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Research in Brain-Computer Interface (BCI) aims to understand human intent with the goal to enhance Human-Robot Interaction (HRI) especially in the field of assistive robotics. The goal of this research is to develop a behavioral sequence based framework to help persons with upper limb disabilities to maintain self-dependence. The framework aims to operate in stages and links multiple functional components to identify human intent and control a robotic arm. The development, operation, and evaluation of the framework and the linked functional components to acquire, process, evaluate, and map BCI signals generated using facial expressions and head movements to predefined actions will be introduced.The framework will integrate multiple functional components such as a non-invasive BCI control device, a vibrotactile haptic feedback device, a visual feedback environment, the evaluation and training platform, and a robotic arm. The robot pick, move and place actions are mapped to different facial expressions and presented using haptic and visual feedback to the user for classified action verification before performing the process using a robotic arm. The initial evaluation of the developed framework was 100% successful with two volunteers who also provided constructive feedback. The initial successful evaluation provides confidence to further test the framework with more volunteers to identify limitations and/or areas of improvement and its application for further research in HRI as it applies to assistive robotic systems.


Aerospace Engineering | Engineering | Mechanical Engineering

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