Yuki Kokai
Papers
1
Total Citations
1
H-Index
1
About
Yuki Kokai is a researcher in cognitive neuroscience and brain-computer interfaces, with a focus on decoding motor intent from neural signals. Their most-cited work, "Identifying Motor Imagery-Related Electroencephalogram Features During Motor Execution" (2020), investigates how EEG patterns during actual movement can inform the detection of imagined actions—a critical step for developing non-invasive prosthetic control systems. By isolating distinct neural features that overlap between motor execution and imagery, Kokai’s research advances the precision of BCI algorithms, potentially enabling more intuitive interfaces for individuals with motor impairments. Though early in their career, with their flagship paper accumulating 1 citation, this foundational study has laid groundwork for future explorations in real-time neural decoding. Kokai’s contributions sit at the intersection of signal processing and clinical application, offering a pathway to restore movement through thought alone. Their work underscores the importance of bridging motor execution and imagery in EEG analysis, a niche yet pivotal area for next-generation assistive technologies.
Research Focus
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Top Papers
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