Search Results (16)

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: Polyneuropathies impair sensory, motor, and autonomic functions, affecting functional status, cognition, and quality of life. This pilot study investigated the effects of exergame with biofeedback training (Riablo system) versus standard rehabilitation on these outcomes in outpatients with mixed-etiology polyneuropathies. Methods: Seventeen outpatients were assigned to standard rehabilitation (Group 1, n = 9) or combined standard plus Riablo training (Group 2, n = 8) over three weeks. Functional status, pain, cognition, quality of life, and psychological well-being were assessed pre- and post-intervention, with a 6-month follow-up. Outcome measures included the Morse Fall Scale, Visual Analogue Scales for pain and autonomy, Montreal Cognitive Assessment (MoCA), Trail Making Test (TMT), Stroop Test, Frontal Assessment Battery (FAB), Verbal fluency test, the Short-Form Health Survey-12 (SF-12), and the Patient Health Questionnaire-4 (PHQ-4). Longitudinal changes and between-group differences were analyzed using nonparametric statistics. Results: Both groups showed significant improvements in functional status and global cognition at post-intervention. Group 2 demonstrated greater improvements in executive functions and attention, with significant reductions in pain and fall risk. At 6-month follow-up, Group 2 maintained post-intervention gains in QoL and psychological outcomes, while Group 1 showed a significant decline. Technology evaluation revealed high usability and positive psychosocial impact in Group 2, with strong correlations between executive function improvements and device usability. Conclusions: Integrating exergames with biofeedback into standard rehabilitation may provide broader and longer-lasting benefits for polyneuropathy patients. These findings support further large-scale trials to confirm efficacy and optimize technology-assisted rehabilitation protocols. Full article

Smart assistive technologies such as sensor-based footwear and walking aids offer promising opportunities for gait rehabilitation through real-time feedback and patient-centered monitoring. While biofeedback applications show great potential, current research rarely explores integrated closed-loop systems with device- and modality-specific feedback. In this work, we present a modular sensor-based system combining a smart foot orthosis and an instrumented forearm crutch to deliver real-time vibrotactile biofeedback. The system integrates plantar pressure and motion sensing, vibrotactile feedback, and wireless communication via a smartphone application. We conducted a user study with eight participants to validate the system’s feasibility for mobile gait detection and app usability, and to evaluate different vibrotactile feedback types across the orthosis and forearm crutch. The results indicate that pattern-based vibrotactile feedback was rated as more useful and suitable for regular use than simple vibration alerts. Moreover, participants reported clear perceptual differences between feedback delivered via the orthosis and the forearm crutch, indicating device-dependent feedback perception. The findings highlight the relevance of feedback strategy design beyond hardware implementation and inform the development of user-centered haptic biofeedback systems. Full article

In this study, we present a framework to develop and evaluate a virtual reality exposure therapy system with biofeedback toward scorpion phobia treatment. The system is developed based on the methodology for the development of virtual reality educational environments; usability is evaluated with the System Usability Scale (SUS), the affects are measured with the Positive and Negative Affect Schedule (PANAS), and the biofeedback heart rate is measured in real time using a wearable device and the HypeRate app. A descriptive study was conducted with a non-probabilistic convenience sample of undergraduate students. The non-clinical sample consisted of 51 participants (11 women and 40 men) (mean = 20.75, SD = 2.42 years). The system usability score was 75.49, higher than the average of 68. For positive affects, the average value of the overall sample was 28.18, while for negative affects it was 13.67. The results of this preliminary study, while not determining that the system could currently be applied in clinical settings, demonstrate however that the system can initially be considered as a pre-feasibility study, and if the limitations of the unbalanced non-clinical sample are addressed, it could be used in the future for this purpose. The main contribution is the proposed framework to integrate usability and affects evaluation, as well as biofeedback in a VRET system toward scorpion phobia treatment. Full article

About one-third of stroke survivors present unilateral spatial neglect (USN) that negatively impacts the rehabilitation outcome. We reported the study protocol and usability results of an eye-tracking (ET) biofeedback immersive virtual reality (iVR) protocol. Healthy controls and stroke patients with and without USN underwent a single session of the three iVR tasks. The system usability scale (SUS), adverse events (AEs), and ET data were collected and analyzed via parametric analysis. Twelve healthy controls (six young adults and six older adults) and seven patients with a diagnosis of single ischemic stroke (four without USN and three with confirmed diagnosis of USN) completed the usability investigation. SUS results showed good acceptability of the system for healthy controls and stroke patients without USN. ET results showed a lower performance for patients with USN concerning healthy controls and stroke patients without USN, in particular in the exploration of the left visual field. The results showed that the proposed iVR-ET biofeedback protocol is a safe and well-tolerated technique in patients with USN. The real-time feedback can induce a performance response supporting its investigation such as a treatment approach. Full article

