NDLI: Low-cost single-channel EEG based communication system for people with lock-in syndrome

Content Provider	IEEE Xplore Digital Library
Author	Ullah, K. Ali, M. Rizwan, M. Imran, M.
Copyright Year	2011
Description	Author affiliation: Deptt. NUCES-FAST Peshawar, Pakistan (Ullah, K.; Ali, M.; Rizwan, M.; Imran, M.)
Abstract	As the use of biomedical signals is incredibly increasing in both clinical and nonclinical applications. They have a great deal in the development of devices that can be controlled by information inferred from thoughts. One of the current hot topics for research is the Brain Computer Interface (BCI) on basis of EEG signals. BCI is a technology that makes humans to control computer or other devices on basis of information inferred from thoughts. BCIs have given new hopes to people who suffer from locked-in syndrome and motor disabilities by providing alternative means of communication channels. The existing BCIs are Multi-channel, thus very expensive in terms of cost and processing speed, which make them difficult for domestic use. The aim of this research paper is to introduce a very cheap, simple and a robust single channel BCI that could prevail in the market. We propose a very low-cost EEG-based BCI that is designed to help severely disabled people communicate with others by means of text and SMS. To make it simple and affordable, the number of channels is limited to one and signal is acquired through homemade silver electrodes and then fed to the computer through the soundcard for further processing and features extractions. The experimental results show that the proposed system is capable enough to provide a very low cost, yet reliable, communication means and a suitable BCI for domestic use. Its average accuracy is 87%. The potential uses for the technology are almost limitless. Instead of communication system, disabled users could have robotic wheelchair, allowing them to move and directly interact with the environments thus it can be used for clinical and nonclinical purposes.
Starting Page	120
Ending Page	125
File Size	1572367
Page Count	6
File Format	PDF
ISBN	9781457706547
e-ISBN	9781457706578
DOI	10.1109/INMIC.2011.6151455
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-22
Publisher Place	Pakistan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Electrodes Computer languages Indexes Robustness Computers Filtering motor disability Brain computer interface (BCI) electroencephalogram (EEG) communication channel locked-in syndrome
Content Type	Text
Resource Type	Article

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