Driver drowsiness detection methods using EEG signals: a systematic review

Electroencephalography (EEG) is a complex signal that may require several years of training, advanced signal processing, and feature extraction methodologies to interpret correctly. Recently, many methods have been used to extract and classify EEG data. This study reviews 62 papers that used EEG signals to detect driver drowsiness, published between January 2018 and 2022. We extract trends and highlight interesting approaches from this large body of literature to inform future research and formulate recommendations. To find relevant papers published in scientific journals, conferences, and electronic preprint repositories, researchers searched major databases covering the domains of science and engineering. For each investigation, many data items about (1) the data, (2) the channels used, (3) the extraction and classification procedure, and (4) the outcomes were extracted. These items were then analyzed one by one to uncover trends. Our analysis reveals that the amount of EEG data used across studies varies. We saw that more than half the studies used simulation driving experimental. About 21% of the studies used support vector machine (SVM), while 19% used convolutional neural networks (CNN). Overall, we can conclude that drowsiness and fatigue impair driving performance, resulting in drivers who are more exposed to risky situations.

Algorithm Development for Full Gaps of Landsat 7 Images

      Landsat7 of Enhanced thematic mapper plus (ETM+) was launched on April 15,  1999. Four years later, images start degrading due to the scan line corrector (SLC). SLC is a malfunction that results in pixel gaps in images captured by the sensor of Landsat7. The pixel gap regions extend from about one pixel near the image center and reach up to about 14 pixels in width near the image edge. The shape of this loss is like a zigzag line; however, there are different studies about repairing these gaps. The challenge of all studies depends on retrieving inhomogeneous areas because the homogenous area can be retrieved quickly depending on the surrounding area. This research focuses on filling these gaps by utilizing pixels around them gaps. Pixels from different satellites with the same resolution at the approximate equal date and exact location would be utilized. Mean and standard deviation were used in gap pixel predicting. For complete pixels gap predicting, an image registration should be applied for predicted a good result—image registration comprised of geometric and radiometric registration. Translation and rotation was the main effect of geometric registration, while pixel tone was mainly related to radiometric registration. Two images of Landsat8 (before and after) with nearly the date of Landsat 7 were used. The fidelity criteria (mean square error and mean absolute error) were utilized to evaluate the results. The results showed a good prediction of the gap pixels in the Landsat 7 image, considering the geometric and radiometric parts.

Serotonin stimulates adenosine 3',5'-monophosphate accumulation in parathyroid adenoma

The effect of serotonin on cAMP accumulation in parathyroid adenoma tissue from patients with primary hyperparathyroidism was studied in vitro. Incubation with 10(-5) M serotonin elicited a marked increase (of 90--150%) in cAMP content in slices of parathyroid adenoma tissue. This stimulatory effect of serotonin was already apparent after 2 min of incubation; stimulation by serotonin was dose dependent, with the highest stimulation being achieved at 10(-4) M serotonin. The serotonin antagonists, methylsergide and cinanserin, in concentrations equimolar to serotonin completely blocked the stimulatory effect of serotonin on cAMP increase. The serotonin content in surgically removed parathyroid adenoma tissue, as determined by fluorometric assay, was 6.4 +/- 1.2 pmol/mg wet wt (approximately 0.8 x 10(-5) M). The present observations demonstrate that parathyroid adenoma tissue has a high content of serotonin, and serotonin stimulates cAMP accumulation in this tissue. Since cAMP acts as a mediator of parathyroid hormone (PTH) release, our results suggest that serotonin could be one of the factors regulating PTH secretion and/or contributing to PTH hypersecretion in various forms of primary hyperparathyroidism.