Tu.P19.C-27
Classifying Freewill Premovement Intentions from EEG Using Q-Learning-Based Neural Decoders in Reinforcement Learning Brain Machine Interfaces
Jenna Kim, santiago posso-murillo, Jihye Bae, University of Kentucky
Session:
Tu.P19: Brain-Computer Interface and Brain-Machine Interface IV Poster
Track:
Neural and Rehabilitation Engineering
Location:
Hall E; Bay C, Board #27
Presentation Time:
Tuesday, 28 July, 16:30 - 18:30
Presentation
Discussion
Resources
No resources available.
Session Tu.P19
Tu.P19.C-12: BANDWIDTH ADAPTATION CONTINUOUS WAVELET TRANSFORM BASED TEMPORAL AND SPECTRAL FUSION NETWORK FOR MOTOR IMAGERY DECODING
Xinlin Que, Yitao Jing, Jiaxing Wang, Zixuan Wang, Tianyu Lin, Kexin Xiang, Weiguo Shi, Limin Shi, Zeng-Guang Hou, Weiqun Wang, Institute of Automation, Chinese Academy of Sciences
Tu.P19.C-13: Cross-Condition EEG Decoding from Auditory Perception to Imagery: A Proof-of-Concept Study with Region-Wise Analysis
Zhuohao Zhang, Phurin Rangpong, Akima Connelly, Haruto Hamada, Tohru Yagi, Institute of Science Tokyo
Tu.P19.C-14: CuteSpeech: Automatic Speech and Phoneme Recognition System tailored for Children Applications
Daria Hemmerling, SoftServe, AGH University of Krakow, Krakow, Poland,; Sebastian Jurczak, Mateusz Kowalewski, SoftServe; Kamil Kwarciak, SoftServe, AGH University of Krakow, Krakow, Poland; Maria Pensko, Leonid Pavlovskyi, SoftServe; Milosz Dudek, SoftServe, AGH University of Krakow, Krakow, Poland; Michal Zakrzewski, Damyr Hadiiev, SoftServe
Tu.P19.C-15: Toward Online EEG Decoding of Mental Imagery
Hsi-An Chen, National Yang Ming Chiao Tung University; Po-Chih Kuo, National Tsing Hua University; Chun-Shu Wei, National Yang Ming Chiao Tung University
Tu.P19.C-16: BCI-2048: BUILDING TRANSLATABLE BRAIN-COMPUTER INTERFACE SKILLS THROUGH AUGMENTED REALITY GAMING
Danielle Jourdain, Taylor Nielsen, Eli Kinney-Lang, University of Calgary
Tu.P19.C-17: Continuous Three-Dimensional Control Based on Visual Brain-Computer Interface
Changxing Huang, Zhangxu Yu, Hui Zheng, Tsinghua University; Yike Sun, Beihang University; Xiaorong Gao, Tsinghua University
Tu.P19.C-18: Privacy-Preserving Outsourced Inference for EEG-Based BCI Systems: A CKKS Approach with Session-Bound Replay Resistance
Meng Chen, Ningbo University of Technology; Shudi Bao, Zhengjie Ji, Zeeshan Ahmad, Hao Zheng, Ningbo Institute of Digital Twin, Eastern Institute of Technology
Tu.P19.C-19: Rhythmic Auditory Stimulation’s Effect on Drumming-Based Motor Imagery
Akima Connelly, Phurin Rangpong, Zhuohao Zhang, Taiki Teranishi, Tohru Yagi, Institute of Science Tokyo
Tu.P19.C-20: THE SSVEP TOOLBOX: A PYTHON-BASED GPU-ACCELERATED TOOLBOX FOR FEATURE EXTRACTION AND CLASSIFICATION
Daniel Comaduran Marquez, University of Calgary; Hadi Habibzadeh, Stratton VA Medical Center; Sebastian Rueda Parra, National Center for Adaptive Neurotechnologies; Emily Schrag, Eli Kinney-Lang, Adam Kirton, University of Calgary; James Norton, Stratton VA Medical Center
Tu.P19.C-21: On-Robot Integrated Visual-Stimulus P300-BCI for Mobile-Robot Navigation: A Comparative Study
Yuta Sasatake, Kazuaki Ito, Gifu University
Tu.P19.C-22: MODEL-AGNOSTIC META-LEARNING BASED CROSS-SUBJECT ADAPTATION FOR FOUR-CLASS UNILATERAL MOTOR IMAGERY DECODING FROM EEG-BASED BCI
Devika K M, Praveen. K Parashiva, Vinod A. P., Singapore Institute of Technology
Tu.P19.C-23: Subject-independent Multi-class Motor Imagery Direction Classification Using EEG-based BCI
Jijomon Chettuthara Moncy, Sagila Gangadharan K., Vinod Achutavarrier Prasad, Singapore Institute of Technology
Tu.P19.C-24: TRANSFER LEARNING FOR PEDIATRIC USERS OF MOTOR IMAGERY AND P300 BRAIN-COMPUTER INTERFACES
Brian Irvine, Hatem Abou-Zeid, Adam Kirton, Eli Kinney-Lang, University of Calgary
Tu.P19.C-25: What Robustness Evaluation Is Needed Toward Practical Usage of EEG Decoding Models?
Jingyuan Wang, Junhua Li, Other
Tu.P19.C-26: EEG-Based Imagined Speech Decoding Using a Hybrid CNN-SNN Architecture
Fatima Shalhoub, Antonine University; Mariam Al Mawla, University of Granada; Kabalan Chaccour, Antonine University; Iván López-Espejo, University of Granada; Hoda Fares, Stanford University
Tu.P19.C-27: Classifying Freewill Premovement Intentions from EEG Using Q-Learning-Based Neural Decoders in Reinforcement Learning Brain Machine Interfaces
Jenna Kim, santiago posso-murillo, Jihye Bae, University of Kentucky
Tu.P19.C-28: Fine-Grained Unilateral Upper-Limb Motor Imagery Classification Using EEG Signals
Ghazal Rahmani-Sane, Sasan Haghani, Rutgers University
Tu.P19.C-29: DETECTING MOVEMENT-RELATED INTENTIONS OF FREEWILL REACHING AND GRASPING TASKS IN EEG-BASED BRAIN MACHINE INTERFACES
Bhoj Raj Thapa, Luis Gonzalo Sanchez Giraldo, Jihye Bae, University of Kentucky
Resources
No resources available.