Kelly Cashion
Papers
1
Total Citations
14
H-Index
1
About
Kelly Cashion is a researcher whose work sits at the intersection of neuroscience and assistive technology, with a primary focus on brain-machine interfaces (BMIs). Her most-cited paper, "Electroencephalograph based brain machine interface for controlling a robotic arm" (2013, 14 citations), demonstrates a foundational contribution to non-invasive neural control systems. In this work, Cashion showed how electroencephalography (EEG) can be used to detect and classify brain signals, enabling direct control of a robotic arm without the need for implanted electrodes. This research is significant for its potential to restore mobility and independence to individuals with severe motor impairments, such as those resulting from spinal cord injury or neurodegenerative disease. By leveraging EEG—a safe, portable, and relatively low-cost technology—Cashion's work helps bridge the gap between human intention and machine action. Her contributions exemplify the practical application of neural signal processing and pattern recognition in real-world assistive devices, offering a compelling glimpse into the future of human-computer interaction and neurorehabilitation.
Research Focus
Key Achievements
Top Papers
- 1