Cardiopulmonary baroreceptors affect reflexive startle eye blink

2009 ◽  
Vol 98 (5) ◽  
pp. 587-593 ◽  
Author(s):  
S. Richter ◽  
A. Schulz ◽  
J. Port ◽  
T.D. Blumenthal ◽  
H. Schächinger
Keyword(s):  
Eye Blink ◽  
Cardiopulmonary Baroreceptors

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.

Phase of menstrual cycle modulates eye-blink startle potentiation and magnitude

1996 ◽  
Author(s):  
Rachel Manber ◽  
Keith W. Burton ◽  
John J. Allen ◽  
Alfred W. Kaszniak
Keyword(s):  
Menstrual Cycle ◽  
Eye Blink ◽  
Startle Potentiation

scholarly journals Eye-blink artifact removal from single channel EEG with k-means and SSA

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ajay Kumar Maddirala ◽  
Kalyana C Veluvolu
Keyword(s):  
Machine Learning ◽  
Single Channel ◽  
Learning Algorithm ◽  
Singular Spectrum Analysis ◽  
Machine Learning Algorithm ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Unsupervised Machine Learning ◽  
Eye Blink ◽  
Blink Artifact

AbstractIn recent years, the usage of portable electroencephalogram (EEG) devices are becoming popular for both clinical and non-clinical applications. In order to provide more comfort to the subject and measure the EEG signals for several hours, these devices usually consists of fewer EEG channels or even with a single EEG channel. However, electrooculogram (EOG) signal, also known as eye-blink artifact, produced by involuntary movement of eyelids, always contaminate the EEG signals. Very few techniques are available to remove these artifacts from single channel EEG and most of these techniques modify the uncontaminated regions of the EEG signal. In this paper, we developed a new framework that combines unsupervised machine learning algorithm (k-means) and singular spectrum analysis (SSA) technique to remove eye blink artifact without modifying actual EEG signal. The novelty of the work lies in the extraction of the eye-blink artifact based on the time-domain features of the EEG signal and the unsupervised machine learning algorithm. The extracted eye-blink artifact is further processed by the SSA method and finally subtracted from the contaminated single channel EEG signal to obtain the corrected EEG signal. Results with synthetic and real EEG signals demonstrate the superiority of the proposed method over the existing methods. Moreover, the frequency based measures [the power spectrum ratio ($$\Gamma $$ Γ ) and the mean absolute error (MAE)] also show that the proposed method does not modify the uncontaminated regions of the EEG signal while removing the eye-blink artifact.

scholarly journals Mask-Type Sensor for Pulse Wave and Respiration Measurements and Eye Blink Detection

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4895
Author(s):  
Thanh-Vinh Nguyen ◽  
Masaaki Ichiki
Keyword(s):  
Pulse Wave ◽  
Pressure Change ◽  
Frequency Component ◽  
High Frequency Component ◽  
Sensing Element ◽  
Eye Blink ◽  
Mask Type ◽  
Blink Detection ◽  
The Subject ◽  
Air Bag

This paper reports on a mask-type sensor for simultaneous pulse wave and respiration measurements and eye blink detection that uses only one sensing element. In the proposed sensor, a flexible air bag-shaped chamber whose inner pressure change can be measured by a microelectromechanical system-based piezoresistive cantilever was used as the sensing element. The air bag-shaped chamber is fabricated by wrapping a sponge pad with plastic film and polyimide tape. The polyimide tape has a hole to which the substrate with the piezoresistive cantilever adheres. By attaching the sensor device to a mask where it contacts the nose of the subject, the sensor can detect the pulses and eye blinks of the subject by detecting the vibration and displacement of the nose skin caused by these physiological parameters. Moreover, the respiration of the subject causes pressure changes in the space between the mask and the face of the subject as well as slight vibrations of the mask. Therefore, information about the respiration of the subject can be extracted from the sensor signal using either the low-frequency component (<1 Hz) or the high-frequency component (>100 Hz). This paper describes the sensor fabrication and provides demonstrations of the pulse wave and respiration measurements as well as eye blink detection using the fabricated sensor.

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