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 | brandsem@email.sc.edu | (631) 988-3040
Ibrahim Akbar | iakbar@u.rochester.edu | (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.