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 inOpto-Electronic Advances Vol. 8; no. 5; p. 240254
Main Authors Li, Wenbo, Long, Yukun, Yan, Yingyin, Xiao, Kun, Wang, Zhuo, Zheng, Di, Leal-Junior, Arnaldo, Kumar, Santosh, Ortega, Beatriz, Marques, Carlos, Li, Xiaoli, Min, Rui
Format Journal Article
LanguageEnglish
Published Institue of Optics and Electronics, Chinese Academy of Sciences 01.01.2025
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Online AccessGet full text
ISSN2096-4579
DOI10.29026/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.
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
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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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Snippet Personalized health services are of paramount importance for the treatment and prevention of cardiorespiratory diseases, such as hypertension. The assessment...
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StartPage 240254
SubjectTerms all-polymer sensing unit
biometric id
blood pressure
cardiorespiratory diseases
heart rate
personalized health services
respiratory rate
Title Wearable photonic smart wristband for cardiorespiratory function assessment and biometric identification
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