Matthew Thomas Cusumano
Papers
1
Total Citations
16
H-Index
1
About
Matthew Thomas Cusumano is a pioneering researcher at the intersection of neural engineering and robotics, best known for his foundational work in brain-machine interfaces (BMI). His most influential contribution, the 2015 study "Brain machine interface using Emotiv EPOC to control robai cyton robotic arm," established a groundbreaking framework for translating raw electroencephalography (EEG) data into actionable commands. By developing and testing a thought-recognition software suite paired with the Emotiv EPOC headset, Cusumano demonstrated how neural signals could directly control a robotic arm—a critical step toward assistive technologies for individuals with motor impairments. This work, cited 16 times, laid the groundwork for non-invasive, low-cost BMI systems. Cusumano’s research bridges cognitive neuroscience and human-robot interaction, offering scalable solutions for prosthetics and rehabilitation. His achievements highlight the potential of accessible neural interfaces, inspiring future innovations in neuroprosthetics and real-time brain-controlled devices.
Research Focus
Key Achievements
Top Papers
- 1Brain machine interface using Emotiv EPOC to control robai cyton robotic arm16 citations · 2015