Atari, S., & Lopez, C. E., & Bialczak, E. J. (2022, April), Disability Assistant System Using Brain-Computer Interface and EEG Signals.  Paper presented at ASEE-NE 2022, Wentworth Institute of Technology, Massachusetts. 10.18260/1-2--42166

\bibitem{asee_peer_42166}
  Atari, S., \& Lopez, C. E., \& Bialczak, E. J. (2022, April), \emph{Disability Assistant System Using Brain-Computer Interface and EEG Signals.}
  Paper presented at ASEE-NE 2022, Wentworth Institute of Technology, Massachusetts.
  10.18260/1-2--42166

Sief Atari, Celso Enrique Lopez, and Eric Joseph Bialczak.  "Disability Assistant System Using Brain-Computer Interface and EEG Signals.".  ASEE-NE 2022, Wentworth Institute of Technology, Massachusetts, 2022, April.  ASEE Conferences, 2022.  https://peer.asee.org/42166 Internet.  14 Dec, 2024

\bibitem{asee_peer_42166}
  Sief Atari, Celso Enrique Lopez, and Eric Joseph Bialczak.
  "Disability Assistant System Using Brain-Computer Interface and EEG Signals.".
  \emph{ASEE-NE 2022, Wentworth Institute of Technology, Massachusetts, 2022, April}.
  ASEE Conferences, 2022.
  https://peer.asee.org/42166 Internet.  14 Dec, 2024

@INPROCEEDINGS{asee_peer_42166
author = "Sief Atari, Celso Enrique Lopez, and Eric Joseph Bialczak"
title = "Disability Assistant System Using Brain-Computer Interface and EEG Signals."
booktitle = "ASEE-NE 2022"
year = "2022"
month = "April"
address = "Wentworth Institute of Technology, Massachusetts"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/42166}
number = {10.18260/1-2--42166}
}

TY  - CPAPER
AB  - Letting people use their minds to move objects telepathically has always been a part of fictional movies and literature. This fictional interpretation can soon become our reality. Machines that read brain signals are improving every day and becoming a part of our technologies for the future. Brain-Computer Interface (BCI) provides a communication channel that enables people with disabilities to interact with their environment. BCI obtains brain signals, analyze, and convert them into commands that are transferred to output devices that continue the action. People suffering from neuromuscular problems/disorders can use their brain signals for communication and handling of objects in their environment, which allows them to do some actions that they are not able to do with their disability. To obtain the brain wave signals, we are going to use the EMOTIV Insight headset. This device measures focus, engagement, interest, excitement, relaxation, and stress levels. It also identifies facial expressions such as blink, wink, surprise, and smile. The brain sends lots of signals, and we are working on finding and relating these measures to program a device to complete a task when this signal is received. The five electrodes located on the headset will measure the voltage differences between neurons. Then, the signal will be amplified, filtered, and interpreted by a computer program that investigates the signals coming from the headset, and analyzes them based on the measurements that we specified which include the trained profile of mental commands and facial expressions like frown, wink L/R, surprise, blink, smile, and clench, which can then be used in any BCI application. We are researching which type of signal or expression can give us the best results when controlling an object.
AU  - Sief Atari
AU  - Celso Enrique Lopez
AU  - Eric Joseph Bialczak
CY  - Wentworth Institute of Technology, Massachusetts
DA  - 2022/04/22
PB  - ASEE Conferences
TI  - Disability Assistant System Using Brain-Computer Interface and EEG Signals.
UR  - https://peer.asee.org/42166
DO  - 10.18260/1-2--42166
ER  -