A deep learning-assisted skin-integrated pulse sensing system for reliable pulse monitoring and cardiac function assessment

被引:7
作者
Jia, Huiling [1 ,2 ]
Gao, Yuyu [1 ,2 ]
Zhou, Jingkun [1 ,2 ]
Li, Jian [1 ,2 ]
Yiu, Chun Ki [1 ,2 ]
Park, Wooyoung [1 ]
Yang, Zhihui [3 ,4 ]
Yu, Xinge [1 ,2 ,5 ]
机构
[1] City Univ Hong Kong, Dept Biomed Engn, Hong Kong, Peoples R China
[2] Hong Kong Ctr Cerebro Cardiovasc Hlth Engn, Hong Kong 999077, Peoples R China
[3] Southwest Med Univ, Dept Pathol, Affiliated Hosp, Luzhou 646000, Sichuan, Peoples R China
[4] Pathol Diag Serious Dieases Key Lab LuZhou, Luzhou 646000, Sichuan, Peoples R China
[5] City Univ Hong Kong, Hong Kong Inst Clean Energy, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Continuous pulse monitoring; Epidermal Electronics; Skin -integrated electronics; Wearable sensors; Deep learning; Signal enhancement; EMPIRICAL MODE DECOMPOSITION; ARTERIAL STIFFNESS; PRESSURE SENSOR; SENSITIVITY; RANGE;
D O I
10.1016/j.nanoen.2024.109796
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Long-term pulse monitoring plays a vital role in the prevention and diagnosis of cardiovascular diseases since pulse signals can provide rich characteristics of cardiac conditions. Flexible sensors mounting on the wrist for pulse monitoring have drawn great attention due to the advantages of soft, skin-interfaced and non-invasive features. However, slight wrist movement and transposition of the sensor on skin would dramatically impact the signal quality because of motion artifacts and interfacial properties. Here, we report an intelligent skinintegrated system by combining a sensitive pressure sensor array and a signal enhancement algorithm to provide reliable pulse signal monitoring. The sensors have the advantages of low cost, simple fabrication, reusability and high sensitivity. The multiple sensor channels offer rich information of vital signals, which can facilitate deep learning-based algorithms to denoise and reconstruct pulses more accurately and thus enable precise heart rate monitoring and heart variability assessments. The reported technology suggests a novel approach for pulse waveform detection in static and dynamic conditions, allowing users to more easily achieve reliable pulse monitoring.
引用
收藏
页数:10
相关论文
共 51 条
  • [1] Predicting arterial stiffness from the digital volume pulse waveform
    Alty, Stephen R.
    Angarita-Jaimes, Natalia
    Millasseau, Sandrine C.
    Chowienczyk, Philip J.
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2007, 54 (12) : 2268 - 2275
  • [2] Influence of mental stress on the pulse wave features of photoplethysmograms
    Celka, Patrick
    Charlton, Peter H.
    Farukh, Bushra
    Chowienczyk, Philip
    Alastruey, Jordi
    [J]. HEALTHCARE TECHNOLOGY LETTERS, 2020, 7 (01) : 7 - 12
  • [3] Flexible Piezoelectric-Induced Pressure Sensors for Static Measurements Based on Nanowires/Graphene Heterostructures
    Chen, Zefeng
    Wang, Zhao
    Li, Xinming
    Lin, Yuxuan
    Luo, Ningqi
    Long, Mingzhu
    Zhao, Ni
    Xu, Jian-Bin
    [J]. ACS NANO, 2017, 11 (05) : 4507 - 4513
  • [4] Skin-interfaced biosensors for advanced wireless physiological monitoring in neonatal and pediatric intensive-care units
    Chung, Ha Uk
    Rwei, Alina Y.
    Hourlier-Fargette, Aurelie
    Xu, Shuai
    Lee, KunHyuck
    Dunne, Emma C.
