The consequences of eye tracking on brain and heart coherence.

When the eye uses the brain and heart, the cardiovascular and nervous systems integrate and interact. Because changes in retinal microcirculation are independent predictors of cardiovascular events, the eye serves as a "display" to the cardiovascular system and brain. The eye, which has two circulatory systems and a rich vascular supply, is a prime candidate for this study and benefits from early damage to the target organ. Eye movements performed during the visual search pose a challenge in identifying critical points in the eye scene. Because it uses different brain pathways and relates to the cardiac cycle, humans' ability to spot anomalies under challenging circumstances means they are always needed for visual search. ECG (electrocardiogram), electroencephalogram (EEG), and eye tracking can improve visual search training and attention-tracking performance. EEG data can also be analyzed in real time using eye-tracking technology. Previous work has discussed the EEG or ECG concerning attraction during visual search. The eyeball's movement combined with the ECG in the previous investigation and introduced large electroencephalographic (EEG) artifacts. This assessment aims to (a) identify brain–heart coherent features influenced by the visual search task and (b) discover the behavior of EEG frequency bands and heart rate variability (HRV) features. EEG and ECG were used to analyze and predict inattention in individuals during a visual search task. The EEG determines human brain function and considers to detect the variability in the EEG frequency band. The work proposed a visual search task with EEG and ECG analysis. Five participants recorded EEG and ECG recordings in three different scenarios: rest, gaze tracking, and normal. Statistical evaluation was used to compare EEG and ECG characteristics and Pearson's correlation was employed for statistical analysis. Statistical ANOVA analysis revealed statistically significant (p > 0.05) differences between theta (F3) and alpha (F3) EEG and ECG features, as well as between theta (F4) and alpha (F4) EEG and ECG features. Additionally, alpha (F3) and theta (F3) were significant in the heart rate variability index (rMSSD), which monitored activity under eye tracking. There was also a significant difference between alpha (F3) and mean HR. Pearson's correlation between ECG and EEG shows that theta (O1) and alpha (O1) correlate with LF/HF and alpha (F3) and theta (F3) with rMSSD. Theta (F3) and mean heart rate were also correlated. Observing the above ECG and EEG characteristics can improve and control treatment options for conditions like neurovascular instability (NCVI), characterized by age-related changes in blood pressure and increased cerebral and cardiac leukoaraiosis. [ABSTRACT FROM AUTHOR]