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