Demonstration of a Semi-Autonomous Hybrid Brain-Machine Interface Using Human Intracranial EEG, Eye Tracking, and Computer Vision to Control a Robotic Upper Limb Prosthetic

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 22; no. 4; pp. 784 - 796
• Main Authors: McMullen, David P., Hotson, Guy, Katyal, Kapil D., Wester, Brock A., Fifer, Matthew S., McGee, Timothy G., Harris, Andrew, Johannes, Matthew S., Vogelstein, R. Jacob, Ravitz, Alan D., Anderson, William S., Thakor, Nitish V., Crone, Nathan E.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Artificial Intelligence; Artificial Limbs; Brain-computer interface (BCI); Brain-Computer Interfaces; brain-machine interface (BMI); Computer vision; Control systems; electrocorticography (ECoG); Electrodes; Electroencephalography - instrumentation; Electroencephalography - methods; Equipment Failure Analysis; Eye Movements; Female; Humans; hybrid BCI; intelligent robotics; intracranial EEG (iEEG); Male; Man-Machine Systems; Modulation; Monitoring; Pilot Projects; Prosthesis Design; Robotics; Robotics - instrumentation; Robotics - methods; Testing; Therapy, Computer-Assisted - instrumentation; Therapy, Computer-Assisted - methods; Training

To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, super...