Neural Multimodal Control for Versatile Motion Generation and Continuous Transitions of a Lower-Limb Exoskeleton
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47272-5_26
Reference12 articles.
1. Baud, R., Manzoori, A.R., Ijspeert, A., Bouri, M.: Review of control strategies for lower-limb exoskeletons to assist gait. J. Neuro Eng. Rehabil. 18(1), 119 (2021)
2. Beil, J., Ehrenberger, I., Scherer, C., Mandery, C., Asfour, T.: Human motion classification based on multi-modal sensor data for lower limb exoskeletons. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5431–5436 (2018)
3. Gordleeva, S.Y., Lobov, S.A., Grigorev, N.A., Savosenkov, A.O., Shamshin, M.O., Lukoyanov, M.V., Khoruzhko, M.A., Kazantsev, V.B.: Real-time EEG-EMG human-machine interface-based control system for a lower-limb exoskeleton. IEEE Access 8, 84070–84081 (2020)
4. Langlois, K., Geeroms, J., Van De Velde, G., Rodriguez-Guerrero, C., Verstraten, T., Vanderborght, B., Lefeber, D.: Improved motion classification with an integrated multimodal exoskeleton interface. Front. Neurorobotics 15 (2021)
5. Shi, K., Mu, F., Huang, R., Huang, K., Peng, Z., Zou, C., Yang, X., Cheng, H.: Multimodal human-exoskeleton interface for lower limb movement prediction through a dense co-attention symmetric mechanism. Front. Neurosci. 16 (2022)
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