Papers
5
Total Citations
117
H-Index
3
About
David Achanccaray is a pioneering researcher at the intersection of neuroscience and robotics, whose work focuses on developing brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs) to control assistive and mobile robotic systems. His major contributions include the early demonstration of EEG-based mobile robot control (70 citations) and the challenging decoding of hand motor imagery tasks within the same limb using deep learning (30 citations), significantly advancing non-invasive neural control for prosthetic and robotic applications. He also developed a P300-based BMI to control an assistive robot arm for daily activities (12 citations), showcasing practical assistive technology. More recently, Achanccaray has explored the neural and physiological profiling of operators during teleoperated social robot interactions using fNIRS and physiological response analysis (2023, 2025), addressing the underexplored domain of mental state monitoring in social teleoperation. His work bridges fundamental neuroscience, machine learning, and human-robot interaction, with a clear trajectory from basic BCI development to applied assistive systems and operator performance optimization. Achanccaray’s research is highly relevant for students and researchers interested in neuroprosthetics, human-robot collaboration, and the future of non-invasive neural control.
Research Focus
Key Achievements
Top Papers
- 1Activation of a mobile robot through a brain computer interface70 citations · 2010
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