A wearable comprehensive data sampling system for gait analysis

被引:5
|
作者
Fang Z. [1 ]
Yang Z. [1 ]
Wang Q. [1 ]
Wang C. [1 ]
Chen S. [1 ]
机构
[1] School of Aerospace Engineering, Xiamen University, Xiamen
基金
中国国家自然科学基金;
关键词
embedded system; Gait analysis; rehabilitation; signal sampling; wearable device;
D O I
10.1080/03091902.2018.1430184
中图分类号
学科分类号
摘要
Gait analysis is important for lower limb movement evaluation and rehabilitation research. More and more laboratories focus on it. Researchers need biomechanical data sampling equipment to obtain original signals for their analysis, sometimes even need kinds of signals for data fusion processing. But, the market supply of relative products is very limited. Moreover, one device acquires only one kind of signal, and needs computer as the control centre. So, there are two problems: moving range limitation, and synchronisation in data fusion processing. Most researchers plan experiments only indoors, and sometimes need to do secondary development for data fusion synchronisation. This article represents a compact-embedded system for lower limb biomechanical signals acquisition. Four kinds of signals are collected: foot plantar pressure, inertial measurement, laser distance sensing and electromyography. The embedded circuit is powered by a lithium battery. All the signals are synchronised by the embedded clock, and stored in secure digital memory card for offline analysis. It is convenient to plan experiments in all kinds of terrains indoors or outdoors. It is unique for its wearable, low power and comprehensive characters. Experimental results show that it is a useful tool for gait analysing research. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
引用
收藏
页码:335 / 343
页数:8
相关论文
共 50 条
  • [41] Wearable-Gait-Analysis-Based Activity Recognition: A Review
    Ansah, Stella
    Chen, Diliang
    INTERNATIONAL JOURNAL ON SMART SENSING AND INTELLIGENT SYSTEMS, 2022, 15 (01):
  • [42] Gait Analysis using Wearable Sensors with Multiple Sclerosis Patients
    Jurisic Skevin, Aleksandra
    Filipovic, Nenad
    Mijailovic, Nikola
    Divjak, Ana
    Nurkovic, Jasmin
    Radakovic, Radivoje
    Gacic, Marija
    Grbovic, Vesna
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2018, 25 : 339 - 342
  • [43] Validation of an Ear-Worn Wearable Gait Analysis Device
    Jung, Chang Keun
    Kim, Jinkyuk
    Rhim, Hye Chang
    SENSORS, 2023, 23 (03)
  • [44] Gait analysis using gravitational acceleration measured by wearable sensors
    Takeda, Ryo
    Tadano, Shigeru
    Todoh, Masahiro
    Morikawa, Manabu
    Nakayasu, Minoru
    Yoshinari, Satoshi
    JOURNAL OF BIOMECHANICS, 2009, 42 (03) : 223 - 233
  • [45] Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications
    Muro-de-la-Herran, Alvaro
    Garcia-Zapirain, Begonya
    Mendez-Zorrilla, Amaia
    SENSORS, 2014, 14 (02): : 3362 - 3394
  • [46] Reliability of the novel gait analysis system RehaWatch
    Schwesig, Rene
    Kauert, Ralf
    Wust, Sylvia
    Becker, Stephan
    Leuchte, Siegfried
    BIOMEDIZINISCHE TECHNIK, 2010, 55 (02): : 109 - 115
  • [47] A Compact Low Cost Wearable Sensor System for Quantitative Gait Measurement
    Tan, Ming-Gui
    Leong, Cheng-Boon
    Ho, Jee-Hou
    Goh, Hui-Ting
    Ng, Hoon-Kiat
    ADVANCED DEVELOPMENT IN INDUSTRY AND APPLIED MECHANICS, 2014, 627 : 212 - +
  • [48] A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics
    Farago, Paul
    Grama, Lacrimioara
    Farago, Monica-Adriana
    Hintea, Sorin
    APPLIED SCIENCES-BASEL, 2021, 11 (01): : 1 - 29
  • [49] Achieving ecological validity in mobility assessment: Validating a wearable sensor technology for comprehensive gait assessment
    Mohammadi, Mostafa
    Singh, Navrag B.
    Hitz, Marco
    Orter, Stefan
    Taylor, William R.
    Frigo, Carlo
    2017 IEEE 3RD INTERNATIONAL FORUM ON RESEARCH AND TECHNOLOGIES FOR SOCIETY AND INDUSTRY (RTSI), 2017, : 431 - 435
  • [50] A Wearable Magneto-Inertial System for Gait Analysis (H-Gait): Validation on Normal Weight and Overweight/Obese Young Healthy Adults
    Agostini, Valentina
    Gastaldi, Laura
    Rosso, Valeria
    Knaflitz, Marco
    Tadano, Shigeru
    SENSORS, 2017, 17 (10)