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A method for analyzing wearing uncertainties and enhancing motion transmission smoothness in exoskeletons and its applications for a novel passive knee exoskeleton.
- Source :
-
Mechanism & Machine Theory . Jul2024, Vol. 197, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- • A novel passive knee exoskeleton with inclusivity in uncertainties • Propose a method for analysis human-exoskeleton with uncertainties • Propose an indicator to quantify the exoskeletons' motion transmission smoothness • Smoothness indicator consider only configuration variables It is suggested that exoskeletons may present challenges in terms of wearability due to unexpected human-machine interaction forces, usually caused by wearing uncertainties such as wearing slips, geometric differences in individual knees, and variable-axis knee movements. Additionally, the forces caused by drastic changes in velocity during exoskeleton locomotion may also be a contributing factor. To address these issues, this paper introduces a new passive knee exoskeleton and its human-machine wearing parallel (HMWP) research prototype to compensate and accommodate these uncertainties. Subsequently, a response interval analysis method based on Chebyshev functions is proposed to investigate the effect of uncertainties on the HMWP system's kinematic performance. In order to enhance the motion transmission smoothness, a new kinematic performance evaluation indicator is proposed, which considers solely the exoskeleton-configuration parameters. The response interval analysis method and new indicator are applied together in kinematic dimensional synthesis, resulting in significant improvements in the exoskeleton's kinematic performance. Furthermore, a parameter sensitivity analysis is conducted to facilitate more effective improvements to the exoskeleton's comfort. This research can also be used to improve the wearability of other wearable devices. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 0094114X
- Volume :
- 197
- Database :
- Academic Search Index
- Journal :
- Mechanism & Machine Theory
- Publication Type :
- Academic Journal
- Accession number :
- 176923266
- Full Text :
- https://doi.org/10.1016/j.mechmachtheory.2024.105648