Wearable photonic smart wristband for cardiorespiratory function assessment and biometric identification
Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases, such as hypertension. The assessment of cardiorespiratory function and biometric identification (ID) is crucial for the effectiveness of such personalized health services. To effe...
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Published in | Opto-Electronic Advances Vol. 8; no. 5; p. 240254 |
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Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Institue of Optics and Electronics, Chinese Academy of Sciences
01.01.2025
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Subjects | |
Online Access | Get full text |
ISSN | 2096-4579 |
DOI | 10.29026/oea.2025.240254 |
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Abstract | Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases, such as hypertension. The assessment of cardiorespiratory function and biometric identification (ID) is crucial for the effectiveness of such personalized health services. To effectively and accurately monitor pulse wave signals, thus achieving the assessment of cardiorespiratory function, a wearable photonic smart wristband based on an all-polymer sensing unit (All-PSU) is proposed. The smart wristband enables the assessment of cardiorespiratory function by continuously monitoring respiratory rate (RR), heart rate (HR), and blood pressure (BP). Furthermore, it can be utilized for biometric ID purposes. Through the analysis of pulse wave signals using power spectral density (PSD), accurate monitoring of RR and HR is achieved. Additionally, utilizing peak detection algorithms for feature extraction from pulse signals and subsequently employing a variety of machine learning methods, accurate BP monitoring and biometric ID have been realized. For biometric ID, the accuracy rate is 98.55%. Aiming to monitor RR, HR, BP, and ID, our solution demonstrates advantages in integration, functionality, and monitoring precision. These enhancements may contribute to the development of personalized health services aimed at the treatment and prevention of cardiorespiratory diseases. |
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AbstractList | Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases, such as hypertension. The assessment of cardiorespiratory function and biometric identification (ID) is crucial for the effectiveness of such personalized health services. To effectively and accurately monitor pulse wave signals, thus achieving the assessment of cardiorespiratory function, a wearable photonic smart wristband based on an all-polymer sensing unit (All-PSU) is proposed. The smart wristband enables the assessment of cardiorespiratory function by continuously monitoring respiratory rate (RR), heart rate (HR), and blood pressure (BP). Furthermore, it can be utilized for biometric ID purposes. Through the analysis of pulse wave signals using power spectral density (PSD), accurate monitoring of RR and HR is achieved. Additionally, utilizing peak detection algorithms for feature extraction from pulse signals and subsequently employing a variety of machine learning methods, accurate BP monitoring and biometric ID have been realized. For biometric ID, the accuracy rate is 98.55%. Aiming to monitor RR, HR, BP, and ID, our solution demonstrates advantages in integration, functionality, and monitoring precision. These enhancements may contribute to the development of personalized health services aimed at the treatment and prevention of cardiorespiratory diseases. |
Author | Long, Yukun Xiao, Kun Marques, Carlos Wang, Zhuo Leal-Junior, Arnaldo Li, Xiaoli Min, Rui Zheng, Di Ortega, Beatriz Yan, Yingyin Kumar, Santosh Li, Wenbo |
Author_xml | – sequence: 1 givenname: Wenbo surname: Li fullname: Li, Wenbo – sequence: 2 givenname: Yukun surname: Long fullname: Long, Yukun – sequence: 3 givenname: Yingyin surname: Yan fullname: Yan, Yingyin – sequence: 4 givenname: Kun surname: Xiao fullname: Xiao, Kun – sequence: 5 givenname: Zhuo surname: Wang fullname: Wang, Zhuo – sequence: 6 givenname: Di surname: Zheng fullname: Zheng, Di – sequence: 7 givenname: Arnaldo surname: Leal-Junior fullname: Leal-Junior, Arnaldo – sequence: 8 givenname: Santosh surname: Kumar fullname: Kumar, Santosh – sequence: 9 givenname: Beatriz surname: Ortega fullname: Ortega, Beatriz – sequence: 10 givenname: Carlos surname: Marques fullname: Marques, Carlos – sequence: 11 givenname: Xiaoli surname: Li fullname: Li, Xiaoli – sequence: 12 givenname: Rui surname: Min fullname: Min, Rui |
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CorporateAuthor | Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Zhuhai 519087, China Center for Information Photonics and Communications, School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China Department of Physics, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai 519087, China CICECO-Aveiro Institute of Materials, Physics Department, University of Aveiro, Aveiro 3810-193, Portugal Graduate Program in Electrical Engineering, Federal University of Espírito Santo, Fernando Ferrari Avenue, Vitoria 29075-910, Brazil Department of Physics, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic Department of Psychology, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai 519087, China Department of Cybernetics and Biomedical Engineering, VSB—Technical University of Ostrava, Ostrava, Czech Republic ITEAM Research Institute, Universitat Politècnica de València, Valencia 46022, Spain Faculty of Psychology, Beijing Normal University, Beijing 100875, China Centre of Excellence for Nanotechnology, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh-522302, India |
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Title | Wearable photonic smart wristband for cardiorespiratory function assessment and biometric identification |
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