A Wearable Physiological Detection System to Monitor Blink From Faint Motion Artifacts by Machine Learning Method-Reference-Cited by-同舟云学术

A Wearable Physiological Detection System to Monitor Blink From Faint Motion Artifacts by Machine Learning Method

Published:2023-11-01 Issue:21 Volume:23 Page:26126-26135
ISSN:1530-437X
Container-title:IEEE Sensors Journal
language:
Short-container-title:IEEE Sensors J.

Author:

Chen Yeshen¹,Feng Yuan²,Chen Zibin¹,Zhou Yuanzhi¹,Yang Yihan¹,Ji Quanyu¹,Xu Weiliang¹,Zhou Guoyuan¹,Gao Tianyu¹,Li Xinming¹^ORCID

Affiliation:

1. Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices, School of Information and Optoelectronic Science and Engineering, South China Normal University, Guangzhou, People’s Republic of China

2. Department of Electrical and Computer Engineering, National University of Singapore, Queenstown, Singapore

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices

South China Normal University startup fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7361/10302460/10250206.pdf?arnumber=10250206

Reference45 articles.

1. The use of photoplethysmography for assessing hypertension

2. Top-Down Induction of Decision Trees Classifiers—A Survey

3. PPG-Based Smart Wearable Device With Energy-Efficient Computing for Mobile Health-Care Applications

4. Toward all-day wearable health monitoring: An ultralow-power, reflective organic pulse oximetry sensing patch

5. Monitoring of the central blood pressure waveform via a conformal ultrasonic device

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