Liu, J. ., Sheng, X. ., Zhang, D. ., Jiang, N. ., & Zhu, X. . (2016). Towards Zero Retraining for Myoelectric Control Based on Common Model Component Analysis. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24. https://doi.org/https://doi.org/10.1109/TNSRE.2015.2420654 (Original work published 2016)
Reference author: Xinjun Sheng
First name
Xinjun
Last name
Sheng
He, J. ., Zhang, D. ., Sheng, X. ., & Zhu, X. . (2015). A Comparison of Open-Loop and Closed-Loop Adaptive Calibration for Pattern Recognition based Myoelectric Control. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). Presented at the. Milan, Italy: Engineering in Medicine and Biology Society (EMBC). https://doi.org/https://doi.org/10.1109/EMBC.2015.7318568 (Original work published 2015)
Pan, L. ., Zhang, D. ., Jiang, N. ., Sheng, X. ., & Zhu, X. . (2015). Improving Robustness against Electrode Shift of High Density EMG for Myoelectric Control through Common Spatial Patterns. Journal of NeuroEngineering and Rehabilitation. https://doi.org/10.1186/s12984-015-0102-9
He, J. ., Sheng, X. ., Zhu, X. ., Jiang, C. ., & Jiang, N. . (2019). Spatial Information Enhances Myoelectric Control Performance with Only Two Channels. IEEE Transactions on Industrial Informatics, 15, 7. https://doi.org/DOI: 10.1109/TII.2018.2869394 (Original work published 2019)
Yao, L. ., Sheng, X. ., Mrachacz-Kersting, N. ., Zhu, X. ., Farina, D. ., & Jiang, N. . (2018). Decoding covert somatosensory attention by a BCI system calibrated with tactile sensation. IEEE Transactions on Biomedical Engineering, 65. https://doi.org/10.1109/TBME.2017.2762461 (Original work published 2018)
He, J. ., Sheng, X. ., Zhu, X. ., & Jiang, N. . (2018). Electrode density affects the robustness of myoelectric pattern recognition system with and without electrode shift. https://doi.org/10.1109/JBHI.2018.2805760
Shu, X. ., Chen, shugeng ., Yao, L. ., Sheng, X. ., Zhang, D. ., Jiang, N. ., Jia, J. ., & Zhu, X. . (2018). Fast Recognition of BCI-inefficient Users Using Physiological Features from EEG Signals: A Screening Study of Stroke Patients. Frontiers in Neuroscience. https://doi.org/10.3389/fnins.2018.00093 (Original work published 2018)
Yao, L. ., Sheng, X. ., Mrachacz-Kersting, N. ., Zhu, X. ., Farina, D. ., & Jiang, N. . (2018). A multi-class tactile brain-computer interface based on stimulus-induced oscillatory dynamics. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26, 10. https://doi.org/10.1109/TNSRE.2017.2731261
Yao, L. ., Sheng, X. ., Mrachacz-Kersting, N. ., Zhu, X. ., Farina, D. ., & Jiang, N. . (2018). Performance of Brain-Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26, 68. https://doi.org/10.1109/TNSRE.2017.2769686
Yao, L. ., Sheng, X. ., Mrachacz-Kersting, N. ., Zhu, X. ., Farina, D. ., & Jiang, N. . (2018). Sensory Stimulation Training for BCI System based on Somatosensory Attentional Orientation. IEEE Transactions on Biomedical Engineering, Early Access. https://doi.org/10.1109/TBME.2018.2852755 (Original work published 2018)
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