Haik, H., & Meng, J., & Hu, Q. (2023, March), A Smart Warning System Design Based on Brainwaves to Maintain Attention  Paper presented at 2023 ASEE North Central Section Conference, Morgantown, West Virginia. 10.18260/1-2--44928

\bibitem{asee_peer_44928}
  Haik, H., \& Meng, J., \& Hu, Q. (2023, March), \emph{A Smart Warning System Design Based on Brainwaves to Maintain Attention}
  Paper presented at 2023 ASEE North Central Section Conference, Morgantown, West Virginia.
  10.18260/1-2--44928

Haylee Haik, Jennifer Meng, and Qin Hu.  "A Smart Warning System Design Based on Brainwaves to Maintain Attention".  2023 ASEE North Central Section Conference, Morgantown, West Virginia, 2023, March.  ASEE Conferences, 2023.  https://peer.asee.org/44928 Internet.  14 Dec, 2024

\bibitem{asee_peer_44928}
  Haylee Haik, Jennifer Meng, and Qin Hu.
  "A Smart Warning System Design Based on Brainwaves to Maintain Attention".
  \emph{2023 ASEE North Central Section Conference, Morgantown, West Virginia, 2023, March}.
  ASEE Conferences, 2023.
  https://peer.asee.org/44928 Internet.  14 Dec, 2024

@INPROCEEDINGS{asee_peer_44928
author = "Haylee Haik, Jennifer Meng, and Qin Hu"
title = "A Smart Warning System Design Based on Brainwaves to Maintain Attention"
booktitle = "2023 ASEE North Central Section Conference"
year = "2023"
month = "March"
address = "Morgantown, West Virginia"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/44928}
number = {10.18260/1-2--44928}
}

TY  - CPAPER
AB  - The rise of digital technology and increasingly busy lifestyles around the world has surrounded people with a growing number of distractions. These distractions may affect an individual’s ability to retain focus in various areas of life that require concentration, especially learning or driving. Utilizing biotechnology can closely monitor an individual's brain state and provide valuable feedback about how and when to adjust their daily habits to maintain better concentration. This technology can help students regain attention during class periods, leading to better focus on class material, and can help drivers refocus during driving, which can prevent accidents and promote safer driving.

The purpose of this project is to develop a warning system that utilizes data collected from electroencephalography (EEG) technology to evaluate user focus. A 16-channel EEG cap with 19 Ag/AgCl coated electrodes will record brainwave data for a user performing a set of tasks requiring active or passive engagement. The EEG signals will be preprocessed using filters to remove artifacts and confounding events from the data. The data will then be analyzed using Fast Fourier Transform (FFT) to abstract features of the EEG signals associated with active and passive tasks. After these initial calibrations, an external device will be created to alert the user when they enter or exit a focused state. Lastly, a machine learning algorithm will be developed to continuously refine the accuracy of the focus monitoring system for individual users as more data is collected. 

AU  - Haylee Haik
AU  - Jennifer Meng
AU  - Qin Hu
CY  - Morgantown, West Virginia
DA  - 2023/03/24
PB  - ASEE Conferences
TI  - A Smart Warning System Design Based on Brainwaves to Maintain Attention
UR  - https://peer.asee.org/44928
DO  - 10.18260/1-2--44928
ER  -