Preliminary Study of Short-Term Visual Perceptual Training Based on Virtual Reality and Augmented Reality in Postoperative Strabismic Patients

The study aimed to explore the potential effect of short-term visual perceptual training based on virtual reality (VR) and augmented reality (AR) platforms in postoperative strabismic patients. We enrolled 236 postoperative strabismic patients, among whom 111 patients received VR-based training, and 125 patients received AR-based training. The stereoacuity of 1.5 m and dynamic stereopsis were improved by VR training; meanwhile, AR training exhibited more improvement in stereoacuity of 0.8 and 1.5 m, dynamic and coarse stereopsis. It was suggested that the visual perceptual training based on VR and AR technology can be potentially applied in postoperative strabismus treatment to promote the recovery of binocular vision.

What the Metaverse Is (Really) and Why We Need to Know About It

Major technology companies are investing significant sums of money in the creation of the metaverse whose main feature will be the fusion between the virtual world and the physical world. To allow this possibility is one of the less obvious features of the metaverse: the metaverse works like our minds. This ability makes the metaverse a significantly different technology from its predecessors. If television and social media are persuasive technologies, because of their ability to influence people's attitudes and behaviors, the metaverse is instead a transformative technology, capable of modifying what people think reality is. To achieve this goal, the technologies of the metaverse hack different key cognitive mechanisms: the experience of being in a place and in a body, the processes of brain-to-brain attunement and synchrony, and the ability of experiencing and inducing emotions. Clearly, these possibilities define totally new scenarios with positive and negative outcomes. Educating ourselves as to its promise, and the challenges it may present, is a necessity. This requires a "humane," integrated, and multidisciplinary approach, with stakeholders at the supranational level joining in the conversation.

COVID Feel Good: Evaluation of a Self-Help Protocol to Overcome the Psychological Burden of the COVID-19 Pandemic in a German Sample

The COVID-19 pandemic has severe consequences for physical as well as mental well-being. In times of restricted social contact, online self-help programs offer a low-threshold first aid to cope with the psychological burden. This current study evaluates the online self-help protocol “COVID Feel Good” in a German sample. The multicentric study was designed as a single cohort with a waiting list control condition. The convenience sample consisted of 38 German individuals who experienced at least two months of restrictions during the COVID-19 pandemic. The 7-day self-help protocol included the VR video “Secret Garden” as well as a social or cognitive exercise each day. General distress, depression, anxiety, stress, and hopelessness were assessed as primary outcomes. Social connectedness and fear of coronavirus were measured as secondary outcomes. Results showed a significant decrease in all primary outcomes except for hopelessness. Furthermore, the results indicated a significant improvement in social connectedness. Treatment effects on general distress, depression, stress, and anxiety persisted for two weeks after participation. The present study indicates that VR-based self-help protocols can mitigate the psychological burden associated with the pandemic, supporting recent findings.

Zero Sales Resistance: The Dark Side of Big Data and Artificial Intelligence

Big data (BD) is the hue and cry of modern science and society. The impact of such data deluge is huge and far reaching for both science and society. Moreover, given the effort required for collecting and analyzing these data, artificial intelligence (AI) has replaced the human mind in accomplishing the enormous task of deriving insight out of the information. In this article, we analyze the role of BD and AI in steering the world population toward the state of Zero Sales Resistance (ZSR): the inability to exert critical judgment over the most seductive aspects of the aforementioned data deluge. Moreover, we discuss the alarming consequences of presenting the merging of BD and AI as a universal panacea even if, to date, they have proven far more efficient for predicting human decisions and behaviors (predictive analytics) than for solving the most critical problems in science and society. Why? Our answer is simple. The causal structures associated with such challenges command a detailed understanding of the underlying mechanisms (causal explanation), typically acting nonlinearly and on a broad range of scales in space and time. In contrast, personality and behavior can be predicted with no need of a microscopic theory and understanding of the brain-mind system (empirical prediction). This is a direct consequence of the fact that our mind, at least for the intuitive level, uses the same prediction techniques applied by AI (bayesian predictions based on our experience). However, prediction is not explanation, and without joining them it will be impossible to achieve a major advance in our understanding of complex systems.

Combat-Related Post-traumatic Stress Disorder: A Case Report of Virtual Reality Graded Exposure Therapy With Physiological Monitoring in a U.S. Navy Officer and a U.S. Army Officer

The U.S. Department of Defense (DoD) and the Department of Veterans Affairs (DVA) seek to enhance the efficacy of treatments for warriors with post-traumatic stress disorder (PTSD) secondary to their combat deployments to Iraq and/or Afghanistan. Virtual Reality Graded Exposure Therapy (VR-GET) with arousal control has shown particular promise in reducing the symptom severity of PTSD in combat veterans. In this report, we describe the outcome of VR-GET for the treatment of combat-related PTSD in two combat veterans, neither of whom had received treatment for PTSD in the initial years after their return from combat duty.