    Xie, Zhaoqian
    Liu, Claire
    Carlini, Andrea
    Kim, Dong Hyun
    Ryu, Dennis
    Kulikova, Elena
    Cao, Jingyue
    Odland, Ian C.
    Fields, Kelsey B.
    Hopkins, Brad
    Banks, Anthony
    Ogle, Christopher
    Grande, Dominic
    Park, Jun Bin
    Kim, Jongwon
    Irie, Masahiro
    Jang, Hokyung
    Lee, JooHee
    Park, Yerim
    Kim, Jungwoo
    Jo, Han Heul
    Hahm, Hyoungjo
    Avila, Raudel
    Xu, Yeshou
    Namkoong, Myeong
    Kwak, Jean Won
    Suen, Emily
    Paulus, Max A.
    Kim, Robin J.
    Parsons, Blake V.
    Human, Kelia A.
    Kim, Seung Sik
    Patel, Manish
    Reuther, William
    Kim, Hyun Soo
    Lee, Sung Hoon
    Leedle, John D.
    Yun, Yeojeong
    Rigali, Sarah
    Son, Taeyoung
    Jung, Inhwa
    Arafa, Hany
    Soundararajan, Vinaya R.
    Ollech, Ayelet
    [J]. NATURE MEDICINE, 2020, 26 (03) : 418 - +
  • [5] Enhancement of self-powered humidity sensing of graphene oxide-based triboelectric nanogenerators by addition of graphene oxide nanoribbons
    Ejehi, Faezeh
    Mohammadpour, Raheleh
    Asadian, Elham
    Fardindoost, Somayeh
    Sasanpour, Pezhman
    [J]. MICROCHIMICA ACTA, 2021, 188 (08)
  • [6] Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals
    Gogna, Anupriya
    Majumdar, Angshul
    Ward, Rabab
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2017, 64 (09) : 2196 - 2205
  • [7] Highly Sensitive Capacitive Pressure Sensors over a Wide Pressure Range Enabled by the Hybrid Responses of a Highly Porous Nanocomposite
    Ha, Kyoung-Ho
    Zhang, Weiyi
    Jang, Hongwoo
    Kang, Seungmin
    Wang, Liu
    Tan, Philip
    Hwang, Hochul
    Lu, Nanshu
    [J]. ADVANCED MATERIALS, 2021, 33 (48)
  • [8] A wearable cardiac ultrasound imager
    Hu, Hongjie
    Huang, Hao
    Li, Mohan
    Gao, Xiaoxiang
    Yin, Lu
    Qi, Ruixiang
    Wu, Ray S.
    Chen, Xiangjun
    Ma, Yuxiang
    Shi, Keren
    Li, Chenghai
    Maus, Timothy M.
    Huang, Brady
    Lu, Chengchangfeng
    Lin, Muyang
    Zhou, Sai
    Lou, Zhiyuan
    Gu, Yue
    Chen, Yimu
    Lei, Yusheng
    Wang, Xinyu
    Wang, Ruotao
    Yue, Wentong
    Yang, Xinyi
    Bian, Yizhou
    Mu, Jing
    Park, Geonho
    Xiang, Shu
    Cai, Shengqiang
    Corey, Paul W.
    Wang, Joseph
    Xu, Sheng
    [J]. NATURE, 2023, 613 (7945) : 667 - 675
  • [9] Pyramid microstructure with single walled carbon nanotubes for flexible and transparent micro-pressure sensor with ultra-high sensitivity
    Huang, Zhenlong
    Gao, Min
    Yan, Zhuocheng
    Pan, Taisong
    Khan, Saeed Ahmed
    Zhang, Yin
    Zhang, Hulin
    Lin, Yuan
    [J]. SENSORS AND ACTUATORS A-PHYSICAL, 2017, 266 : 345 - 351
  • [10] Jain PK, 2016, 2016 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), P6, DOI 10.1109/ICDSP.2016.7868504