Background: An effective method that is easy to implement and widely applicable for improving driving performance and reducing driving risks remains a challenge. Although fragrances are widely used in daily driving, there is a gap between empirical research on everyday blended fragrances and functional fragrances clinical reports. In this study, a deliberately chosen blend of scent without overtly stimulating or functional proven evidence was tested for its potential to enhance performance in a driving environment.Method: Thirty qualified young drivers were recruited to participate in the experiment. They were asked to watch a 15‐min first‐person perspective driving video to simulate a driving environment and then complete questionnaires and three sets of behavioral experiments while their brain activity was monitored by EEG.Result: Participants in the scented environment exhibited statistically significant advantages in two cognitive tasks during behavioral measures. These findings were effectively supported by the EEG data, showing that beta waves exhibited more activity in the occipital and prefrontal cortex, enhanced theta waves were observed in the prefrontal cortex, and the TAB index characterizing driving fatigue was suppressed in the prefrontal cortex.Conclusion: This empirical evidence highlights the potential of pleasant, natural, and blended scents in enhancing driving performance, suggesting that promoting the aromatherapy while driving as an easily applicable approach in daily life seems justified and expands the application of aromatherapy in daily life.

Background: COVID-19 has spread worldwide and generated tremendous stress on human beings. Unfortunately, it is often hard for distressed individuals to access mental health services under conditions of restricted movement or even lockdown. Objective: The study first aims to develop an online digital intervention package based on a commercially released coloring game. The second aim is to test the effectiveness of difference intervention packages for players to increase subjective well-being (SWB) and reduce anxiety during the pandemic. Methods: An evidence-based coloring intervention package was developed and uploaded to an online coloring game covering almost 1.5 million players worldwide in January 2021. Players worldwide participated to color either 4 rounds of images characterized by awe, pink, nature, and blue or 4 rounds of irrelevant images. Participants' SWB and anxiety and the perceived effectiveness of the game in reducing anxiety (subjective effectiveness [SE]) were assessed 1 week before the intervention (T1), after the participants completed pictures in each round (T2-T5), and after the intervention (T6). Independent 2-tailed t tests were conducted to examine the general intervention (GI) effect and the intervention effect of each round. Univariate analysis was used to examine whether these outcome variables were influenced by the number of rounds completed. Results: In total, 1390 players worldwide responded and completed at least 1 assessment. Overall, the GI group showed a statistical significantly greater increase in SWB than the general control (GC) group (N=164, t162=3.59, Cohen d=0.59, 95% CI 0.36-1.24, P<.001). Compared to the control group, the best effectiveness of the intervention group was seen in the awe round, in which the increase in SWB was significant (N=171, t169=2.51, Cohen d=0.39, 95% CI 0.10-0.82, P=.01), and players who colored all 4 pictures had nearly significant improvements in SWB (N=171, F4,170=2.34, partial ŋ2=0.053, P=.06) and a significant decrease in anxiety (N=171, F4,170=3.39, partial ŋ2=0.075, P=.01). Conclusions: These data indicate the effectiveness of online psychological interventions, such as coloring games, for mental health in the specific period. They also show the feasibility of applying existing commercial games embedded with scientific psychological interventions that can fill the gap in mental crises and services for a wider group of people during the pandemic. The results would inspire innovations to prevent the psychological problems caused by public emergencies and encourage more games, especially the most popular ones, to take more positive action for the common crises of humankind.

As a convenient device for observing neural activity in the natural environment, portable EEG technology (PEEGT) has an extensive prospect in expanding neuroscience research into natural applications. However, unlike in the laboratory environment, PEEGT is usually applied in a semiconstrained environment, including management and engineering, generating much more artifacts caused by the subjects’ activities. Due to the limitations of existing artifacts annotation, the problem limits PEEGT to take advantage of portability and low-test cost, which is a crucial obstacle for the potential application of PEEGT in the natural environment. This paper proposes an intelligent method to identify two leading antecedent causes of EEG artifacts, participant’s blinks and head movements, and annotate the time segments of artifacts in real time based on computer vision (CV). Furthermore, it changes the original postprocessing mode based on artifact signal recognition to the preprocessing mode based on artifact behavior recognition by the CV method. Through a comparative experiment with three artifacts mark operators and the CV method, we verify the effectiveness of the method, which lays a foundation for accurate artifact removal in real time in the next step. It enlightens us on how to adopt computer technology to conduct large-scale neurotesting in a natural semiconstrained environment outside the laboratory without expensive laboratory equipment or high manual costs.

Mild cognitive impairment (MCI) is a very unstable transition state between normal aging and dementia. Due to lack of accurate treatment and with high risk of dementia transformation, early diagnosis and intervention of MCI has become very important. In view of the limitations of current MCI screening methods dominated by neuropsychological testing and intervention measures dominated by traditional occupational therapy (OT), this paper proposes one intelligent framework based on online chess and cards games, which integrates online behaviour big data's MCI screening and game cognitive OT methods. Thus, a new method of screening and rehabilitation intervention for potential patients with MCI will be realised through the routine tracks of the actions online.

[This corrects the article DOI: 10.2196/37026.].