Integrating virtual realities and psychotherapy: SWOT analysis on VR and MR based treatments of anxiety and stress-related disorders

The use of virtual reality (VR) and mixed reality (MR) technology in clinical psychology is growing. Efficacious VR-based treatments for a variety of disorders have been developed. However, the field of technology-assisted psychotherapy is constantly changing with the advancement in technology. Factors such as interdisciplinary collaboration, consumer familiarity and adoption of VR products, and progress in clinical science all need to be taken into consideration when integrating virtual technologies into psychotherapies. We aim to present an overview of current expert opinions on the use of virtual technologies in the treatment of anxiety and stress-related disorders. An anonymous survey was distributed to a select group of researchers and clinicians, using an analytic framework known as Strengths, Weaknesses, Opportunities, and Threats (SWOT). Overall, the respondents had an optimistic outlook regarding the current use as well as future development and implementation of technology-assisted interventions. VR and MR psychotherapies offer distinct advantages that can overcome shortcomings associated with traditional therapy. The respondents acknowledged and discussed current limitations of VR and MR psychotherapies. They recommended consolidation of existing knowledge and encouraged standardisation in both theory and practice. Continued research is needed to leverage the strengths of VR and MR to develop better treatments.Abbreviations: AR: Augmented Reality; MR: Mixed Reality; RCT: Randomised Controlled Trial; SWOT: Strengths, Weaknesses, Opportunities, and Threats; VR: Virtual Reality; VR-EBT: Virtual Reality Exposure-Based Therapy.

Human-Robot Confluence: Toward a Humane Robotics

The new humanoid robots not only perform tasks, but also can activate interactions and social relationships with other robots and with humans. In this view, the diffusion of humanoid robots with a physical structure reminiscent of the human body, endowed with decision-making abilities, and capable of externalizing and generating emotions, is opening a new line of research with a main objective of understanding the dynamics of social interactions generated by the encounters between robots and humans. However, this process is not easy. To be accepted by society, robots have to "understand" people and to adapt themselves to complex real-life social environments. This goal underlines the importance for research of aspects such as communication, acceptance, and ethics that require the collaboration between multiple disciplines, including psychology, neuroscience, design, mechatronics, computer science, philosophy, sociology, anthropology, biomechanics, and roboethics. This special issue seeks to gather knowledge from these disciplines with respect to human-robot confluence (HRC) in the application of robots in everyday life, including robot training partners and industrial collaborative robots (Cobots). It covers a wide range of topics related to HRC, involving theories, methodologies, technologies, and empirical and experimental studies. The final goal is to support researchers and developers in creating robots that not only have a humanoid body but that are really "humane": accessible, sympathetic, generous, compassionate, and forbearing.

Machines Like Us and People Like You: Toward Human-Robot Shared Experience

In the past years, the field of collaborative robots has been developing fast, with applications ranging from health care to search and rescue, construction, entertainment, sports, and many others. However, current social robotics is still far from the general abilities we expect in a robot collaborator. This limitation is more evident when robots are faced with real-life contexts and activities occurring over long periods. In this article, we argue that human-robot collaboration is more than just being able to work side by side on complementary tasks: collaboration is a complex relational process that entails mutual understanding and reciprocal adaptation. Drawing on this assumption, we propose to shift the focus from "human-robot interaction" to "human-robot shared experience." We hold that for enabling the emergence of such shared experiential space between humans and robots, constructs such as coadaptation, intersubjectivity, individual differences, and identity should become the central focus of modeling. Finally, we suggest that this shift in perspective would imply changing current mainstream design approaches, which are mainly focused on functional aspects of the human-robot interaction, to the development of architectural frameworks that integrate the enabling dimensions of social cognition.

The Study of Perceptual Eye Position Examination and Visual Perceptual Training in Postoperative Intermittent Exotropes

The aim of this study was to investigate perceptual eye position (PEP) and to evaluate the effect of dichoptic visual perceptual training in postoperative intermittent exotropia [X(T)]. We enrolled 30 non-strabismus children (control group) and 54 postoperative X(T) children [divided into training group (33 patients) and non-training group (21 patients)]. All subjects received measurements of PEP, and the postoperative X(T) children were measured both in the third postoperative day and the third postoperative month. All patients in training group received 3-month dichoptic visual perceptual training based on a unique virtual reality platform. The results showed that the postoperative X(T) children with normal eye position still had an abnormal PEP. After a period of visual perceptual training, the PEP pixels in postoperative children dramatically decreased. The results revealed that PEP could evaluate fixation disparity and binocular visual function perceptively and precisely, and the dichoptic visual perceptive training may rebuild binocular visual function.