生物识别
心肺适能
可穿戴计算机
鉴定(生物学)
计算机科学
可穿戴技术
功能(生物学)
人机交互
人工智能
嵌入式系统
医学
生物
物理疗法
植物
进化生物学
作者
Wenbo Li,Yukun Long,Ying Yan,Kun Xiao,Zhuo Wang,Di Zheng,Arnaldo Leal‐Junior,Santosh Kumar,B. Ortega,Carlos Marques,Xiaoli Li,Rui Min
标识
DOI:10.29026/oea.2025.240254
摘要
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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