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Cortorizing blinkk9/4/2023 ![]() ![]() In addition to circadian and time-awake influences, blink duration and KSS show a large variability among subjects. ![]() also demonstrated similar cyclic patterns for pAVR, nAVR, and %TEC. ![]() demonstrated that perceived sleepiness as measured by the Karolinska Sleepiness Scale (KSS) ( Akerstedt and Gillberg, 1990) follows the same cyclic behavior as mean performance and mean reaction time lapses in a PVT (psychomotor vigilance task). Blink duration also showed a strong circadian relationship, rising sharply after the subject's core body temperature reached a minimum. (2013) found that blink duration began to increase dramatically after subjects had been awake for 18 h, reaching a peak at 28 h and then falling to a local minimum at around 34 h of continuous wake time. Continuing themes in research on these ocular indices are significant individual differences in these indicators across subjects and consistent relationships among subjects to levels of perceived sleepiness and to time-of-day ( Ingre et al., 2006 Sandberg et al., 2011).īlink duration, usually measured in seconds or milliseconds, typically ranges from 0.1 s to 0.5 s, but can go as high as 2 or 3 s as subjects start to fall asleep. The ocular indices that can be easily extracted from EEG include blink rate ( BR), blink duration ( BD), blink amplitude deviation ratio ( BAR), positive amplitude velocity ratio ( pAVR), negative amplitude velocity ratio ( nAVR), percent time closed ( %TEC), as well as standard deviations, rates of change and ratios of these measures. This work investigates the identification of blinks and the extraction of standard ocular indices related to eye blinks from EEG and/or electrooculography (EOG) in an automated fashion. As large collections of EEG become available, these approaches enable the study of the distributions of ocular indices across many experimental conditions, diverse subject pools, and various disease conditions. ![]() Although direct measurement of eye activity is desirable, it is also possible to extract some types of ocular indices directly from EEG without additional experimental considerations. Eye movements also integrally relate to perception and attention. On a parallel track, human performance characterization uses ocular indices to characterize fatigue and other changes in subject state ( Schuri and von Cramon, 1981 Recarte et al., 2008 Benedetto et al., 2011 Wilkinson et al., 2013 McIntire et al., 2014 Marquart et al., 2015). Ĭontamination of electroencephalography (EEG) by eye and muscle activity is an ongoing challenge, and many techniques exist for the removal of these artifacts ( Jung et al., 2000 Delorme et al., 2007 Nolan et al., 2010 Mognon et al., 2011 Winkler et al., 2011). User documentation and examples appear at. Users can run BLINKER as a script or as a plugin for EEGLAB. The tools extract blinks, calculate common ocular indices, generate a report for each dataset, dump labeled images of the individual blinks, and provide summary statistics across collections. The toolbox, which is easy to use and can be applied to collections of data without user intervention, can automatically discover which channels or ICs capture blinks. We have implemented our algorithms in a freely available MATLAB toolbox called BLINKER. We also investigate dependence of ocular indices on task in a shooter study. To illustrate the use of our approach, we have applied the pipeline to a large corpus of EEG data (comprising more than 2000 datasets acquired at eight different laboratories) in order to characterize variability of certain ocular indicators across subjects. We have implemented an automated pipeline (BLINKER) for extracting ocular indices such as blink rate, blink duration, and blink velocity-amplitude ratios from EEG channels, EOG channels, and/or independent components (ICs). Further, the existence of EEG studies covering a variety of subjects and tasks provides opportunities for the community to better characterize variability of these measures across tasks and subjects.
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