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Human-in-the-loop Bayesian optimization of a tethered soft exosuit for assisting hip extension
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Web of Science
Cited 2 time in Scopus
- Authors
- Issue Date
- 2019
- Publisher
- Springer International Publishing
- Citation
- Biosystems and Biorobotics, Vol.22, pp.142-146
- Abstract
- Advances in wearable devices have led to an increased need to develop sophisticated and individualized control strategies. To address this problem, several researchers have begun exploring human-in-the-loop optimization methods that automatically adjust control parameters in a wearable device using real-time physiological measurements. A common physiological measurement, metabolic cost, poses significant experimental challenges due to its long measurement times and low signal-to-noise ratio. This study addresses the challenges by using Bayesian optimization—an algorithm well-suited to optimizing noisy performance signals with very limited data—to perform control adaptation online. When applied to a soft exosuit designed to provide hip assistance, optimized control parameters were found in 24 min with a significant reduction in metabolic cost. These results suggest that this method could have a practical impact on improving the performance of wearable robotic devices.
- ISSN
- 2195-3562
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Related Researcher
- College of Engineering
- Department of Electrical and Computer Engineering
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