Ambulatory Cardiovascular Monitoring Via a Machine‐Learning‐Assisted Textile Triboelectric Sensor

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 arteria...

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Veröffentlicht in:	Advanced materials (Weinheim) Jg. 33; H. 41; S. e2104178 - n/a
Hauptverfasser:	Fang, Yunsheng, Zou, Yongjiu, Xu, Jing, Chen, Guorui, Zhou, Yihao, Deng, Weili, Zhao, Xun, Roustaei, Mehrdad, Hsiai, Tzung K., Chen, Jun
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Germany Wiley Subscription Services, Inc 01.10.2021
Schlagworte:	Algorithms Biomonitoring Blood Pressure carbon nanotubes Cardiovascular Diseases - diagnosis Cardiovascular system Data retrieval Diastolic pressure Heart - physiology Humans Internet of Things Machine Learning Materials science Mobile Applications Monitoring, Ambulatory - instrumentation Monitoring, Ambulatory - methods motion artifacts Nanotubes, Carbon - chemistry personalized healthcare Perspiration pulse wave monitoring Response time Sensors Signal-To-Noise Ratio smart textiles Textiles Waveforms Wearable Electronic Devices personalized healthcare pulse wave monitoring smart textiles carbon nanotubes motion artifacts machine learning
ISSN:	0935-9648, 1521-4095, 1521-4095
Online-Zugang:	Volltext
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