Brain-Computer Interface based on Neural Network with Dynamically Evolved for Hand Movement Classification

Widhi Winata Sakti1, Windhi (2023) Brain-Computer Interface based on Neural Network with Dynamically Evolved for Hand Movement Classification. FORTEI-International Conference on Electrical Engineering (FORTEI-ICEE): 2022. pp. 72-73.

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Abstract

Translating brain commands into movements on
the prosthetic robot is not an easy task. It is needed a control
system for the prosthetic robot based on human body signals to
predict the desired movement so that the robot is part of the
body. This assistive device is used to help people with disabilities
perform functional movements such as gripping with motor
activities performed on all five fingers. This paper proposed a
hand movement recognition system based on
electroencephalogram (EEG) using the Neural Network with
Dynamically Evolved Capacity (NADINE). The data generated
from the model test shows almost the same value as NADINE,
with a maximum accuracy of 98% and an average prediction
time of 14 milliseconds. These results further strengthen that the
NADINE model can be used in real-tim

Item Type:	Article
Subjects:	Cek Plagiasi Jurnal Peer Review
Divisions:	F. Fakultas Teknik > Teknik Elektro
Depositing User:	perpus perpustakaan unibabwi
Date Deposited:	26 Oct 2023 02:41
Last Modified:	26 Oct 2023 02:41
URI:	http://repository.unibabwi.ac.id/id/eprint/888

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