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Cited by 595

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

Eardrum‐Inspired Active Sensors for Self‐Powered Cardiovascular System Characterization and Throat‐Attached Anti‐Interference Voice Recognition

Yang, Jin, Chen, Jun, Su, Yuanjie, Jing, Qingshen, Li, Zhaoling, Yi, Fang, Wen, Xiaonan, Wang, Zhaona, Wang, Zhong Lin·2015·Advanced Materials

Abstract

The first bionic membrane sensor based on triboelectrification is reported for self-powered physiological and behavioral measurements such as local internal body pressures for non-invasive human health assessment. The sensor can also be for self-powered anti-interference throat voice recording and recognition, as well as high-accuracy multimodal biometric authentication, thus potentially expanding the scope of applications in self-powered wearable medical/health monitoring, interactive input/control devices as well as accurate, reliable, and less intrusive biometric authentication systems.

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Crossref · 10.1002/adma.201404794

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Metadata

Authors
Yang, J., Chen, J., Su, Y., Jing, Q., Li, Z., Yi, F., Wen, X., Wang, Z., & Wang, Z. L.
Venue
Advanced Materials
Publisher
Wiley
Published
2015-01-12
Volume
27
Issue
8
Pages
1316-1326
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W2055542322
Cited by
595
References
15
FWCI
22.49
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Eardrum‐Inspired Active Sensors for Self‐Powered Cardiovascular System Characterization and Throat‐Attached Anti‐Interference Voice Recognition. https://app.cochat.ai/papers/10.1002/adma.201404794
The paper
Yang, J., Chen, J., Su, Y., Jing, Q., Li, Z., Yi, F., Wen, X., Wang, Z., & Wang, Z. L. (2015). Eardrum‐Inspired Active Sensors for Self‐Powered Cardiovascular System Characterization and Throat‐Attached Anti‐Interference Voice Recognition. Advanced Materials. https://doi.org/10.1002/adma.201404794

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.