EOG signal detection for home appliances activation

Harun, Hafizah; Mansor, W.

doi:10.1109/cspa.2009.5069215

Cited by 22 publications

(7 citation statements)

References 4 publications

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“…Eye blinks are used as control signals in this BCI. With the help of maximum amplitude and minimum amplitude in a sample window, eye blinks from non-eye blink signal can be detected (Harun, 2009). It was found that eye blinks can be detected successfully from 90% of the records after applying the proposed eye blinking detection algorithm to EEG signals.…”

mentioning

confidence: 84%

Computer-based Communication Aid using EEG for Paralytic Clients

Gobi

Arun²,

Geethanjali³

et al. 2014

DCID

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confidence: 84%

Computer-based Communication Aid using EEG for Paralytic Clients

Gobi

Arun²,

Geethanjali³

et al. 2014

DCID

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“…The effects of the offset in the horizontal direction were 23 cm and 27 cm in the vertical direction. X cm/pixel = 34 cm/1020 pixel (1) y cm/pixel = 27 cm/720 pixel (2) The end-effector of the robot moved to the target position (Px, Py). Px was the end-effector position in the x-axis, and Py was the end-effector position in the y-axis.…”

Section: Design Of a Two-dof Robot Manipulatormentioning

confidence: 99%

“…Nowadays, in daily activity, people are used to working with computers or machines to improve their quality of work. However, for some paralysis patients, armless persons [1], older adults [2] and locked-in syndrome patients, they face some barriers in controlling devices, because of their limitations. To solve this problem, people have tried to discover alternative ways to transmit and receive signals between humans and machines [3].…”

Section: Introductionmentioning

confidence: 99%

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Rotation Matrix to Operate a Robot Manipulator for 2D Analog Tracking Objects Using Electrooculography

et al. 2014

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Performing some special tasks using electrooculography (EOG) in daily activities is being developed in various areas. In this paper, simple rotation matrixes were introduced to help the operator move a 2-DoF planar robot manipulator. The EOG sensor, NF 5201, has two output channels (Ch1 and Ch2), as well as one ground channel and one reference channel. The robot movement was the indicator that this system could follow gaze motion based on EOG. Operators gazed into five training target points each in the horizontal and vertical line as the preliminary experiments, which were based on directions, distances and the areas of gaze motions. This was done to get the relationships between EOG and gaze motion distance for four directions, which were up, down, right and left. The maximum angle for the horizontal was 46°, while it was 38° for the vertical. Rotation matrixes for the horizontal and vertical signals were combined, so as to diagonally track objects. To verify, the errors between actual and desired target positions were calculated using the Euclidian distance. This test section had 20 random target points. The result indicated that this system could track an object with average angle errors of 3.31° in the x-axis and 3.58° in the y-axis.

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“…It is used to control devices e.g. home appliances [5], wheelchair navigation [6] and to develop gaming consoles [7]. It is also used in applications like activity recognition, analysis of human cognition etc.…”

Section: Introductionmentioning

confidence: 99%

Command the computer with your eye - An electrooculography based approach

Hossain

Huda

Ahmad

2014

The 8th International Conference on Software, Knowledge, Information Management and Applications (SKIMA 2014)

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In this paper, a user independent human computer interface system using eye movement and blink feature detection is introduced. A hands free interface between computer and human can potentially replace the traditional human computer interface devices like mouse, keyboard etc. This technology is intended to give functionality to peoples with severe motor disabilities to control a computer by just moving their eyes. This paper describes a method of controlling the mouse cursor on a computer screen using the electrical potentials developed by eye movements known as Electrooculography. Electrooculography (EOG) signal is used to detect eye movement and blink features. The EOG signal is recorded from electrodes placed at appropriate positions around the eyes. The captured EOG signal is then analyzed to detect and classify eye movement features of interest. The detected features were then used to generate control signals to control a mouse cursor. The cursor control application is implemented offline. The detection accuracy for blinks, horizontal and vertical saccades are 100%, 97% and 93% respectively. Keywords-human computer interface (HCI), cornea retinal potential, electrooculography (EOG), eye movement analysis, automatic threshold determination.

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EOG signal detection for home appliances activation

Cited by 22 publications

References 4 publications

Computer-based Communication Aid using EEG for Paralytic Clients

Computer-based Communication Aid using EEG for Paralytic Clients

Rotation Matrix to Operate a Robot Manipulator for 2D Analog Tracking Objects Using Electrooculography

Command the computer with your eye - An electrooculography based approach

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