Decoding emotional responses to AI-generated architectural imagery.

Introduction: The integration of AI in architectural design represents a significant shift toward creating emotionally resonant spaces. This research investigates AI's ability to evoke specific emotional responses through architectural imagery and examines the impact of professional training on emotional interpretation. Methods: We utilized Midjourney AI software to generate images based on direct and metaphorical prompts across two architectural settings: home interiors and museum exteriors. A survey was designed to capture participants' emotional responses to these images, employing a scale that rated their immediate emotional reaction. The study involved 789 university students, categorized into architecture majors (Group A) and non-architecture majors (Group B), to explore differences in emotional perception attributable to educational background. Results: Findings revealed that AI is particularly effective in depicting joy, especially in interior settings. However, it struggles to accurately convey negative emotions, indicating a gap in AI's emotional range. Architecture students exhibited a greater sensitivity to emotional nuances in the images compared to non-architecture students, suggesting that architectural training enhances emotional discernment. Notably, the study observed minimal differences in the perception of emotions between direct and metaphorical prompts among architecture students, indicating a consistent emotional interpretation across prompt types. Conclusion: AI holds significant promise in creating spaces that resonate on an emotional level, particularly in conveying positive emotions like joy. The study contributes to the understanding of AI's role in architectural design, emphasizing the importance of emotional intelligence in creating spaces that reflect human experiences. Future research should focus on expanding AI's emotional range and further exploring the impact of architectural training on emotional perception.

Facial expression recognition in virtual reality environments: challenges and opportunities.

This study delved into the realm of facial emotion recognition within virtual reality (VR) environments. Using a novel system with MobileNet V2, a lightweight convolutional neural network, we tested emotion detection on 15 university students. High recognition rates were observed for emotions like "Neutral", "Happiness", "Sadness", and "Surprise". However, the model struggled with 'Anger' and 'Fear', often confusing them with "neutral". These discrepancies might be attributed to overlapping facial indicators, limited training samples, and the precision of the devices used. Nonetheless, our research underscores the viability of using facial emotion recognition technology in VR and recommends model improvements, the adoption of advanced devices, and a more holistic approach to foster the future development of VR emotion recognition.

Uncovering the connection between ceiling height and emotional reactions in art galleries with editable 360-degree VR panoramic scenes.

Introduction: This study investigates the relationship between ceiling height and emotional responses in art galleries, using editable 360-degree VR panoramic scenes. Prior research has explored the influence of spatial dimensions on general emotions, but the specific impact of ceiling height in art gallery settings, particularly on discrete emotions, remains understudied. Methods: The study utilized 360-degree panoramic photo scene modeling to modify ceiling heights within virtual art galleries, assessing emotional responses through self-report measures. Participants were presented with virtual art gallery environments featuring varying ceiling heights. Two studies were conducted: Study 1 involved absolute emotion rating across different ceiling heights, and Study 2 focused on selecting ceiling heights based on assigned emotions. Results: The data revealed that ceiling height significantly impacts specific emotions, notably disgust and joy. Lower ceiling heights generally evoked higher levels of fear and anger, while higher ceiling heights were associated with increased joy. The impact on other emotions like sadness, surprise, and disgust was more nuanced and varied across different ceiling heights. Discussion: The findings highlight a complex relationship between ceiling height and emotional responses in art galleries. The study demonstrates the efficacy of using editable 360-degree VR panoramic scenes in environmental psychology and architecture research, offering insights into how spatial dimensions influence emotional experiences in architectural settings.

Mini review: Challenges in EEG emotion recognition.

Electroencephalography (EEG) stands as a pioneering tool at the intersection of neuroscience and technology, offering unprecedented insights into human emotions. Through this comprehensive review, we explore the challenges and opportunities associated with EEG-based emotion recognition. While recent literature suggests promising high accuracy rates, these claims necessitate critical scrutiny for their authenticity and applicability. The article highlights the significant challenges in generalizing findings from a multitude of EEG devices and data sources, as well as the difficulties in data collection. Furthermore, the disparity between controlled laboratory settings and genuine emotional experiences presents a paradox within the paradigm of emotion research. We advocate for a balanced approach, emphasizing the importance of critical evaluation, methodological standardization, and acknowledging the dynamism of emotions for a more holistic understanding of the human emotional landscape.

Effects of Early Physical Therapy and Follow-Up in Acute Severe Coronavirus Disease 2019 Pneumonia: A Retrospective Observational Study.

Background: Rehabilitation in subjects with severe coronavirus disease 2019 (COVID-19) pneumonia has been widely recommended. However, data regarding the starting time of rehabilitation, subjects and healthcare workers' safety, as well as rehabilitation program features are limited. We aimed to assess the safety and characterize the effect of early and non-early physiotherapy on severe COVID-19 pneumonia subjects. Methods: A retrospective cohort study, including a consecutive sample of surviving subjects admitted to an acute care hospital due to severe COVID-19 pneumonia from March 13th to May 15th of 2020, is made. Subjects were separated into three groups: non-physical therapy, early physiotherapy (onset <7 days of admission), and non-early physiotherapy. Subject and therapist safety and length of hospital stay were the main evaluated outcomes. Results: A total of 159 subjects were included (72% men; median age 62 years). Rehabilitation was performed on 108 subjects (32 early and 76 non-early physiotherapies). The length of hospital stay was 19 [interquartile range (IQR) 36.25] and 34 days (IQR 27.25) (p = 0.001) for early and non-early physiotherapy groups, respectively. No physiotherapist was infected and no subject adverse effect was identified. Multivariate analysis of subjects receiving physiotherapy during admission identified obesity [odds ratio (OR) 3.21; p-value 0.028], invasive mechanical ventilation (OR 6.25; p-value <0.001), and non-early physiotherapy (OR 3.54; p-value 0.017) as independent factors associated with a higher risk of prolonged hospital stay. Survivors' follow-up after hospital discharge at 8 weeks was completed by 54% of subjects. Conclusion: Rehabilitation in acute severe COVID-19 pneumonia is safe for subjects and healthcare workers and could reduce the length of hospitalization stay, especially in those that may start early.