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User-Friendly LabVIEW GUI for Prosthetic Hand Control Using Emotiv EEG Headset

Authors :
Mohamad Amlie Abu Kasim
Muhammad Azmi Ayub
Khairunnisa Johar
Cheng Yee Low
Noor Ayuni Che Zakaria
Hizzul Hamli
Muhammad Haszerul Mohd Salleh
Source :
Procedia Computer Science. 105:276-281
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

Prosthetic hand acts as a tool that enables the amputee to perform daily tasks. Instead of passive devices which are aesthetically pleasing, current devices come with improved functionality utilizing robotic technology. There are various ways to control a prosthetic hand. One of it includes Brain Computer Interface (BCI) which has advanced technologies and creates new possibilities in providing healthcare solutions for people with severe motor impairment. Generally, Electroencephalography (EEG) is dominated by BCI researchers as it provides non-invasive, inexpensive equipment, good resolution, ease of use, portability and no implantation approaches. EEG signals were recorded from healthy subjects through brain waves at specific locations on the scalp using Emotiv EEG Headset. This device can capture brain waves that include artifacts such as movement of a limb, respiration, speech, heartbeat and many more. Most artifacts will disturb the data, but artifacts can also be used for researchers to control the prosthetic hand. This paper shows that this technology is still undergoing a maturing process. In this work, the state-of-the-art is reviewed and a conceptual design for a non-invasive approach for controlling a prosthesis hand using Emotiv EEG Headset integrated with Graphical User Interface (GUI) is presented and designed using LabVIEW. This project is designed for applying cost-effective prosthetic hands controlled using signal artifacts. This device can be used and controlled by paralyzed individuals with limited communication ability using simple GUI.

Details

ISSN :
18770509
Volume :
105
Database :
OpenAIRE
Journal :
Procedia Computer Science
Accession number :
edsair.doi.dedup.....bec566180cae5f4261871e1cbcbb5ce3
Full Text :
https://doi.org/10.1016/j.procs.2017.01.222