Abstract
Estimation of low-back load can be used to determine the assistance to be provided by an actuated back-support exoskeleton. To this end, an EMG-driven muscle model and a regression model can be implemented. The goal of the regression model is to reduce the number of required sensors for load estimation. Both models need to be calibrated. This study aims to find the impacts of limiting calibration data on low-back loading estimation through these models.
Original language | English |
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Title of host publication | Wearable Robotics: Challenges and Trends |
Subtitle of host publication | Proceedings of the 5th International Symposium on Wearable Robotics, WeRob2020, and of WearRAcon Europe 2020, October 13–16, 2020 |
Editors | Juan C. Moreno, Jawad Masood, Urs Schneider, Christophe Maufroy, Jose L. Pons |
Publisher | Springer Science and Business Media Deutschland GmbH |
Pages | 401-405 |
Number of pages | 5 |
ISBN (Electronic) | 9783030695477 |
ISBN (Print) | 9783030695460, 9783030695491 |
DOIs | |
Publication status | Published - 2022 |
Publication series
Name | Biosystems and Biorobotics |
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Volume | 27 |
ISSN (Print) | 2195-3562 |
ISSN (Electronic) | 2195-3570 |
Bibliographical note
Funding Information:Acknowledgements This research was funded by the i-Botics Early Research Program of TNO (the Netherlands Organization for Applied Scientific Research). Additionally, this work was supported by the Dutch Research Council (NWO), program ‘perspectief’ (project P16-05).
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Funding
Acknowledgements This research was funded by the i-Botics Early Research Program of TNO (the Netherlands Organization for Applied Scientific Research). Additionally, this work was supported by the Dutch Research Council (NWO), program ‘perspectief’ (project P16-05).