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SmoothEye is a wearable device that allows to accurately measure your level of focus and alertness by tracking your eye movements.  Eyes of a healthy and alert person follow a moving object smoothly while eyes of a drunk, tried or sick person "jump" during the movement. 

SmoothEye can capture and process the eye movement with great accuracy which allows you to measure not only smaller degree of intoxication but also your level of tiredness or alertness. 
This eye tracking technology was presented at Society for Neuroscience conference in 2010 and is now available to you. SmoothEye evaluates smooth pursuit, fixation, pupil size and other parameters. Deterioration of a parameter is a red flag signaling possible brain impairment. Among most evident reason of impairment is alcohol consumption which is detectable even after 1-2 drinks. Other reasons may include depression, physical or psychological brain trauma, sleep deprivation, distress and others. 

SmoothEye uses specialized hardware that is placed close to the eye in order to make an extremely accurate measurement. In addition, we use infrared illumination of the eye to mitigate variation of light conditions when the test is performed.

SmoothEye does not require calibration as it calculates absolute eye and head orientation using pattern recognition and matrix algebra. DSP technique also allows to get sub-pixel and sub-frame resolution even when using inexpensive CCD cameras. 
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When using SmoothEye you will put on special goggles that have built in infrared diodes and a video camera connected to a computer. You will then follow a moving object on the computer screen for about one minute while the video camera captures the eye movement and calculates your score. 

See our tips for using SmoothEye & How To Guide.
We also have Advanced Research Eye Tracker with 1000Hz sampling rate. 

SmoothEye uses advanced data processing methods while it allows to use relatively simple data collection hardware. The DSP is used in every stage of the processing. In the data collection: filtering, smoothing and oversampling of the data: Hermite spline, 2D Fourier filtering. The system uses pattern recognition to obtain initial position. The analysis part also intensively uses DSP:  filtering, data fitting, likelihood estimation, FFT convolution, blinking and saccade detection algorithm, matrix algebra and other techniques.  


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