The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Human-in-the-loop optimization of exoskeleton assistance during walking
Abstract
Optimum human input: Exoskeletons can be used to augment human abilities—for example, to lift very heavy loads or to provide greater endurance. For each user, though, a device will need to be adjusted for optimum effect, which can be time-consuming. Zhang et al. show that the human can be included in the optimization process, with real-time adaptation of an ankle exoskeleton (see the Perspective by Malcolm et al. ). By using indirect calorimetry to measure metabolic rates, the authors were able to adjust the torque provided by the device while users were walking, running, and carrying a load. Science , this issue p. 1280 ; see also p. 1230
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Cites
Completely Derandomized Self-Adaptation in Evolution Strategies
Hansen, N., & Ostermeier, A. (2001) · Evolutionary Computation · doi:10.1162/106365601750190398 · Cited by 4,397
Huang, H., Zhang, F., Hargrove, L. J., Dou, Z., Rogers, D. R., & Englehart, K. B. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2161671 · Cited by 542
Altered Running Economy Directly Translates to Altered Distance-Running Performance
HOOGKAMER, W., KIPP, S., SPIERING, B. A., & KRAM, R. (2016) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001012 · Cited by 230
Neurocognitive barriers to the embodiment of technology
Makin, T. R., de Vignemont, F., & Faisal, A. A. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-016-0014 · Cited by 165
Cited by
A survey of human-in-the-loop for machine learning
Wu, X., Xiao, L., Sun, Y., Zhang, J., Ma, T., & He, L. (2022) · Future Generation Computer Systems · doi:10.1016/j.future.2022.05.014 · Cited by 800
Self-citationReducing the metabolic rate of walking and running with a versatile, portable exosuit
Kim, J., Lee, G., Heimgartner, R., Arumukhom Revi, D., Karavas, N., Nathanson, D., Galiana, I., Eckert-Erdheim, A., Murphy, P., Perry, D., et al. (2019) · Science · doi:10.1126/science.aav7536 · Cited by 482
A review of current state-of-the-art control methods for lower-limb powered prostheses
Gehlhar, R., Tucker, M., Young, A. J., & Ames, A. D. (2023) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2023.03.003 · Cited by 131
Task-agnostic exoskeleton control via biological joint moment estimation
Molinaro, D. D., Scherpereel, K. L., Schonhaut, E. B., Evangelopoulos, G., Shepherd, M. K., & Young, A. J. (2024) · Nature · doi:10.1038/s41586-024-08157-7 · Cited by 107
Bio-inspired upper limb soft exoskeleton to reduce stroke-induced complications
Li, N., Yang, T., Yu, P., Chang, J., Zhao, L., Zhao, X., Elhajj, I. H., Xi, N., & Liu, L. (2018) · Bioinspiration & Biomimetics · doi:10.1088/1748-3190/aad8d4 · Cited by 92
Metadata
- Authors
- Zhang, J., Fiers, P., Witte, K. A., Jackson, R. W., Poggensee, K. L., Atkeson, C. G., & Collins, S. H.
- Venue
- Science
- Published
- 2017-06-23
- Volume
- 356
- Issue
- 6344
- Pages
- 1280-1284
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2700163520
- Cited by
- 1,011
- References
- 4
- FWCI
- 28.28
- Type
- journal article
- Language
- en
- Open access
- closed
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