Hideki Akiyama
Papers
2
Total Citations
11
H-Index
2
About
Hideki Akiyama is a researcher focused on advancing non-invasive brain-machine interfaces (BMI), with a particular emphasis on portable neuroimaging technologies. His core research area lies in the development of practical BMI systems using Near-InfraRed Spectroscopy (NIRS), a technique that measures cerebral blood flow to decode human intent. Akiyama’s major contributions include improving the classification performance of NIRS-based BMIs through advanced signal processing methods, such as Independent Component Analysis (ICA) and self-proliferating Learning Vector Quantization (LVQ). His 2013 paper on this topic, which has garnered 8 citations, demonstrates a significant step toward making BMIs more accurate and reliable for real-world applications. By focusing on portability and practicality, Akiyama aims to bridge the gap between laboratory prototypes and everyday use in robotics and medical science, where BMIs could serve as intuitive input devices for assistive technologies or rehabilitation tools. His work, though early in citation impact, lays foundational groundwork for accessible, wearable brain-computer interfaces that could transform how humans interact with machines.
Research Focus
Key Achievements
Top Papers
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- 2