Visual Marking Across Eye Blinks

2012 ◽  
Author(s):  
David E. Irwin ◽  
Glyn W. Humphreys
Keyword(s):  
Eye Blinks ◽  
Visual Marking

scholarly journals Visual marking across eye blinks

2012 ◽  
Vol 20 (1) ◽  
pp. 128-134 ◽  
Author(s):  
David E. Irwin ◽  
Glyn W. Humphreys
Keyword(s):  
Eye Blinks ◽  
Visual Marking

Staring Down Death

Crisis ◽  
2016 ◽  
Vol 37 (3) ◽  
pp. 212-217 ◽  
Author(s):  
Thomas E. Joiner ◽  
Melanie A. Hom ◽  
Megan L. Rogers ◽  
Carol Chu ◽  
Ian H. Stanley ◽  
...  
Keyword(s):  
Suicide Risk ◽  
Clinical Utility ◽  
Blink Rate ◽  
Specific Task ◽  
Careful Planning ◽  
Eye Blink ◽  
Eye Blinks ◽  
Potential Clinical Utility ◽  
The Relationship

Abstract. Background: Lowered eye blink rate may be a clinically useful indicator of acute, imminent, and severe suicide risk. Diminished eye blink rates are often seen among individuals engaged in heightened concentration on a specific task that requires careful planning and attention. Indeed, overcoming one’s biological instinct for survival through suicide necessitates premeditation and concentration; thus, a diminished eye blink rate may signal imminent suicidality. Aims: This article aims to spur research and clinical inquiry into the role of eye blinks as an indicator of acute suicide risk. Method: Literature relevant to the potential connection between eye blink rate and suicidality was reviewed and synthesized. Results: Anecdotal, cognitive, neurological, and conceptual support for the relationship between decreased blink rate and suicide risk is outlined. Conclusion: Given that eye blinks are a highly observable behavior, the potential clinical utility of using eye blink rate as a marker of suicide risk is immense. Research is warranted to explore the association between eye blink rate and acute suicide risk.

Comparing IOR and Visual Marking in a Divided Search Task

2008 ◽  
Author(s):  
J. Devin Land ◽  
Matthew Kaiser ◽  
Andrew Everson ◽  
James F. Juola
Keyword(s):  
Search Task ◽  
Visual Marking

Detection of EEG-Based Eye-Blinks Using A Thresholding Algorithm

2021 ◽  
Vol 6 (4) ◽  
pp. 6-12
Author(s):  
Dang-Khoa Tran ◽  
Thanh-Hai Nguyen ◽  
Thanh-Nghia Nguyen
Keyword(s):  
Detection Algorithm ◽  
Time Frequency ◽  
Eye Blink ◽  
Eye Blinks ◽  
User Training ◽  
Electrical Potentials ◽  
Ocular Artifact ◽  
Blink Detection ◽  
Thresholding Algorithm ◽  
Frequency Properties

In the electroencephalography (EEG) study, eye blinks are a commonly known type of ocular artifact that appears most frequently in any EEG measurement. The artifact can be seen as spiking electrical potentials in which their time-frequency properties are varied across individuals. Their presence can negatively impact various medical or scientific research or be helpful when applying to brain-computer interface applications. Hence, detecting eye-blink signals is beneficial for determining the correlation between the human brain and eye movement in this paper. The paper presents a simple, fast, and automated eye-blink detection algorithm that did not require user training before algorithm execution. EEG signals were smoothed and filtered before eye-blink detection. We conducted experiments with ten volunteers and collected three different eye-blink datasets over three trials using Emotiv EPOC+ headset. The proposed method performed consistently and successfully detected spiking activities of eye blinks with a mean accuracy of over 96%.

scholarly journals Safe and sensible baseline correction of pupil-size data

2017 ◽  
Author(s):  
Sebastiaan Mathôt ◽  
Jasper Fabius ◽  
Elle van Heusden ◽  
Stefan Van der Stigchel
Keyword(s):  
Pupil Size ◽  
Statistical Power ◽  
Baseline Period ◽  
Experimental Manipulation ◽  
Pupillary Response ◽  
Baseline Correction ◽  
Data Loss ◽  
Eye Blinks ◽  
Random Fluctuations ◽  
Size Data

Measurement of pupil size (pupillometry) has recently gained renewed interest from psychologists, but there is little agreement on how pupil-size data is best analyzed. Here we focus on one aspect of pupillometric analyses: baseline correction, that is, analyzing changes in pupil size relative to a baseline period. Baseline correction is useful in experiments that investigate the effect of some experimental manipulation on pupil size. In such experiments, baseline correction improves statistical power by taking into account random fluctuations in pupil size over time. However, we show that baseline correction can also distort data if unrealistically small pupil sizes are recorded during the baseline period, which can easily occur due to eye blinks, data loss, or other distortions. Divisive baseline correction (corrected pupil size = pupil size / baseline) is affected more strongly by such distortions than subtractive baseline correction (corrected pupil size = pupil size - baseline). We make four recommendations for safe and sensible baseline correction of pupil-size data: 1) use subtractive baseline correction; 2) visually compare your corrected and uncorrected data; 3) be wary of pupil-size effects that emerge faster than the latency of the pupillary response allows (within ±220 ms after the manipulation that induces the effect); and 4) remove trials on which baseline pupil size is unrealistically small (indicative of blinks and other distortions).

Conditioned Middle Ear Muscle Tinnitus

1982 ◽  
Vol 91 (3) ◽  
pp. 330-331 ◽  
Author(s):  
Mary E. Collard ◽  
Cynthia A. Wagner ◽  
Fred R. Tingwald
Keyword(s):  
Muscle Contraction ◽  
Middle Ear ◽  
Muscle Response ◽  
Eye Blinks

A case of bilateral middle ear muscle contraction tinnitus associated with eye blinks is presented. It is hypothesized that the association represents a conditioned middle ear muscle response.

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