@misc{10481/66497,
year = {2020},
month = {11},
url = {http://hdl.handle.net/10481/66497},
abstract = {Electroencephalography (EEG) signals to detect motor imagery have been used to help
patients with low mobility. However, the regular brain computer interfaces (BCI) capturing the EEG
signals usually require intrusive devices and cables linked to machines. Recently, some commercial
low-intrusive BCI headbands have appeared, but with less electrodes than the regular BCIs. Some
works have proved the ability of the headbands to detect basic motor imagery. However, all of these
works have focused on the accuracy of the detection, using session sizes larger than 10 s, in order to
improve the accuracy. These session sizes prevent actuators using the headbands to interact with the
user within an adequate response time. In this work, we explore the reduction of time-response in
a low-intrusive device with only 4 electrodes using deep learning to detect right/left hand motion
imagery. The obtained model is able to lower the detection time while maintaining an acceptable
accuracy in the detection. Our findings report an accuracy above 83.8% for response time of 2 s
overcoming the related works with both low- and high-intrusive devices. Hence, our low-intrusive
and low-cost solution could be used in an interactive system with a reduced response time of 2 s.},
organization = {Spanish Ministry of Economy and Competitiveness (Agencia Estatal de Investigacion-AEI) 	
TIN2016-79484-R},
organization = {European Union (EU)

TIN2016-79484-R},
organization = {Spanish Government

PID2019-109644RB-I00/AEI/10.13039/501100011033
FPU18/00287},
publisher = {Mdpi},
keywords = {Neural networks},
keywords = {Deep learning},
keywords = {Motor imagery},
keywords = {Wearable},
keywords = {EEG},
keywords = {BCI},
keywords = {Users’ interaction},
keywords = {Response time},
title = {Reducing Response Time in Motor Imagery Using A Headband and Deep Learning},
doi = {10.3390/s20236730},
author = {García Moreno, Francisco Manuel and Bermúdez Edo, María del Campo and Garrido Bullejos, José Luis and Rodríguez Fórtiz, María José},
}