Blending of brain-machine interface and vision-guided autonomous robotics improves neuroprosthetic arm performance during grasping

• Published in: Journal of neuroengineering and rehabilitation Vol. 13; no. 1; p. 28
• Main Authors: Downey, John E., Weiss, Jeffrey M., Muelling, Katharina, Venkatraman, Arun, Valois, Jean-Sebastien, Hebert, Martial, Bagnell, J. Andrew, Schwartz, Andrew B., Collinger, Jennifer L.
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 18.03.2016; BioMed Central
• Subjects: Adult; Analysis; Brain - physiopathology; Brain-Computer Interfaces; Care and treatment; Female; Hand - physiopathology; Hand Strength; Health aspects; Humans; Male; Middle Aged; Movement; Neural prostheses; Neurological Rehabilitation - instrumentation; Quadriplegia; Quadriplegia - physiopathology; Robotics; Robotics - methods; Upper Extremity - physiopathology; Brain-computer interface; Neuroprosthetic; Shared mode control; Assistive technology; Brain-machine interface

Recent studies have shown that brain-machine interfaces (BMIs) offer great potential for restoring upper limb function. However, grasping objects is a complicated task and the signals extracted from the brain may not always be capable of driving these movements reliably. Vision-guided robotic assist...