Andrew J. Sutter
Papers
1
Total Citations
16
H-Index
1
About
Andrew J. Sutter is a pioneering researcher in brain-machine interfaces (BMI) and neuroprosthetics, with a focus on translating neural signals into real-world robotic control. His most cited work, "Brain machine interface using Emotiv EPOC to control robai cyton robotic arm" (2015, 16 citations), established a foundational framework for electroencephalography (EEG)-based thought recognition software. Sutter developed and tested a complete software suite that decodes raw EEG data from an Emotiv EPOC headset, pairing specific human thoughts with corresponding actions to control a robotic arm. This proof-of-concept demonstrated the viability of low-cost, non-invasive BMI systems for assistive robotics. By integrating accessible hardware with custom signal-processing algorithms, Sutter’s work opened pathways for more affordable neuroprosthetic solutions, directly impacting rehabilitation engineering and human-robot interaction. His contributions continue to influence researchers developing real-time neural control systems, bridging the gap between cognitive intent and physical actuation.
Research Focus
Key Achievements
Top Papers
- 1Brain machine interface using Emotiv EPOC to control robai cyton robotic arm16 citations · 2015