Search Results (4)

Smart virtual reality (VR) systems are becoming central to media production education, where immersive practice, real-time feedback, and hands-on simulation are essential. This review synthesizes the integration of artificial intelligence (AI) into human-centered, interactive VR learning for television and media production. Searches in Scopus, Web of Science, IEEE Xplore, ACM Digital Library, and SpringerLink (2013–2024) identified 790 records; following PRISMA screening, 94 studies met the inclusion criteria and were synthesized using a systematic scoping review approach. Across this corpus, common AI components include learner modeling, adaptive task sequencing (e.g., RL-based orchestration), affect sensing (vision, speech, and biosignals), multimodal interaction (gesture, gaze, voice, haptics), and growing use of LLM/NLP assistants. Reported benefits span personalized learning trajectories, high-fidelity simulation of studio workflows, and more responsive feedback loops that support creative, technical, and cognitive competencies. Evaluation typically covers usability and presence, workload and affect, collaboration, and scenario-based learning outcomes, leveraging interaction logs, eye tracking, and biofeedback. Persistent challenges include latency and synchronization under multimodal sensing, data governance and privacy for biometric/affective signals, limited transparency/interpretability of AI feedback, and heterogeneous evaluation protocols that impede cross-system comparison. We highlight essential human-centered design principles—teacher-in-the-loop orchestration, timely and explainable feedback, and ethical data governance—and outline a research agenda to support standardized evaluation and scalable adoption of smart VR education in the creative industries. Full article

Background/Objectives: Gait retraining is widely used in orthopedic rehabilitation to address abnormal movement patterns. However, retaining walking modifications can be challenging without guidance from physical therapists. Real-time auditory biofeedback can help patients learn and maintain gait alterations. This study piloted the feasibility of the musification of feedback to medialize the center of pressure (COP). Methods: To provide musical feedback, COP and plantar pressure were captured in real time at 100 Hz from a wireless 16-sensor pressure insole. Twenty healthy subjects (29 ± 5 years old, 75.9 ± 10.5 Kg, 1.73 ± 0.07 m) were recruited to walk using this system and were further analyzed via marker-based motion capture. A lowpass filter muffled a pre-selected music playlist when the real-time center of pressure exceeded a predetermined lateral threshold. The only instruction participants received was to adjust their walking to avoid the muffling of the music. Results: All participants significantly medialized their COP (−9.38% ± 4.37, range −2.3% to −19%), guided solely by musical feedback. Participants were still able to reproduce this new walking pattern when the musical feedback was removed. Importantly, no significant changes in cadence or walking speed were observed. The results from a survey showed that subjects enjoyed using the system and suggested that they would adopt such a system for rehabilitation. Conclusions: This study highlights the potential of musical feedback for orthopedic rehabilitation. In the future, a portable system will allow patients to train at home, while clinicians could track their progress remotely through cloud-enabled telemetric health data monitoring. Full article

Neurological diseases including stroke and neurodegenerative disorders cause a hefty burden on the healthcare system. Survivors experience significant impairment in mobility and daily activities, which requires extensive rehabilitative interventions to assist them to regain lost skills and restore independence. The advent of remote rehabilitation architecture and enabling technology mandates the elaboration of sensing mechanisms tailored to individual clinical needs. This study aims to review current trends in the application of sensing mechanisms in remote monitoring and rehabilitation in neurological diseases, and to provide clinical insights to develop bespoke sensing mechanisms. A systematic search was performed using the PubMED database to identify 16 papers published for the period between 2018 to 2022. Teleceptive sensors (56%) were utilized more often than wearable proximate sensors (50%). The most commonly used modality was infrared (38%) and acceleration force (38%), followed by RGB color, EMG, light and temperature, and radio signal. The strategy adopted to improve the sensing mechanism included a multimodal sensor, the application of multiple sensors, sensor fusion, and machine learning. Most of the stroke studies utilized biofeedback control systems (78%) while the majority of studies for neurodegenerative disorders used sensors for remote monitoring (57%). Functional assessment tools that the sensing mechanism may emulate to produce clinically valid information were proposed and factors affecting user adoption were described. Lastly, the limitations and directions for further development were discussed. Full article

The presented paper examines the students’ adoption of the use of a cost-effective biofeedback system for anxiety awareness in parallel to examination activities. Human anxiety is classified by evaluating bio-signals related to skin conductance, skin temperature and heart rate. The participants of the research were 44 students who were taking examinations in the form of synchronous online tests in the classroom for one of their courses. At first, the usability of the biofeedback system was examined using the system usability scale (SUS). The statistical analysis indicated that the examined system usability is quite satisfactory. Then, the study attempted to investigate the relationships between the students’ technology readiness personality dimensions, perceptions of usability, and the usefulness of the presented system by exploiting the technology readiness and acceptance model (TRAM). The results showed that the students’ optimism and attitude towards using the system are significant factors that affect the model’s relationships. The examined relationships are presented via a path model. Full article