TY  - JOUR
Y1  - 2022///
VL  - 758
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142715621&doi=10.1007%2f978-981-16-2183-3_85&partnerID=40&md5=9f328ad5c9847a768f90c44458b51808
A1  - Talha Ejaz, M.
A1  - Zahid, A.
A1  - Mudassir Ejaz, M.
JF  - Lecture Notes in Electrical Engineering
KW  - Brain computer interface; HTTP; Internet of things
KW  -  Android applications; Attention level; BCI; Classifieds; EEG signals; Input datas; Nuerosky; Performance; Quadriplegia; Wireless communications
KW  -  Remote control
ID  - scholars17397
N2  - The brain-controlled interface is gaining popularity in the academic and research industry due to its promising performance in many fields. In this research work, a prototype is mentioned to help the Quadriplegic patients move the wheelchair from their thinking decision. The proposed method used the BCI technology that takes the input data in an EEG signal using a Neurosky headset. The signal is then processed and classified into five significant actions. The movement of the remote-controlled (RC) car is controlled through attention levels. We incorporate the Internet of Things (IoT) for wireless communication that transmits the data using an android application. For safety purposes, we have designed a mobile application that allows the user to control the RC car manually. The proposed method was implemented on the RC car, and the attention level of 5 different subjects was recorded for 3 min. A video of our experiments can be found at https://www.youtube.com/watch?v=UzPGdy54AZw. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
SN  - 18761100
PB  - Springer Science and Business Media Deutschland GmbH
EP  - 917
AV  - none
TI  - EEG Based Brain Controlled RC Car with Attention Level
SP  - 907
N1  - cited By 1; Conference of 1st International Conference on Artificial Intelligence for Smart Community, AISC 2020 ; Conference Date: 17 December 2020 Through 18 December 2020; Conference Code:286319
ER  -