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

ABSTRACT:

Background

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 assistance is one possible way to improve BMI performance. We describe a method of shared control where the user controls a prosthetic arm using a BMI and receives assistance with positioning the hand when it approaches an object.

Methods

Two human subjects with tetraplegia used a robotic arm to complete object transport tasks with and without shared control. The shared control system was designed to provide a balance between BMI-derived intention and computer assistance. An

SUBMITTER: Downey JE 

PROVIDER: S-EPMC4797113 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature