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231225s2021 xx |||||o 00| ||eng c |
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|a 10.1002/adma.202104178
|2 doi
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|a pubmed25n1100.xml
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|a eng
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|a Fang, Yunsheng
|e verfasserin
|4 aut
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|a Ambulatory Cardiovascular Monitoring Via a Machine-Learning-Assisted Textile Triboelectric Sensor
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|c 2021
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Completed 07.02.2022
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|a Date Revised 30.08.2024
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a © 2021 Wiley-VCH GmbH.
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|a Wearable bioelectronics for continuous and reliable pulse wave monitoring against body motion and perspiration remains a great challenge and highly desired. Here, a low-cost, lightweight, and mechanically durable textile triboelectric sensor that can convert subtle skin deformation caused by arterial pulsatility into electricity for high-fidelity and continuous pulse waveform monitoring in an ambulatory and sweaty setting is developed. The sensor holds a signal-to-noise ratio of 23.3 dB, a response time of 40 ms, and a sensitivity of 0.21 µA kPa-1 . With the assistance of machine learning algorithms, the textile triboelectric sensor can continuously and precisely measure systolic and diastolic pressure, and the accuracy is validated via a commercial blood pressure cuff at the hospital. Additionally, a customized cellphone application (APP) based on built-in algorithm is developed for one-click health data sharing and data-driven cardiovascular diagnosis. The textile triboelectric sensor enabled wireless biomonitoring system is expected to offer a practical paradigm for continuous and personalized cardiovascular system characterization in the era of the Internet of Things
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|a Journal Article
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|a carbon nanotubes
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|a machine learning
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|a motion artifacts
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|a personalized healthcare
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|a pulse wave monitoring
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|a smart textiles
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|a Nanotubes, Carbon
|2 NLM
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| 700 |
1 |
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|a Zou, Yongjiu
|e verfasserin
|4 aut
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|a Xu, Jing
|e verfasserin
|4 aut
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| 700 |
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|a Chen, Guorui
|e verfasserin
|4 aut
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|a Zhou, Yihao
|e verfasserin
|4 aut
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|a Deng, Weili
|e verfasserin
|4 aut
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| 700 |
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|a Zhao, Xun
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Roustaei, Mehrdad
|e verfasserin
|4 aut
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| 700 |
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|a Hsiai, Tzung K
|e verfasserin
|4 aut
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| 700 |
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|a Chen, Jun
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Advanced materials (Deerfield Beach, Fla.)
|d 1998
|g 33(2021), 41 vom: 20. Okt., Seite e2104178
|w (DE-627)NLM098206397
|x 1521-4095
|7 nnas
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| 773 |
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|g volume:33
|g year:2021
|g number:41
|g day:20
|g month:10
|g pages:e2104178
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|u http://dx.doi.org/10.1002/adma.202104178
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