Esmeralda C. Djamal
Papers
7
Total Citations
77
H-Index
5
About
Esmeralda C. Djamal is a leading researcher at the intersection of Brain-Computer Interfaces (BCI), robotics, and artificial intelligence, whose work has garnered over 77 citations. Her primary contributions lie in decoding neural signals—particularly EEG—to enable direct brain control of machines, from arcade games to robotic simulators. In her most cited work (29 citations), she pioneered a BCI-controlled game using Fast Fourier Transform and Learning Vector Quantization, allowing players to move characters with their thoughts. She further advanced emotion-based BCI by employing wavelet transforms and Recurrent Neural Networks to control a robot simulator based on three distinct emotional states (13 citations). Her research also tackles motor imagery classification, notably hand grasping imagination, using autoregressive models and neural networks (10 citations). Beyond BCI, Djamal has made significant strides in autonomous robotics, designing fuzzy logic controllers for hexapod mobile robots to achieve speed control and obstacle avoidance (10 citations). Her innovative use of single-stream spatial convolutional neural networks for hand movement identification (5 citations) showcases her versatility in human-robot interaction. Djamal’s work bridges the gap between cognitive neuroscience and practical automation, offering transformative pathways for assistive technologies and intelligent systems.
Research Focus
Key Achievements
Top Papers
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- 2Emotion brain-computer interface using wavelet and recurrent neural networks13 citations · 2020
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