Studies using source localization results have shown that cortical involvement increased in treadmill walking with brain–computer interface (BCI) control. However, the reorganization of cortical functional connectivity in treadmill walking with BCI control is largely unknown. To investigate this, a public dataset, a mobile brain–body imaging dataset recorded during treadmill walking with a brain–computer interface, was used. The electroencephalography (EEG)-coupling strength of the between-region and within-region during the continuous self-determinant movements of lower limbs were analyzed. The time–frequency cross-mutual information (TFCMI) method was used to calculate the coupling strength. The results showed the frontal–occipital connection increased in the gamma and delta bands (the threshold of the edge was >0.05) during walking with BCI, which may be related to the effective communication when subjects adjust their gaits to control the avatar. In walking with BCI control, the results showed theta oscillation within the left-frontal, which may be related to error processing and decision making. We also found that between-region connectivity was suppressed in walking with and without BCI control compared with in standing states. These findings suggest that walking with BCI may accelerate the rehabilitation process for lower limb stroke.

A complex command and control task was selected as the test task, which included observing the overall and local situation, the interactive operation and situation display of detection equipment, the erection and launch of air defense equipment, and the check and display status. The disadvantages of the traditional two-dimensional display interactive system include poor intuitiveness, insufficient information display dimension and complicated interactive operation. The mixed reality display interaction system can avoid these problems well and has the advantages of good portability and high efficiency, but this display interaction system has the problem of high cognitive load. Therefore, based on the premise of completing the same complex task, how to select and improve the display interaction system has become a problem worthy of urgent research. Based on the same complex command and control task, this paper compared the traditional two-dimensional display interaction system and the mixed reality display interaction system and analyzed the performance and cognitive load of the two systems. It is concluded that when completing the same task, the performance of the mixed reality display interaction system is significantly higher than that of the traditional two-dimensional display interaction system, but the cognitive load is slightly higher than that of the traditional two-dimensional display. Cognitive load was reduced while task performance was improved through multi-channel improvements to the mixed reality display interaction system. Considering the effects of performance and cognitive load, the improved multi-channel mixed reality display interaction system is superior to the unimproved mixed reality display interaction system and the two-dimensional display interaction system. This research provides an improvement strategy for the existing display interaction system and provides a new display interaction mode for future aerospace equipment and multi-target, multi-dimensional command and control tasks in war.

The development of miniaturized electronic devices is highly dependent on precision manufacturing techniques. To achieve device miniaturization, material removal and processing accuracy down to the submicrometer or even nanometer level are required. The precision machining of the mass block, a key component of the silicon micro-gyroscope, is taken as a reference. To achieve the precision positioning function of the micro-gyroscope, the mass at a certain position of the Si-based mass block must be precisely controlled. Therefore, the ultra-fine quantitative removal process of silicon materials is studied. A femtosecond laser processing system is constructed, and the evolution of micro–nanostructure and etching depth on the silicon surface is explored. An ultra-fine quantitative removal process is developed to achieve quantitative removal of different etching depths on the silicon surface. The experimental results show that the minimum removal thickness can be 0.502 µm. The processing index requirement for a silicon surface removal thickness of less than 0.001 mm has been fulfilled. It is critical to resolve the issue of high-quality manufacturing of miniaturized silicon-based devices.