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.
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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).
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Tabasi, A. et al. (2022). Calibrating an EMG-Driven Muscle Model and a Regression Model to Estimate Moments Generated Actively by Back Muscles for Controlling an Actuated Exoskeleton with Limited Data. In: Moreno, J.C., Masood, J., Schneider, U., Maufroy, C., Pons, J.L. (eds) Wearable Robotics: Challenges and Trends. WeRob 2020. Biosystems & Biorobotics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-030-69547-7_65
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DOI: https://doi.org/10.1007/978-3-030-69547-7_65
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