Analysis on the Correlation Degree between the Driver’s Reaction Ability and Physiological Parameters

In this paper, the correlation degree between driver’s reaction time and the physiological signal is analyzed. For this purpose, a large number of road experiments are performed using the biopac and the reaction time test systems to collect data. First, the electroencephalograph (EEG) signal is processed by using the fast Fourier and the inverse Fourier transforms. Then, the power spectrum densities (PSD) of α, β, δ, and EEG wave are calculated by Welch procedure. The average power of the power spectrum of α, β, and θ is calculated by the biopac software and two ratio formulas, (α+θ)/β and α/β, are selected to be the impact factors. After that the heart rate and the standard deviation of RR interval are calculated from the electrocardiograph (ECG) signal. Lastly, the correlation degree between the eight impact factors and the reaction time are analyzed based on the grey correlation analysis. The results demonstrate that α/β has the greatest correlation to the reaction time except EEG-PSD. Furthermore, two mathematical models for the reaction time-driving time and the α/β-driving time are developed based on the Gaussian function. These mathematical models are then finally used to establish the functional relation of α/β-the reaction time

Imagining density distribution of molecular orbitals in IR+XUV co-rotating circular laser fields by frequency-domain theory

We have investigated the angle-resolved ATI spectrum of oriented molecules in the IR+XUV co-rotating circular laser fields. According to the different roles of IR and XUV laser in the ionization process, we purposefully adjust the photon energy of XUV and the intensity of IR laser to make the ionization spectrum of the molecule distributed in a suitable momentum region. Moreover, under the same laser conditions, the background fringes in the ionization spectrum of the molecule can be removed by using the ionization spectrum of the atom with the same ionization energy as the molecule, so that the molecular orbital density distribution in the suitable momentum region can be obtained. That is, for any unknown molecule, as long as the ionization energy of the molecule can be measured, the density distribution of the molecular orbital can be imaged in a definite momentum region by adjusting the laser field conditions, which may shed light on the experimental detection of molecular orbitals

The impact of SARS-Cov-2 infection on the periocular injection pain and hypersensitive reaction to botulinum toxin type A: results from clinical questionnaires

BackgroundThe COVID-19 pandemic has brought about significant changes in the medical field, yet the use of botulinum toxin type A has remained uninterrupted. Plastic surgeons must carefully consider the timing of administering botulinum toxin type A to patients who have recovered from COVID-19.MethodsA questionnaire survey was conducted among patients who had contracted and recovered from SARS-CoV-2 within a month. The survey aimed to investigate various indicators in patients who had received botulinum toxin A injections at the same site before and after their infection, including pain scores and allergic reactions and the occurrence of complications.ResultsThe pain scores of patients who contracted SARS-CoV-2 infection between 14-21 days post-infection exhibited significant variation from previous injections. However, patients who contracted the infection between 22-28 days post-infection did not exhibit significant variation from previous injections. Furthermore, the incidence of allergic reactions and complications following botulinum toxin injection within one month after contracting the infection did not significantly differ from that observed prior to infection.ConclusionAdministering botulinum toxin type A three weeks after COVID-19 recovery is a justifiable and comparatively secure approach

Research on the Relationship between Reaction Ability and Mental State for Online Assessment of Driving Fatigue

Background: Driving fatigue affects the reaction ability of a driver. The aim of this research is to analyze the relationship between driving fatigue, physiological signals and driver’s reaction time. Methods: Twenty subjects were tested during driving. Data pertaining to reaction time and physiological signals including electroencephalograph (EEG) were collected from twenty simulation experiments. Grey correlation analysis was used to select the input variable of the classification model. A support vector machine was used to divide the mental state into three levels. The penalty factor for the model was optimized using a genetic algorithm. Results: The results show that α/β has the greatest correlation to reaction time. The classification results show an accuracy of 86%, a sensitivity of 87.5% and a specificity of 85.53%. The average increase of reaction time is 16.72% from alert state to fatigued state. Females have a faster decrease in reaction ability than males as driving fatigue accumulates. Elderly drivers have longer reaction times than the young. Conclusions: A grey correlation analysis can be used to improve the classification accuracy of the support vector machine (SVM) model. This paper provides basic research that online detection of fatigue can be performed using only a simple device, which is more comfortable for users