“Payload estimation using forcemyography sensors for control of upper-body exoskeleton in load carrying assistance”

Authors: Muhammad R. U. Islam and Shaoping Bai,
Affiliation: Aalborg University
Reference: 2019, Vol 40, No 4, pp. 189-198.

Keywords: Forcemyography, payload estimation, assistive exoskeleton, physical human-robot interaction

Abstract: In robotic assistive devices, the determination of required assistance is vital for proper functioning of assistive control. This paper presents a novel solution to measure conveniently and accurately carried payload in order to estimate the required assistance level. The payload is estimated using upper arm forcemyography (FMG) through a sensor band made of force sensitive resistors. The sensor band is worn on the upper arm and is able to measure the change of normal force applied due to muscle contraction. The readings of the sensor band are processed using support vector machine (SVM) regression technique to estimate the payload. The developed method was tested on human subjects, carrying a payload. Experiments were further conducted on an upper-body exoskeleton to provide the required assistance. The results show that the developed method is able to estimate the load carrying status, which can be used in exoskeleton control to provide effectively physical assistance needed.

PDF PDF (2945 Kb)        DOI: 10.4173/mic.2019.4.1

DOI forward links to this article:
[1] Muhammad Ahsan Gull, Shaoping Bai and Thomas Bak (2020), doi:10.3390/robotics9010016
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BibTeX:
@article{MIC-2019-4-1,
  title={{Payload estimation using forcemyography sensors for control of upper-body exoskeleton in load carrying assistance}},
  author={Islam, Muhammad R. U. and Bai, Shaoping},
  journal={Modeling, Identification and Control},
  volume={40},
  number={4},
  pages={189--198},
  year={2019},
  doi={10.4173/mic.2019.4.1},
  publisher={Norwegian Society of Automatic Control}
};