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The emergence of off-screen interaction devices is bringing the field of virtual reality to a broad range of applications where virtual objects can be manipulated without the use of traditional peripherals. However, to facilitate object interaction, other stimuli such as haptic feedback are necessary to improve the user experience. To enable the identification of virtual 3D objects without visual feedback, a haptic display based on a vibrotactile glove and multiple points of contact gives users an enhanced sensation of touching a virtual object with their hands. Experimental results demonstrate the capacity of this technology in practical applications.

This review aims to evaluate the effectiveness of virtual reality-based interventions (VR-based interventions) on cognitive deficits in children with attention deficit hyperactivity disorder (ADHD). A systematic review and meta-analysis were performed according to the PRISMA statement and the Cochrane Handbook guidelines for conducting meta-analyses. The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used to assess the quality of the evidence. Clinical trials published up to 29 October 2020, were included. The meta-analysis included four studies, with a population of 125 participants with ADHD. The magnitude of the effect was large for omissions (SMD = −1.38; p = 0.009), correct hits (SMD = −1.50; p = 0.004), and perceptual sensitivity (SMD = −1.07; p = 0.01); and moderate for commissions (SMD = −0.62; p = 0.002) and reaction time (SMD = −0.67; p = 0.03). The use of VR-based interventions for cognitive rehabilitation in children with ADHD is limited. The results showed that VR-based interventions are more effective in improving sustained attention. Improvements were observed in attentional vigilance measures, increasing the number of correct responses and decreasing the number of errors of omission. No improvements were observed in impulsivity responses.

Automatic identification of negative stress is an unresolved challenge that has received great attention in the last few years. Many studies have analyzed electroencephalographic (EEG) recordings to gain new insights about how the brain reacts to both short- and long-term stressful stimuli. Although most of them have only considered linear methods, the heterogeneity and complexity of the brain has recently motivated an increasing use of nonlinear metrics. Nonetheless, brain dynamics reflected in EEG recordings often exhibit a multiscale nature and no study dealing with this aspect has been developed yet. Hence, in this work two nonlinear indices for quantifying regularity and predictability of time series from several time scales are studied for the first time to discern between visually elicited emotional states of calmness and negative stress. The obtained results have revealed the maximum discriminant ability of 86.35% for the second time scale, thus suggesting that brain dynamics triggered by negative stress can be more clearly assessed after removal of some fast temporal oscillations. Moreover, both metrics have also been able to report complementary information for some brain areas.

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