BCI Poster
- 1. Brain-Computer Interface for Volume and Tuning Control of a Radio System using the Emotiv EPOC+ Headset Walter Brandsema, Ibrahim Akbar University of South Carolina, University of Rochester IREECE REU, Oakland University • Brain-Computer Interface (BCI) is a direct communication pathway between the brain and an external device. • Often directed at assisting, augmenting, or repairing human cognitive or sensory-motor functions. • Some BCI is dependent on the capability of individuals to consistently produce discernable changes in their electroencephalographic (EEG) activity (i.e. brainwaves). • Provides a non-muscular channel for sending commands to an external environment. • This was a study to assess the feasibility of BCI using the commercially available Emotiv EPOC+ interfaced with a radio console. • Effective brain-computer interface is designed via correlation of mental commands to actions of the radio system. Introduction • The development of a Brain-Computer Interface using the commercially available Emotiv EPOC+ headset was successful via pairing of mental commands to radio console actions. • This is one of the first step in producing a device to allow disabled persons to interact with their environment. • Precise responses are limited to how well the BCI interprets the brain signals and the how the hardware is properly adjusted to the software. • Reduction of signal to noise ratio in BCI applications would help increase accuracy and precision of BCI’s interpretation of the user’s intentions. • The completion of the Power Method on the raw data allows for future possible methods of feature extractions allowing BCIs to interact successfully with the subject and their environment. • The Power Method shows the change in power over time in the signal that is occurring and can be used as a means of extracting features (i.e intentions) from the brainwave when incorporated with other methods of signal processing. • The graphs display how the three trials of the disappear command from the Emotiv software were used to generate the single graph displaying fluctuation in power for that specific command. Experimental Setup To characterize BCIs, a radio control BCI system was designed using the following material and procedure. • This setup allowed for real-time interaction with the radio and analysis of the systems integrity. Experimental Setup Brain-Computer Interface is a direct communication pathway between the brain and an external device, and as such contains a plethora of opportunity in scientific fields. Other researchable areas of BCI include reduction of signal to noise ratio and more precise localization of signals, and this research at present may be applied to other external hardware or feature extraction methods. We recommend further investigation to refine BCI user training and data collection, as it currently lacks necessary precision for more intricate interfaces. Conclusion We would like to thank Dr. Brian Dean and Sakshi Agrawal for their continued guidance and support in this research. This research work was conducted at Oakland University through the IREECE REU program, funded by NSF under Award Number 1263133. Acknowledgements • Goal: See the potential capabilities of current BCI technology and characterize its limitations and successes, as well as develop potential algorithms that’s can improve the response and accuracy of BCIs. The research was separated into four main sections: Data collection of mental commands from the Emotiv EPOC+ headset for use in feature extraction algorithms. Testing of algorithms on data for localization of ERD/ERS, Development of radio console. Connection of Emotiv software package to Arduino hardware Results Walter Brandsema | [email protected] | (631) 988-3040 Ibrahim Akbar | [email protected] | (858) 336-4767 Contact Results Figure 1. General BCI system. Figure 2. Flowchart of BCI System. Figure 4. Angled view of BCI Radio Setup. Figure 5. Front view BCI Radio Setup. Figure 6. Filtered Data of Disappear Command (Trial 1). Figure 7. Filtered Data of Disappear Command (Trial 2). Figure 8. Filtered Data of Disappear Command (Trial 3). Figure 9. Power Method Analysis of Disappear Trials. Figure 2. Emotiv Headset with Corresponding Channel Numbers.