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Research Article

Microcavity assisted graphene pressure sensor for single-vessel local blood pressure monitoring

Jinan Luo1,2Jingzhi Wu1,2Xiaopeng Zheng1,2Haoran Xiong1,2Lin Lin1,2Chang Liu1,2Haidong Liu1,2Hao Tang1,2Houfang Liu3Fei Han4Zhiyuan Liu4Zhikang Deng1,2Chuting Liu1,2Tianrui Cui3Bo Li5( )Tian-Ling Ren3 ( )Jianhua Zhou1,2( )Yancong Qiao1,2( )
School of Biomedical Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou 510275, China
School of Integrated Circuits and Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China
CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen 518055, China
Cardiovascular surgery, Seventh affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China
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Abstract

Dynamic monitoring of blood pressure (BP) is beneficial to obtain comprehensive cardiovascular information of patients throughout the day. However, the clinical BP measurement method relies on wearing a bulky cuff, which limits the long-term monitoring and control of BP. In this work, a microcavity assisted graphene pressure sensor (MAGPS) for single-vessel local BP monitoring is designed to replace the cuff. The microcavity structure increases the working range of the sensor by gas pressure buffering. Therefore, the MAGPS achieves a wide linear response of 0–1050 kPa and sensitivity of 15.4 kPa−1. The large working range and the microcavity structure enable the sensor to fully meet the requirements of BP detection at the radial artery. A database of 228 BP data (60-s data fragment detected by MAGPS) and 11,804 pulse waves from 9 healthy subjects and 5 hypertensive subjects is built. Finally, the BP was detected and analyzed automatically by combining MAGPS and a two-stage convolutional neural network algorithm. For the BP detection method at local radial artery, the first stage algorithm first determines whether the subject has hypertension by the pulse wave. Then, the second stage algorithm can diagnose systolic and diastolic BP with the accuracy of 93.5% and 97.8% within a 10 mmHg error, respectively. This work demonstrates a new BP detection method based on single vessel, which greatly promotes the efficiency of BP detection.

Graphical Abstract

A microcavity assisted graphene pressure sensor is developed capable of replacing traditional cuffs, specifically designed for local radial artery blood pressure monitoring. The large amount of clinical data, coupled with innovative detection algorithm, ensures precise and accurate blood pressure monitoring.

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Nano Research
Pages 10058-10068

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Cite this article:
Luo J, Wu J, Zheng X, et al. Microcavity assisted graphene pressure sensor for single-vessel local blood pressure monitoring. Nano Research, 2024, 17(11): 10058-10068. https://doi.org/10.1007/s12274-024-6969-7
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Received: 20 June 2024
Revised: 30 July 2024
Accepted: 13 August 2024
Published: 11 September 2024
© Tsinghua University Press 2024