Show simple item record

dc.contributor.advisorYihun, Yimesker S.
dc.contributor.advisorDesai, Jaydip M.
dc.contributor.authorDon, Thisath Attampola Arachchige
dc.date.accessioned2021-05-04T12:03:14Z
dc.date.available2021-05-04T12:03:14Z
dc.date.issued2021-04-02
dc.identifier.citationDon, 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
dc.identifier.urihttps://soar.wichita.edu/handle/10057/19912
dc.descriptionPresented to the 17th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held online, Wichita State University, April 2, 2021.
dc.descriptionResearch completed in the Department of Mechanical Engineering, College of Engineering; Department of Biomedical Engineering, College of Engineering
dc.description.abstractIn 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.
dc.description.sponsorshipGraduate School, Academic Affairs, University Libraries
dc.language.isoen_US
dc.publisherWichita State University
dc.relation.ispartofseriesGRASP
dc.relation.ispartofseriesv. 17
dc.titleBrain-computer interface to control a 6 DOF robotic arm
dc.typeAbstract
dc.rights.holderWichita State University


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record