Eye Blink Detection System for Paralyzed Patients

Paralysis of an human being is caused due to the degeneration of motor neurons which weakens the muscle, so that it does not allow patient to move, speak, breathe , and loss in the voluntary actions. It is an incurable disease. To understand the feelings of a paralyzed patients Brain wave technique and Electro-oculography techniques were used. These techniques are afflictive, discomfortable and leads to unconsciousness of the paralyzed patient. The real time video oculography system fills the communication gap between the patient and the world. Video Oculography (VOG) is video-based method of measuring the vertical, torsional and horizontal position components of both the eye blinks with the help of small cameras placed in the head-mounted mask .This paper presents different visual technologies, such as eye blink detection, eye center localization and conversion of the eye blink to speech. The video oculography could achieve accuracy of 0.968.

Download Full-text

EEG-Eye Blink Detection System for Brain Computer Interface

Converging Clinical and Engineering Research on Neurorehabilitation - Biosystems & Biorobotics ◽

10.1007/978-3-642-34546-3_98 ◽

2013 ◽

pp. 603-608 ◽

Cited By ~ 3

Author(s):

S. Rihana ◽

P. Damien ◽

T. Moujaess

Keyword(s):

Detection System ◽

Brain Computer Interface ◽

Computer Interface ◽

Eye Blink ◽

Blink Detection

Download Full-text

Eye-Blink Detection System for Virtual Keyboard

2021 National Computing Colleges Conference (NCCC) ◽

10.1109/nccc49330.2021.9428797 ◽

2021 ◽

Author(s):

Afraa Z. Attiah ◽

Enas F. Khairullah

Keyword(s):

Detection System ◽

Virtual Keyboard ◽

Eye Blink ◽

Blink Detection

Download Full-text

Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient

Bulletin of Electrical Engineering and Informatics ◽

10.11591/eei.v10i6.3200 ◽

2021 ◽

Vol 10 (6) ◽

pp. 3032-3041

Author(s):

Norasyimah Sahat ◽

Afishah Alias ◽

Fouziah Md Yassin

Keyword(s):

Brain Computer Interface ◽

Threshold Value ◽

Computer Interface ◽

Male Adult ◽

Eye Blink ◽

Human Attention ◽

Blink Detection ◽

Paralyzed Patient ◽

The Right ◽

Bci System

Integrated wheelchair controlled by human brainwave using a brain-computer interface (BCI) system was designed to help disabled people. The invention aims to improve the development of integrated wheelchair using a BCI system, depending on the ability individual brain attention level. An electroencephalography (EEG) device called mindwave mobile plus (MW+) has been employed to obtain the attention value for wheelchair movement, eye blink to change the mode of the wheelchair to move forward (F), to the right (R), backward (B) and to the left (L). Stop mode (S) is selected when doing eyebrow movement as the signal quality value of 26 or 51 is produced. The development of the wheelchair controlled by human brainwave using a BCI system for helping a paralyzed patient shows the efficiency of the brainwave integrated wheelchair and improved using human attention value, eye blink detection and eyebrow movement. Also, analysis of the human attention value in different gender and age category also have been done to improve the accuracy of the brainwave integrated wheelchair. The threshold value for male children is 60, male teenager (70), male adult (40) while for female children is 50, female teenager (50) and female adult (30).

Download Full-text