An Energy-Efficient Flexible Multi-Modal Wireless Sweat Sensing System Based on Laser Induced Graphene

被引:3
|
作者
Feng, Jiuqing [1 ]
Jiang, Yizhou [1 ]
Wang, Kai [1 ]
Li, Jianzheng [1 ]
Zhang, Jialong [1 ]
Tian, Mi [2 ]
Chen, Guoping [1 ]
Hu, Laigui [1 ]
Zhan, Yiqiang [1 ]
Qin, Yajie [1 ]
机构
[1] Fudan Univ, Sch Informat Sci & Technol, Shanghai 200433, Peoples R China
[2] Huashan Hosp, Shanghai 200040, Peoples R China
关键词
laser-induced graphene; lactate enzyme electrode; wearable sensor; sweat sensing system; human motion monitoring; single-walled carbon nanotubes; health monitoring;
D O I
10.3390/s23104818
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Real-time sweat monitoring is vital for athletes in order to reflect their physical conditions, quantify their exercise loads, and evaluate their training results. Therefore, a multi-modal sweat sensing system with a patch-relay-host topology was developed, which consisted of a wireless sensor patch, a wireless data relay, and a host controller. The wireless sensor patch can monitor the lactate, glucose, K+, and Na+ concentrations in real-time. The data is forwarded via a wireless data relay through Near Field Communication (NFC) and Bluetooth Low Energy (BLE) technology and it is finally available on the host controller. Meanwhile, existing enzyme sensors in sweat-based wearable sports monitoring systems have limited sensitivities. To improve their sensitivities, this paper proposes a dual enzyme sensing optimization strategy and demonstrates Laser-Induced Graphene (LIG)-based sweat sensors decorated with Single-Walled Carbon Nanotubes (SWCNT). Manufacturing an entire LIG array takes less than one minute and costs about 0.11 yuan in materials, making it suitable for mass production. The in vitro test result showed sensitivities of 0.53 mu A/mM and 3.9 mu A/mM for lactate and glucose sensing, and 32.5 mV/decade and 33.2 mV/decade for K+ and Na+ sensing, respectively. To demonstrate the ability to characterize personal physical fitness, an ex vivo sweat analysis test was also performed. Overall, the high-sensitivity lactate enzyme sensor based on SWCNT/LIG can meet the requirements of sweat-based wearable sports monitoring systems.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] On the Way to a Multi-Modal Energy-Efficient Route
    Prandtstetter, Matthias
    Straub, Markus
    Puchinger, Jakob
    [J]. 39TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2013), 2013, : 4779 - 4784
  • [2] CAS: Fusing DNN Optimization & Adaptive Sensing for Energy-Efficient Multi-Modal Inference
    Weerakoon Mudiyanselage, Dulanga Kaveesha Weerakoon
    Subbaraju, Vigneshwaran
    Lim, Joo Hwee
    Misra, Archan
    [J]. IEEE Robotics and Automation Letters, 2024, 9 (11) : 10057 - 10064
  • [3] A rail transit simulation system for multi-modal energy-efficient routing applications
    Wang, Jinghui
    Ghanem, Ahmed
    Rakha, Hesham
    Du, Jianhe
    [J]. INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION, 2021, 15 (03) : 187 - 202
  • [4] Energy-Efficient Motion Planning for Multi-Modal Hybrid Locomotion
    Suh, H. J. Terry
    Xiong, Xiaobin
    Singletary, Andrew
    Ames, Aaron D.
    Burdick, Joel W.
    [J]. 2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, : 7027 - 7033
  • [5] An Energy-Efficient Multi-Modal IoT System Leveraging NB-IoT and BLE
    Basu, Subho Shankar
    Haxhibeqiri, Jetmir
    Baert, Mathias
    Moons, Bart
    Hoebeke, Jeroen
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS AND INTELLIGENCE SYSTEM (IOTAIS), 2021, : 30 - 36
  • [6] An Energy-Efficient Flexible Capacitive Pressure Sensing System
    Huang, Yuxuan
    Zhao, Qinghang
    Tang, Xiyuan
    Su, Fang
    Sun, Nan
    Yang, Huazhong
    Liu, Yongpan
    [J]. 2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2020,
  • [7] An Energy-Efficient Quality Adaptive Framework for Multi-Modal Sensor Context Recognition
    Roy, Nirmalya
    Misra, Archan
    Julien, Christine
    Das, Sajal K.
    Biswas, Jit
    [J]. 2011 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS (PERCOM 2011), 2011, : 63 - 73
  • [8] A Highly Energy-Efficient Hyperdimensional Computing Processor for Wearable Multi-modal Classification
    Menon, Alisha
    Sun, Daniel
    Sabouri, Sarina
    Lee, Kyoungtae
    Aristio, Melvin
    Liew, Harrison
    Rabaey, Jan M.
    [J]. 2021 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (IEEE BIOCAS 2021), 2021,
  • [9] A laser-micromachined multi-modal resonating power transducer for wireless sensing systems
    Ching, NNH
    Wong, HY
    Li, WJ
    Leong, PHW
    Wen, ZY
    [J]. SENSORS AND ACTUATORS A-PHYSICAL, 2002, 97-8 : 685 - 690
  • [10] MMRL: A Multi-Modal Reinforcement Learning Technique for Energy-efficient Medical IoT Systems
    Abo-eleneen, Amr
    Mohamed, Amr
    [J]. IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC), 2021, : 2026 - 2031