Minkyu Ahn
Affiliations: | Handong Global University | Computer Science and Engineering |
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Publications
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| Won K, Kim H, Gwon D, et al. (2023) Can vibrotactile stimulation and tDCS help inefficient BCI users? Journal of Neuroengineering and Rehabilitation. 20: 60 |
| Gwon D, Won K, Song M, et al. (2023) Review of public motor imagery and execution datasets in brain-computer interfaces. Frontiers in Human Neuroscience. 17: 1134869 |
| Ahn M, Lee S, Lauro P, et al. (2020) Rapid motor fluctuations reveal short-timescale neurophysiological biomarkers of Parkinson's disease. Journal of Neural Engineering |
| Baek HJ, Kim HS, Ahn M, et al. (2020) Ergonomic Issues in Brain-Computer Interface Technologies: Current Status, Challenges, and Future Direction. Computational Intelligence and Neuroscience. 2020: 4876397 |
| Kwon M, Cho H, Won K, et al. (2020) Use of Both Eyes-Open and Eyes-Closed Resting States May Yield a More Robust Predictor of Motor Imagery BCI Performance Electronics. 9: 690 |
| Lee J, Won K, Kwon M, et al. (2020) CNN With Large Data Achieves True Zero-Training in Online P300 Brain-Computer Interface Ieee Access. 8: 74385-74400 |
| Won K, Kwon M, Jang S, et al. (2019) P300 Speller Performance Predictor Based on RSVP Multi-feature. Frontiers in Human Neuroscience. 13: 261 |
| Kim S, Jeong S, Lee E, et al. (2019) OpenViBE2Unity: Open Source API for Brain-Computer Interface and Unity3D Application Journal of Kiise. 46: 1157-1164 |
| Schaeffer EL, Liu DY, Guerin J, et al. (2018) A Low-Cost Solution for Quantification of Movement during DBS Surgery. Journal of Neuroscience Methods |
| Ahn M, Cho H, Ahn S, et al. (2018) User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface. Frontiers in Human Neuroscience. 12: 59 |