A self-powered human gait monitoring sensor for osteoarthritis prevention

被引:1
|
作者
Ding, Yunyi [1 ]
Luo, Yichen [2 ]
Zhou, Xue [2 ]
Zhang, Shaojie [3 ,4 ]
Zhang, Bin [2 ]
Li, Yayu [3 ,4 ]
机构
[1] Zhejiang Chinese Med Univ, Hangzhou TCM Hosp, Dept Nephrol, Hangzhou 10053, Peoples R China
[2] Zhejiang Univ, State Key Lab Fluid Power & Mech Syst, Hangzhou 310058, Peoples R China
[3] Zhejiang Univ, Sch Mech Engn, Hangzhou 310058, Peoples R China
[4] Hangzhou TCM Hosp, Dept Nephrol, Hangzhou 310007, Peoples R China
关键词
OUTPUT TRIBOELECTRIC NANOGENERATOR; HARVESTING ENERGY; PAPER;
D O I
10.1063/5.0161127
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
Recently, wearable sensors for human motion posture and medical diagnosis have received widespread attention. However, most wearable sensors rely on a power supply, and their preparation technology still faces limitations. Here, we used eyebrow powder to fabricate a triboelectric nanogenerator (E-TENG) for bio-mechanical energy harvesting and gait monitoring of patients with osteoarthritis. Under a maximum separation distance (5 mm) and a maximum motion frequency (6 Hz), the E-TENG device can attain a open-circuit voltage (V-oc) of 169 V and a short-circuit current (I-sc) of 5.5 mu A. Meanwhile, the maximum output power of the E-TENG can arrive at 175 mu W (load resistance: 20 M Omega). The E-TENG can detect human gait patterns (walking, running, and jumping), finger motion, and elbow joint movements. Further research has shown that the E-TENG can be used for gait recognition and monitoring in patients with osteoarthritis, providing reference data for osteoarthritis prevention and treatment. This research can promote the application of TENG devices based on cosmetic materials in medical diagnosis and adjuvant treatment.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] A Self-Powered Wireless Temperature Sensor Platform for Foot Ulceration Monitoring
    Duah, Joseph Agyemang
    Lee, Kye-Shin
    Kim, Byung-Gyu
    Sensors, 2024, 24 (20)
  • [32] Fibrous self-powered sensor with high stretchability for physiological information monitoring
    Fu, Kun
    Zhou, Jie
    Wu, Hanguang
    Su, Zhiqiang
    NANO ENERGY, 2021, 88 (88)
  • [33] Wireless Self-powered Plant Health-monitoring Sensor System
    Tanaka, Ami
    Ishihara, Toyoshi
    Utsunomiya, Fumiyasu
    Douseki, Takakuni
    2012 IEEE SENSORS PROCEEDINGS, 2012, : 311 - 314
  • [34] Self-Powered, Ultrathin, and Transparent Printed Pressure Sensor for Biosignal Monitoring
    Montero, Karem Lozano
    Laurila, Mika-Matti
    Peltokangas, Mikko
    Haapala, Mira
    Verho, Jarmo
    Oksala, Niku
    Vehkaoja, Antti
    Mantysalo, Matti
    ACS APPLIED ELECTRONIC MATERIALS, 2021, 3 (10) : 4362 - 4375
  • [35] Design of Self-powered Environment Monitoring Sensor Based on TEG and TENG
    Liu, Jianhao
    Liu, Changxin
    Zhao, Cong
    Li, Huaan
    Qu, Guanghao
    Mao, Zhuofan
    Zhou, Zhenghui
    2021 IEEE 16TH INTERNATIONAL CONFERENCE ON NANO/MICRO ENGINEERED AND MOLECULAR SYSTEMS (NEMS), 2021, : 749 - 753
  • [36] Self-Powered Acoustic Sensor Based on Triboelectric Nanogenerator for Smart Monitoring
    Yingzhe Li
    Chaoran Liu
    Sanshan Hu
    Peng Sun
    Lingxing Fang
    Serguei Lazarouk
    Vladimir Labunov
    Weihuang Yang
    Dujuan Li
    Kai Fan
    Gaofeng Wang
    Linxi Dong
    Lufeng Che
    Acoustics Australia, 2022, 50 : 383 - 391
  • [37] Magnetostrictive vibration sensor for a self-powered structural health monitoring system
    Koganezawa, Shinji
    Ishii, Tomotake
    Tani, Hiroshi
    Lu, Renguo
    Tagawa, Norio
    JOURNAL OF ADVANCED MECHANICAL DESIGN SYSTEMS AND MANUFACTURING, 2022, 16 (01):
  • [38] A Self-Powered Flexible Sensor for Speed Skating Land Technology Monitoring
    Deng, Xuefeng
    Fu, Yanmin
    Gao, Jun
    JOURNAL OF NANOELECTRONICS AND OPTOELECTRONICS, 2022, 17 (04) : 674 - 679
  • [39] New sensor technology enables self-powered, wireless structural monitoring
    Kalantari, Mehdi
    MATERIALS PERFORMANCE, 2011, 50 (11) : 20 - 21
  • [40] Self-Powered ZigBee Wireless Sensor Nodes for Railway Condition Monitoring
    Gao, Mingyuan
    Wang, Ping
    Wang, Yifeng
    Yao, Lingkan
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2018, 19 (03) : 900 - 909