Literature DB >> 34072553

Design of a Plantar Pressure Insole Measuring System Based on Modular Photoelectric Pressure Sensor Unit.

Bin Ren1, Jianwei Liu1.   

Abstract

Accurately perceiving and predicting the parameters related to human walking is very important for man-machine coupled cooperative control systems such as exoskeletons and power prostheses. Plantar pressure data is rich in human gait and posture information and is an essential source of reference information as the input of the exoskeleton control system. Therefore, the proper design of the pressure sensing insole and validation is a big challenge considering the requirements such as convenience, reliability, no interference and so on. In this research, we developed a low-cost modular sensing unit based on the principle of photoelectric sensing and designed a plantar pressure sensing insole to achieve the purpose of sensing human walking gait and posture information. On the one hand, the sensor unit is made of economy-friendly commercial flexible circuits and elastic silicone, and the mechanical and electrical characteristics of the modular sensor unit are evaluated by a self-developed pressure-related calibration system. The calibration results show that the modular sensor based on the photoelectric sensing principle has fast response and negligible hysteresis. On the other hand, we analyzed the area where the plantar pressure is densely distributed. One benefit of the modular sensing unit design is that it is rather convenient to fabricate different insole solutions, so we fabricated and compared several pressure-sensitive insole solutions in this preliminary study. During the dynamic locomotion experiments of wearing the pressure-sensing insole, the time series signal of each sensor unit was collected and analyzed. The results show that the pressure sensing insole based on the photoelectric effect can sense the distribution of the plantar pressure by capturing the deformation of the insole caused by the foot contact during locomotion, and provide reliable gait information for wearable applications.

Entities:  

Keywords:  gait parameters; modular sensing unit; optical sensing principle; plantar pressure measurement

Mesh:

Year:  2021        PMID: 34072553     DOI: 10.3390/s21113780

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  6 in total

1.  Ground reaction forces in distance running.

Authors:  P R Cavanagh; M A Lafortune
Journal:  J Biomech       Date:  1980       Impact factor: 2.712

2.  Foot plantar pressure measurement system: a review.

Authors:  Abdul Hadi Abdul Razak; Aladin Zayegh; Rezaul K Begg; Yufridin Wahab
Journal:  Sensors (Basel)       Date:  2012-07-23       Impact factor: 3.576

3.  A wireless flexible sensorized insole for gait analysis.

Authors:  Simona Crea; Marco Donati; Stefano Marco Maria De Rossi; Calogero Maria Oddo; Nicola Vitiello
Journal:  Sensors (Basel)       Date:  2014-01-09       Impact factor: 3.576

4.  A Systematic Approach to the Design and Characterization of A Smart Insole for Detecting Vertical Ground Reaction Force (vGRF) in Gait Analysis.

Authors:  Anas M Tahir; Muhammad E H Chowdhury; Amith Khandakar; Sara Al-Hamouz; Merna Abdalla; Sara Awadallah; Mamun Bin Ibne Reaz; Nasser Al-Emadi
Journal:  Sensors (Basel)       Date:  2020-02-11       Impact factor: 3.576

5.  A flexible sensor technology for the distributed measurement of interaction pressure.

Authors:  Marco Donati; Nicola Vitiello; Stefano Marco Maria De Rossi; Tommaso Lenzi; Simona Crea; Alessandro Persichetti; Francesco Giovacchini; Bram Koopman; Janez Podobnik; Marko Munih; Maria Chiara Carrozza
Journal:  Sensors (Basel)       Date:  2013-01-15       Impact factor: 3.576

6.  Pressure-Sensitive Insoles for Real-Time Gait-Related Applications.

Authors:  Elena Martini; Tommaso Fiumalbi; Filippo Dell'Agnello; Zoran Ivanić; Marko Munih; Nicola Vitiello; Simona Crea
Journal:  Sensors (Basel)       Date:  2020-03-06       Impact factor: 3.576

  6 in total
  2 in total

1.  Intelligent Sensors for Human Motion Analysis.

Authors:  Tomasz Krzeszowski; Adam Switonski; Michal Kepski; Carlos T Calafate
Journal:  Sensors (Basel)       Date:  2022-06-30       Impact factor: 3.847

2.  AI Prediction of Brain Signals for Human Gait Using BCI Device and FBG Based Sensorial Platform for Plantar Pressure Measurements.

Authors:  Asad Muhammad Butt; Hassan Alsaffar; Muhannad Alshareef; Khurram Karim Qureshi
Journal:  Sensors (Basel)       Date:  2022-04-18       Impact factor: 3.847

  2 in total

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