Publications

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Author [ Title(Asc)] Type Year
C
Farina, D. , Jiang, N. , & Lorrain, T. . (2010). Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference. Surface EMG classification during dynamic contractions for multifunction transradial prostheses.
Zhou, R. , Jiang, N. , Englehart, K. , & Parker, P. . (2010). A computational model and simulation study of the efferent activity in the brachial nerves during voluntary motor intent. Medical and Biological Engineering and Computing, 48, 67–77. Springer.
Jochumsen, M. , Niazi, I. Khan, Mrachacz-Kersting, N. , Jiang, N. , Farina, D. , & Dremstrup, K. . (2015). Comparison of spatial filters and features for the detection and classification of movement-related cortical potentials in healthy individuals and stroke patients. Journal of neural engineering, 12, 056003. IOP Publishing.
Karimi, F. , Kofman, J. , Mrachcz-Kersting, N. , Farina, D. , & Jiang, N. . (2016). Comparison of EEG spatial filters for movement related cortical potential detection. In Engineering in Medicine and Biology Society (EMBC), 2016 IEEE 38th Annual International Conference of the (pp. 1576–1579). IEEE.
Chen, M. Lin, Yao, L. , & Jiang, N. . (2016). Commanding Wheelchair in Virtual Reality with Thoughts by Multiclass BCI based on Movement-related Cortical Potentials. Journal of Computational Vision and Imaging Systems, 2.
Xu, R. , Jiang, N. , Mrachacz-Kersting, N. , Lin, C. , Prieto, G. Asín, Moreno, J. C. , Pons, J. L. , et al. (2014). A closed-loop brain–computer interface triggering an active ankle–foot orthosis for inducing cortical neural plasticity. IEEE Transactions on Biomedical Engineering, 61, 2092–2101. IEEE.
Clinical Neurophysiology . (2015). A brain–computer interface for single-trial detection of gait initiation from movement related cortical potentials . Retrieved from http://www.sciencedirect.com/science/article/pii/S1388245714002521
Kapelner, T. , Jiang, N. , Vujaklija, I. , Aszmann, O. C. , Holobar, A. , & Farina, D. . (2015). Classification of motor unit activity following targeted muscle reinnervation. In Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on (pp. 652–654). IEEE.
Mrachacz-Kersting, N. , Jiang, N. , Aliakbaryhosseinabadi, S. , Xu, R. , Petrini, L. , Lontis, R. , Dremstrup, K. , et al. (2015). The Changing Brain: Bidirectional Learning Between Algorithm and User. In Brain-Computer Interface Research (pp. 115–125). Springer.
Kristensen, S. Rom, Niazi, I. Khan, Jochumsen, M. , Jiang, N. , Farina, D. , & Mrachacz-Kersting, N. . (Submitted). Changes in corticospinal excitability following the use of a BCI based protocol combined with sham visual feedback. In International Conference on NeuroRehabilitation, ICNR (pp. 599–602).
Niazi, I. Khan, Jiang, N. , Lorrain, T. , Cabrera, A. Rodrigo, Mrachacz-Kersting, N. , Dremstrup, K. , & Farina, D. . (2010). Changes in cortical excitability following the use of a BCI with abstract feedback. In BCI International Meeting.
Zhu, X. , Liu, J. , Zhang, D. , Sheng, X. , & Jiang, N. . (2017). Cascaded Adaptation Framework for Fast Calibration of Myoelectric Control. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25, 254–264. IEEE.
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Jiang, N. , Gizzi, L. , Mrachacz-Kersting, N. , Dremstrup, K. , & Farina, D. . (2015). A brain–computer interface for single-trial detection of gait initiation from movement related cortical potentials. Clinical Neurophysiology, 126, 154–159. Elsevier.
Brain-Computer Interfaces. (2015). Detection of movement intention from single-trial movement-related cortical potentials using random and non-random paradigms. Retrieved from http://dx.doi.org/10.1080/2326263X.2015.1053301
Brain-Computer Interface Workshop and hands-on seminar. (2013). Detection of movement intentions and applications in motor rehabilitation for stroke.
Brain-Computer Interface Research: A State-of-the-Art Summary 3. (2014). Brain-Computer Interface Research: A State-of-the-Art Summary 3. Retrieved from http://dx.doi.org/10.1007/978-3-319-09979-8_5
Brain-Computer Interface Research: A State-of-the-Art Summary -2. (2014). Brain-Computer Interface Research: A State-of-the-Art Summary -2. Retrieved from http://dx.doi.org/10.1007/978-3-642-54707-2_6
Brain-Computer Interface Research. (2014). A novel brain-computer interface for chronic stroke patients.
Biomedizinische Technik. (2014). Feasibility of an asynchronous event related desynchronization based brain switch for control of functional electrical stimulation.
Muceli, S. , Vujaklija, I. , Jiang, N. , Amsuess, S. , Graimann, B. , Aszmann, O. C. , & Farina, D. . (2017). A Biologically-Inspired Robust Control System for Myoelectric Control. In Converging Clinical and Engineering Research on Neurorehabilitation II (pp. 975–979). Springer.

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