Detection of eye blinks from EEG signals for home lighting system activation

Rani, Mohd Shaifulrizal b Abd; Mansor, W.

doi:10.1109/isma.2009.5164828

Cited by 29 publications

(4 citation statements)

References 8 publications

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“…Eye blink artifacts are easily noticeable in the brain waves because eye blinks cause large disturbances [18] in the electric potentials. ii.…”

Section: Eye Blink Artifactmentioning

confidence: 99%

“…Secondly, older individuals struggled to keep up with the pace of the GUI and failed to make timely voluntary eye blinks. Figure 18. Correlation of the wheelchair"s accuracy with the age of the subject BCI research that has been done in the past years, on decoding the clockwork inside the human brain has brought major technological advancements resulting in better solutions for improving the lives of many physically challenged people.…”

Section: Wheelchair Chassismentioning

confidence: 99%

“…Therefore, upscaling this work would be profitable and viable for industrial production. This technology can also be developed to bring life to the daily activities of paralyzed individuals such as controlling home appliances [18,21], playing video games, and interactive toys. It also has the potential to increase the work opportunities for the disabled, thus enhancing the quality of their life.…”

Section: Wheelchair Chassismentioning

confidence: 99%

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Brain-Computer Interfacing for Wheelchair Control by Detecting Voluntary Eye Blinks

Francis

Umayal

Kanimozhi

2021

IJEEI

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The human brain is considered one of the most powerful quantum computers and combining the human brain with technology can even outperform artificial intelligence. Using a Brain-Computer Interface (BCI) system, the brain signals can be analyzed and programmed for specific tasks. This research work employs BCI technology for a medical application that gives the unfortunate paralyzed individuals the capability to interact with their surroundings solely using voluntary eye blinks. This research contributes to the existing technology to be more feasible by introducing a modular design with three physically separated components: headwear, a computer, and a wheelchair. As the signal-to-noise ratio (SNR) of the existing systems is too high to separate the eye blink artifacts from the regular EEG signal, a precise ThinkGear module is used which acquired the raw EEG signal through a single dry electrode. An embedded Bluetooth module acquires and transfers the signals wirelessly to a computer. A MATLAB program captures voluntary eye blink artifacts from the brain waves and commands the movement of a miniature wheelchair via Bluetooth. To distinguish voluntary eye blinks from involuntary eye blinks, blink strength thresholds are determined. A Graphical User Interface (GUI) designed in MATLAB displays the EEG waves in realtime and enables the user to determine the movements of the wheelchair which is specially designed to take commands from the GUI. The findings from the testing phase unveil the advantages of a modular design and the efficacy of using eye blink artifacts as the control element for brain-controlled wheelchairs. The wheelchair attained a command detection and execution accuracy of 96.4% which is an improvement from the existing systems. The work presented here gives a basic understanding of the functionality of a BCI system and provides eye blink-controlled navigation of a wheelchair for patients suffering from severe paralysis.

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“…Eye blink artifacts are easily noticeable in the brain waves because eye blinks cause large disturbances [18] in the electric potentials. ii.…”

Section: Eye Blink Artifactmentioning

confidence: 99%

Section: Wheelchair Chassismentioning

confidence: 99%

Section: Wheelchair Chassismentioning

confidence: 99%

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Brain-Computer Interfacing for Wheelchair Control by Detecting Voluntary Eye Blinks

Francis

Umayal

Kanimozhi

2021

IJEEI

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“…In addition, they are highly preferred due to their lower cost and risk. Voluntary eye-blinks from the EEG signals has been used in tasks such as activating the home lighting system [2,3], controlling an external device such as a computer or a wheelchair [4]. Detection of eye-related events such as opening eyes, closing eyes, eye-blinking and eye movements [3,[5][6][7] and smart lock to be opened remotely by detecting a certain number of eye-blink signals [8] are remarkable studies.…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Eye-Blink to Speech Conversion by Dynamic Time Warping

Ekim¹,

Atasoy²,

IKIZLER³

2021

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Motor neuron patients such as paralysis, locking syndrome, and amyotrophic lateral sclerosis can see and hear what is happening in their environment, but cannot communicate with their environment. It is very important for these patients, who do not have any physical function other than eye movements, to be able to express their needs, feelings and thoughts. Therefore, to express the thoughts, needs and feelings of these patients, a system that converts eye-blink signals to speech was developed in this study. The main purpose of the designed system is high accuracy, low cost, high speed and independence from environmental factors. Undoubtedly, it is also very important that it causes as little discomfort to the patient as possible. Morse-coded signals generated by voluntary eye-blinks and the single-channel wireless NeuroSky MindWave Mobile device eliminates the need for cost-increasing equipment such as a camera or eye tracker and environmental factors such as light. With the use of Dynamic Time Warping (DTW), an algorithm which works at high speed and high accuracy at the time domain and does not require any training process has been implemented. In this way, the recorded speech was performed with a quite impressive accuracy.

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