Cognitive control is often perplexing to elucidate and can be easily influenced by emotions. Understanding the individual cognitive control level is crucial for enhancing VR interaction and designing adaptive and self-correcting VR/AR applications. Emotions can reallocate processing resources and influence cognitive control performance. However, current research has primarily emphasized the impact of emotional valence on cognitive control tasks, neglecting emotional arousal. In this study, we comprehensively investigate the influence of emotions on cognitive control based on the arousal-valence model. A total of 26 participants are recruited, inducing emotions through VR videos with high ecological validity and then performing related cognitive control tasks. Leveraging physiological data including EEG, HRV, and EDA, we employ classification techniques such as SVM, KNN, and deep learning to categorize cognitive control levels. The experiment results demonstrate that high-arousal emotions significantly enhance users' cognitive control abilities. Utilizing complementary information among multi-modal physiological signal features, we achieve an accuracy of 84.52% in distinguishing between high and low cognitive control. Additionally, time-frequency analysis results confirm the existence of neural patterns related to cognitive control, contributing to a better understanding of the neural mechanisms underlying cognitive control in VR. Our research indicates that physiological signals measured from both the central and autonomic nervous systems can be employed for cognitive control classification, paving the way for novel approaches to improve VR/AR interactions.

Abstract For autistic children with slow language function, it is a classic and easy way to understand the development of their cognitive ability through simple painting experiments. Due to the lack of professional evaluators for painting assessment of autistic children, this article research and implement an intelligent assessment system for child autism through recognition of portrait sketch components. A portrait sketch database is constructed with the sample size of 30,400 after data expansion. The data consists of two formats: stroke vector sequence and 2D image. Then we propose a joint model coupled with LSTM and CNN features to automatically segment the portrait sketch components. It can perform better segmentation for exaggerated proportion and incomplete components samples. Finally, according to the evaluation criteria of the painting, we design an assessment model for child autism. The experiments are conducted in cooperation with relevant rehabilitation institutions to verify the effectiveness of the system. The analysis results show that our painting assessment system has a good ability to identify autistic tendencies. It can accurately evaluate children's autistic tendencies through “draw‐a‐man” experiments.

The ecological validity of emotion-inducing scenarios is essential for emotion research. In contrast to the classical passive induction paradigm, immersive VR fully engages the psychological and physiological components of the subject, which is considered an ecologically valid paradigm for studying emotion. Several studies investigate the emotional responses to different VR tasks or games using subjective scales. However, little research regards VR as an eliciting material, especially when systematically analyzing emotional processes in VR from a neurophysiological perspective. To fill this gap and scientifically evaluate VR's ability to be used as an active method for emotion elicitation, we investigate the dynamic relationship between explicit information (subjective evaluations) and implicit information (objective neurophysiological data). A total of 28 participants are enlisted to watch eight VR videos while their SAM/IPQ scores and EEG data are recorded simultaneously. In ecologically valid scenarios, the subjective results demonstrate that VR has significant advantages for evoking emotion in arousal-valence. This conclusion is backed by our examination of objective neurophysiological evidence that VR videos effectively induce high-arousal emotions. In addition, we obtain features of critical channels and frequency oscillations associated with emotional valence, thereby validating previous research in more lifelike circumstances. In particular, we discover hemispheric asymmetry in the occipital region under high and low emotional arousal, which adds to our understanding of neural features and the dynamics of emotional arousal. As a result, we successfully integrate EEG and VR to demonstrate that VR is more pragmatic for evoking natural feelings and is beneficial for emotional research. Our research has set a precedent for new methodologies of using VR induction paradigms to acquire a more reliable explanation of affective computing.

In recent years, virtual reality (VR) based training has greatly changed surgeons learning mode. It can simulate the surgery from the visual, auditory, and tactile aspects. VR medical simulator can greatly reduce the risk of the real patient and the cost of hospitals. Laparoscopic cholecystectomy is one of the typical representatives in minimal invasive surgery (MIS). Due to the large incidence of cholecystectomy, the application of its VR-based simulation is vital and necessary for the residents' surgical training. In this paper, we present a VR simulation framework based on position-based dynamics (PBD) for cholecystectomy. To further accelerate the deformation of organs, PBD constraints are solved in parallel by a graph coloring algorithm. We introduce a bio-thermal conduction model to improve the realism of the fat tissue electrocautery. Finally, we design a hybrid multi-model connection method to handle the interaction and simulation of the liver-gallbladder separation. This simulation system has been applied to laparoscopic cholecystectomy training in several hospitals. From the experimental results, users can operate in real-time with high stability and fidelity. The simulator is also evaluated by a number of digestive surgeons through preliminary studies. They believed that the system can offer great help to the improvement of surgical skills.