TY - JOUR
T1 - Mind your thoughts
T2 - BCI using single EEG electrode
AU - Narayana, Sujay
AU - Venkatesha Prasad, RangaRao
AU - Warmerdam, Kevin
PY - 2019
Y1 - 2019
N2 - These days, the Internet of things (IoT) research is driving large-scale development and deployment of many innovative applications. IoT has indeed brought many smart applications to the doorstep of users. IoT has also made it possible to connect many sensors and control equipment. Here, the authors address an important application for physically challenged. The authors present a brain–computer interface (BCI) system to lock/unlock a wheelchair and control its movements using BCI. The approach presented here uses NeuroSky's MindWave Mobile, a single electrode electroencephalography (EEG) headset that can be connected to any Bluetooth-enabled system. The raw EEG data from the headset is processed on an Android mobile device to extract the electromyography (EMG) patterns that occur due to eye blinks and activity of muscles in the jaw. These patterns are used to control the movement of a wheelchair in all possible directions. A biometric security system is provided to lock and unlock the wheelchair by extracting the information about different brain waves from the raw EEG signal. In this system, only the user knows the password which is generated using brain waves and it can lock/unlock the wheelchair and control it. The proposed system was verified and evaluated using a prototype.
AB - These days, the Internet of things (IoT) research is driving large-scale development and deployment of many innovative applications. IoT has indeed brought many smart applications to the doorstep of users. IoT has also made it possible to connect many sensors and control equipment. Here, the authors address an important application for physically challenged. The authors present a brain–computer interface (BCI) system to lock/unlock a wheelchair and control its movements using BCI. The approach presented here uses NeuroSky's MindWave Mobile, a single electrode electroencephalography (EEG) headset that can be connected to any Bluetooth-enabled system. The raw EEG data from the headset is processed on an Android mobile device to extract the electromyography (EMG) patterns that occur due to eye blinks and activity of muscles in the jaw. These patterns are used to control the movement of a wheelchair in all possible directions. A biometric security system is provided to lock and unlock the wheelchair by extracting the information about different brain waves from the raw EEG signal. In this system, only the user knows the password which is generated using brain waves and it can lock/unlock the wheelchair and control it. The proposed system was verified and evaluated using a prototype.
UR - http://www.scopus.com/inward/record.url?scp=85065869295&partnerID=8YFLogxK
U2 - 10.1049/iet-cps.2018.5059
DO - 10.1049/iet-cps.2018.5059
M3 - Article
AN - SCOPUS:85065869295
VL - 4
SP - 164
EP - 172
JO - IET Cyber-Physical Systems: Theory and Applications
JF - IET Cyber-Physical Systems: Theory and Applications
SN - 2398-3396
IS - 2
ER -