TY - GEN
T1 - The Effect of Neurofeedback Training in Virtual and Real Environments based on BCI
AU - Han, Dong Kyun
AU - Lee, Min Ho
AU - Williamson, John
AU - Lee, Seong Whan
N1 - Funding Information:
This research was supported in part by the Institute for Information and Communications Technology Promotion (IITP) through the Korea Government (MSIT) under Grant IITP-2015-1107, the SW Starlab support program, and under Grant 2017-0-00451, the Development of BCI-based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/2
Y1 - 2019/2
N2 - In this study, we investigated the effect of real-Time neurofeedback systems by adjusting the speed of a racing car and report the difference in effect between virtual and real environments. Thirty participants were divided into two conditions of the neurofeedback system (i.e., racing in real track and virtual game). For the performance evaluation, the band power of resting state EEG data and cognitive tests (Stroop and Digit span) were evaluated before and after the neurofeedback training. In the result, a significant increase of band power in the alpha frequency range (8-13Hz) as well as the test score were observed in both the virtual and real environments. Furthermore, neurofeedback in the virtual environment showed enhanced training effects compared to the real environment. We conclude that the performance of the neurofeedback training can be profoundly effected by the system environment as various factors (e.g., motivation, reward) are involved in the performance.
AB - In this study, we investigated the effect of real-Time neurofeedback systems by adjusting the speed of a racing car and report the difference in effect between virtual and real environments. Thirty participants were divided into two conditions of the neurofeedback system (i.e., racing in real track and virtual game). For the performance evaluation, the band power of resting state EEG data and cognitive tests (Stroop and Digit span) were evaluated before and after the neurofeedback training. In the result, a significant increase of band power in the alpha frequency range (8-13Hz) as well as the test score were observed in both the virtual and real environments. Furthermore, neurofeedback in the virtual environment showed enhanced training effects compared to the real environment. We conclude that the performance of the neurofeedback training can be profoundly effected by the system environment as various factors (e.g., motivation, reward) are involved in the performance.
KW - Alpha band power
KW - Electroencephalography
KW - Neurofeedback game
KW - Neurofeedback training
UR - http://www.scopus.com/inward/record.url?scp=85068328517&partnerID=8YFLogxK
U2 - 10.1109/IWW-BCI.2019.8737323
DO - 10.1109/IWW-BCI.2019.8737323
M3 - Conference contribution
AN - SCOPUS:85068328517
T3 - 7th International Winter Conference on Brain-Computer Interface, BCI 2019
BT - 7th International Winter Conference on Brain-Computer Interface, BCI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Winter Conference on Brain-Computer Interface, BCI 2019
Y2 - 18 February 2019 through 20 February 2019
ER -