Seung-Bo Lee
Papers
3
Total Citations
105
H-Index
2
About
Dr. Seung-Bo Lee is a leading researcher in brain-computer interfaces (BCI) and biomedical signal processing, with a particular focus on motor imagery classification for rehabilitation. His most impactful work, "Comparative analysis of features extracted from EEG spatial, spectral and temporal domains for binary and multiclass motor imagery classification" (2019), has garnered 99 citations, establishing a foundational framework for decoding neural activity to assist paralyzed patients. Dr. Lee further advanced this field with his recurrent convolutional neural network model, which integrates temporal and spatial EEG features to enhance classification accuracy—a critical step toward practical BCI-based rehabilitation systems. Beyond neurotechnology, he has applied machine learning to perioperative medicine, developing a model to predict immediate postoperative desaturation from spirometry data, addressing a key challenge in respiratory care. By bridging neural engineering and clinical prediction, Dr. Lee’s work demonstrates a versatile commitment to translating computational methods into tangible improvements in patient quality of life and safety.
Research Focus
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Top Papers
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