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    Brain-computer interface to control a 6 DOF robotic arm

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    abstract (45.10Kb)
    Date
    2021-04-02
    Author
    Don, Thisath Attampola Arachchige
    Advisor
    Yihun, Yimesker S.; Desai, Jaydip M.
    Metadata
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    Citation
    Don, T. A. A. 2021. Brain-computer interface to control a 6 DOF robotic arm -- In Proceedings: 17th Annual Symposium on Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University
    Abstract
    In this study, a brain-computer interface (BCI) system is developed to control a six degrees of freedom robot arm. Such interface systems have a potential application in space missions for astronauts to have supplemental human-robot communication platform. Also, such human-robot interface system can be used to aid and enhance the quality of life for people with disability. However, decoding brain signal information into multi-degree of freedom system is a real challenge as the signals are easily affected by noise and crosstalk. In this research, an integrated electroencephalogram (EEG) and near-infrared spectroscopy (fNIR) system is used to record the brain's electrical activity and its blood-oxygen-level dependent (BOLD) responses. Then an algorithm has been developed and used to classify the signals related to six different directional intents. These six different features were utilized to command a robot manipulator to follow the six directional motions (left-right, up-down, and in-out). The task planning, robot kinematics and dynamics are computed using MATLAB/SIMULINK environment. Polynomial based inverse kinematic approach is applied to find the corresponding robot joint positions. The integrated system was simulated in a virtual environment using unity software. The preliminary result has shown the feasibility of decoding brain signals to create a BCI systems for the control of multi- degrees of freedom robotic system.
    Description
    Presented to the 17th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held online, Wichita State University, April 2, 2021.

    Research completed in the Department of Mechanical Engineering, College of Engineering; Department of Biomedical Engineering, College of Engineering
    URI
    https://soar.wichita.edu/handle/10057/19912
    Collections
    • BIOMED Research Publications
    • ME Graduate Student Conference Papers
    • Proceedings 2021: 17th Annual Symposium on Graduate Research and Scholarly Projects

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