Author

S.-P. Kim

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 4

Signature Assays, Organisms & Methods

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Assay:electrophysiology· 4 Organism:human· 4 Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

C.-K. Chung· 1 shared D. Heo· 1 shared E. Jeong· 1 shared J. Kim· 1 shared J.-S. Kim· 1 shared M. Chung· 1 shared M. Kim· 1 shared O.-S. Kwon· 1 shared

Activity by Year

2022-2024 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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1 shared paperBioengineering

C.-K. Chung

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Task-Relevant Stimulus Design Improves P300-Based Brain-Computer Interfaces

J. Kim, S.-P. Kim, Y. S. Cho

This paper introduces a task-relevant dynamic stimulus design for P300-based BCIs, achieving high accuracy and information transfer rates with reduced calibration needs.

bioRxiv · May 1, 2024 · PreprintBioengineering

Distraction Impact of Concurrent Conversation on Event-Related Potential Based Brain-Computer Interfaces

M. Kim, S.-P. Kim

This study examines how concurrent conversation affects ERP-based BCIs, finding that speaking degrades accuracy and ERP amplitude while listening has less impact.

bioRxiv · Apr 29, 2024Bioengineering

Freeing P300-Based Brain-Computer Interfaces from Daily Calibration by Extracting Daily Common ERPs

D. Heo, S.-P. Kim

This paper addresses daily calibration challenges in P300-based BCIs by developing a method to extract daily common ERP patterns, improving performance without daily recalibration.

bioRxiv · Mar 2, 2024 · PreprintBioengineering

Decoding Imagined Musical Pitch from Human Scalp Electroencephalograms

M. Chung, T. Kim, E. Jeong, C.-K. Chung, J.-S. Kim, O.-S. Kwon, S.-P. Kim

This study decodes imagined musical pitch from human scalp EEG, achieving 35.68% accuracy using SVM and showing similar performance with DC features across different class numbers.

bioRxiv · Jun 13, 2022Bioengineering