Maulana Yusuf Abdullah
Papers
2
Total Citations
32
H-Index
2
About
Maulana Yusuf Abdullah is a researcher at the forefront of Brain-Computer Interface (BCI) technology, with a specific focus on translating neural signals into real-time control for interactive systems. His primary research areas include EEG signal processing, game-based BCI applications, and the integration of machine learning for neural decoding. Abdullah’s major contribution lies in demonstrating how Fast Fourier Transform (FFT) and Learning Vector Quantization (LVQ) can be effectively combined to interpret human thoughts for controlling game characters, bridging the gap between cognitive intent and digital action. His most cited work, "Brain Computer Interface Game Controlling Using Fast Fourier Transform and Learning Vector Quantization" (2017), has garnered 29 citations, highlighting its influence in the field of neurogaming. This research pioneered a non-muscular control pathway, allowing players to navigate an arcade game solely through brain activity captured via EEG signals. By developing systems that bypass traditional motor functions, Abdullah has advanced the practical application of BCI, offering new possibilities for assistive technology and immersive human-computer interaction. His work continues to inspire innovations in accessible gaming and neural control systems.
Research Focus
Key Achievements
Top Papers
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- 2