Visual evoked potential (VEP) has been used as an alternative method to assess visual acuity objectively, especially in non-verbal infants and adults with low intellectual abilities or malingering. By sweeping the spatial frequency of visual stimuli and recording the corresponding VEP, VEP acuity can be defined by analyzing electroencephalography (EEG) signals. This paper presents a review on the VEP-based visual acuity assessment technique, including a brief overview of the technique, the effects of the parameters of visual stimuli, and signal acquisition and analysis of the VEP acuity test, and a summary of the current clinical applications of the technique. Finally, we discuss the current problems in this research domain and potential future work, which may enable this technique to be used more widely and quickly, deepening the VEP and even electrophysiology research on the detection and diagnosis of visual function.

Nowadays, more people tend to go to bed late and spend their sleep time with various electronic devices. At the same time, the BCI (brain–computer interface) rehabilitation equipment uses a visual display, thus it is necessary to evaluate the problem of visual fatigue to avoid the impact on the training effect. Therefore, it is very important to understand the impact of using electronic devices in a dark environment at night on human visual fatigue. This paper uses Matlab to write different color paradigm stimulations, uses a 4K display with an adjustable screen brightness to jointly design the experiment, uses eye tracker and g.tec Electroencephalogram (EEG) equipment to collect the signal, and then carries out data processing and analysis, finally obtaining the influence of the combination of different colors and different screen brightness on human visual fatigue in a dark environment. In this study, subjects were asked to evaluate their subjective (Likert scale) perception, and objective signals (pupil diameter, θ + α frequency band data) were collected in a dark environment (<3 lx). The Likert scale showed that a low screen brightness in the dark environment could reduce the visual fatigue of the subjects, and participants preferred blue to red. The pupil data revealed that visual perception sensitivity was more vulnerable to stimulation at a medium and high screen brightness, which is easier to deepen visual fatigue. EEG frequency band data concluded that there was no significant difference between paradigm colors and screen brightness on visual fatigue. On this basis, this paper puts forward a new index—the visual anti-fatigue index, which provides a valuable reference for the optimization of the indoor living environment, the improvement of satisfaction with the use of electronic equipment and BCI rehabilitation equipment, and the protection of human eyes.

The series of Kinect, which has the third-generation device now, is a low-cost scene information collection sensor to capture the color information and depth information from the scene at the same time. Due to the hardware structure of the sensor, the color image and the depth image shot by Kinect is not homologous. In this article, we compared the hardware parameters of different Kinect three generations of products, and we have calibrated the RGB camera and IR (infrared) camera of Azure Kinect, so as to the internal parameters and external parameters between the RGB camera and IR camera, and align the color image and depth image taken with Azure Kinect. At the same time, we evaluated the shooting accuracy and stability of Azure Kinect’s depth camera, and conducted experiments on the relationship between shooting error and measurement distance on three generations of products, also the parameter optimization suggestions are provided. In addition, according to different usage scenarios, we recommend the shooting parameters and the image effective range of the sensor simultaneously.

Bearings are key components in mechanical equipment, which are widely used in various fields such as automobiles and airplanes. Aiming at the analysis of vibration signal processing under the variable speed condition of bearings, this paper proposes a new bearing fault diagnosis method, which firstly resamples the vibration signals in the angular domain, and then converts the resampled signals into images by the relative position matrix method, and finally uses the transfer learning to automatically extract the features and classify them. To verify the effectiveness of the method, it is tested on the Case Western Reserve University bearing fault dataset and University of Ottawa bearing fault dataset respectively. Compared with other time series to image methods (Recurrence Plot, etc) and other pre-trained models (GoogLeNet, etc), the proposed method has some advantages in terms of accuracy, image generation time, training time, and testing time. The accuracy of the proposed method in this paper reaches more than 90%, which suggests its potential effectiveness in the classification of bearing faults under variable speed working conditions.

With the development of modern technology, many people work for a long time around various artificial light sources and electronic equipment, causing them to feel discomfort in their eyes and even eye diseases. The industry currently lacks an objective quantitative environmental–visual comfort index that combines subjective and objective indicators. For this experiment, objective eye movement and electroencephalogram (EEG) signals were collected in combination with a subjective questionnaire survey and a preference inquiry for comprehensive data mining. Finally, the results on a Likert scale show that high screen brightness can reduce the visual fatigue of subjects under high illuminance and high correlated color temperature (CCT). Pupil data show that, under medium and high ambient illuminance, visual perception sensitivity is more likely to be stimulated, and visual fatigue is more likely to deepen. EEG data show that visual fatigue is related to illuminance and screen brightness. On this basis, this study proposes a new evaluation index, the visual comfort level (0.6404 average at a low screen brightness, 0.4218 average at a medium screen brightness, and 0.5139 average at a high screen brightness), where a higher score for the visual comfort level represents a better visual experience. The visual comfort level provides a useful reference for enhancing the processing of multi-dimensional and biomedical signals and protecting the eyes.