Design of a Sensor Insole for Gait Analysis

  • Kamen Ivanov
  • Zhanyong Mei
  • Ludwig Lubich
  • Nan Guo
  • Deng Xile
  • Zhichun Zhao
  • Olatunji Mumini Omisore
  • Derek Ho
  • Lei WangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11743)


There is an increasing interest in the application of instrumented insoles in sport and medicine to obtain gait information during activities of daily living. Despite the high number of research works dedicated to smart insole design, there is a lack of discussions on strategies to optimize the design of the force sensing electronic acquisition module. Such strategies are needed to achieve a small form factor while maintaining reliable kinetic data acquisition. In the present work, we describe our implementation of a smart insole and demonstrate channel multiplexing to optimize electronic component count. We discuss the details of the analog part, including the analog-to-digital conversion, optimal sampling frequency selection, and methods to reduce errors and influences of component imperfections. We demonstrated a complete framework for insole signal processing developed in Python. We used the insole prototype to collect data from twenty volunteers and implemented a basic algorithm for person recognition. As a result, we achieved a reasonable classification accuracy of 98.75%.


Smart insole Channel multiplexing GaitPy Person recognition Gait analysis 



This project was supported in parts by the Key Project 2017GZ0304 of the Science and Technology Department of Sichuan province, Key Program of Joint Funds of the National Natural Science Foundation of China, grant U1505251, The Enhancement Project for Shenzhen Biomedical Electronics Technology Public Service Platform, and the Outstanding Youth Innovation Research Fund of SIAT-CAS, grant Y8G0381001.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kamen Ivanov
    • 1
    • 2
  • Zhanyong Mei
    • 3
  • Ludwig Lubich
    • 4
  • Nan Guo
    • 5
  • Deng Xile
    • 6
  • Zhichun Zhao
    • 7
  • Olatunji Mumini Omisore
    • 1
  • Derek Ho
    • 5
  • Lei Wang
    • 1
    Email author
  1. 1.Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenChina
  2. 2.Shenzhen College of Advanced TechnologyUniversity of Chinese Academy of SciencesShenzhenChina
  3. 3.College of Cyber SecurityChengdu University of TechnologyChengduChina
  4. 4.Faculty of TelecommunicationsTechnical University of SofiaSofiaBulgaria
  5. 5.Department of Materials Science and EngineeringCity University of Hong KongKowloonHong Kong
  6. 6.Xi’an Polytechnic UniversityShaanxiChina
  7. 7.College of Information Science and TechnologyChengdu University of TechnologyChengduChina

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