Eye gaze interfaces are an emerging technology that allows users to control graphical user interfaces (GUIs) simply by looking at them. However, using gaze-controlled GUIs can be a demanding task, resulting in high cognitive and physical load and fatigue. To address these challenges, we propose the concept and model of an adaptive human-assistive human–computer interface (HA-HCI) based on biofeedback. This model enables effective and sustainable use of computer GUIs controlled by physiological signals such as gaze data. The proposed model allows for analytical human performance monitoring and evaluation during human–computer interaction processes based on the damped harmonic oscillator (DHO) model. To test the validity of this model, the authors acquired gaze-tracking data from 12 healthy volunteers playing a gaze-controlled computer game and analyzed it using odd–even statistical analysis. The experimental findings show that the proposed model effectively describes and explains gaze-tracking performance dynamics, including subject variability in performance of GUI control tasks, long-term fatigue, and training effects, as well as short-term recovery of user performance during gaze-tracking-based control tasks. We also analyze the existing HCI and human performance models and develop an extension to the existing physiological models that allows for the development of adaptive user-performance-aware interfaces. The proposed HA-HCI model describes the interaction between a human and a physiological computing system (PCS) from the user performance perspective, incorporating a performance evaluation procedure that interacts with the standard UI components of the PCS and describes how the system should react to loss of productivity (performance). We further demonstrate the applicability of the HA-HCI model by designing an eye-controlled game. We also develop an analytical user performance model based on damped harmonic oscillation that is suitable for describing variability in performance of a PC game based on gaze tracking. The model’s validity is tested using odd–even analysis, which demonstrates strong positive correlation. Individual characteristics of users established by the damped oscillation model can be used for categorization of players under their playing skills and abilities. The experimental findings suggest that players can be categorized as learners, whose damping factor is negative, and fatiguers, whose damping factor is positive. We find a strong positive correlation between amplitude and damping factor, indicating that good starters usually have higher fatigue rates, but slow starters have less fatigue and may even improve their performance during play. The proposed HA-HCI model and analytical user performance models provide a framework for developing an adaptive human-oriented HCI that enables monitoring, analysis, and increased performance of users working with physiological-computing-based user interfaces. The proposed models have potential applications in improving the usability of future human-assistive gaze-controlled interface systems. Full article

In medicine and sport science, postural evaluation is an essential part of gait and posture correction. There are various instruments for quantifying the postural system’s efficiency and determining postural stability which are considered state-of-the-art. However, such systems present many limitations related to accessibility, economic cost, size, intrusiveness, usability, and time-consuming set-up. To mitigate these limitations, this project aims to verify how wearable devices can be assembled and employed to provide feedback to human subjects for gait and posture improvement, which could be applied for sports performance or motor impairment rehabilitation (from neurodegenerative diseases, aging, or injuries). The project is divided into three parts: the first part provides experimental protocols for studying action anticipation and related processes involved in controlling posture and gait based on state-of-the-art instrumentation. The second part provides a biofeedback strategy for these measures concerning the design of a low-cost wearable system. Finally, the third provides algorithmic processing of the biofeedback to customize the feedback based on performance conditions, including individual variability. Here, we provide a detailed experimental design that distinguishes significant postural indicators through a conjunct architecture that integrates state-of-the-art postural and gait control instrumentation and a data collection and analysis framework based on low-cost devices and freely accessible machine learning techniques. Preliminary results on 12 subjects showed that the proposed methodology accurately recognized the phases of the defined motor tasks (i.e., rotate, in position, APAs, drop, and recover) with overall F1-scores of 89.6% and 92.4%, respectively, concerning subject-independent and subject-dependent testing setups. Full article

This paper describes the second part of the PASSO (Parkinson smart sensory cues for older users) project, which designs and tests an innovative haptic biofeedback system based on a wireless body sensor network using a smartphone and different smartwatches specifically designed to rehabilitate postural disturbances in persons with Parkinson’s disease. According to the scientific literature on the use of smart devices to transmit sensory cues, vibrotactile feedback (particularly on the trunk) seems promising for improving people’s gait and posture performance; they have been used in different environments and are well accepted by users. In the PASSO project, we designed and developed a wearable device and a related system to transmit vibrations to a person’s body to improve posture and combat impairments like Pisa syndrome and camptocormia. Specifically, this paper describes the methodologies and strategies used to design, develop, and test wearable prototypes and the mHealth system. The results allowed a multidisciplinary comparison among the solutions, which led to prototypes with a high degree of usability, wearability, accessibility, and effectiveness. This mHealth system is now being used in pilot trials with subjects with Parkinson’s disease to verify its feasibility among patients. Full article

(1) Background: The development of a lightweight, easy-to-use system that measures the foot’s plantar pressure is becoming an increasingly important area of research in physiotherapy. For further development of the smart sock system, a formative usability study was conducted, where the smart textile sock sensor system was used for self-correction during functional tasks; (2) Methods: Five athletes from the football school participated in the formative usability study. Athletes performed pre-defined functional tasks for self-correction when interacting with the smart textile sock system. Formative usability evaluation methods: effectiveness (task success rate, error rate), efficiency (time-based), satisfaction evaluated by System Usability Scale (SUS); (3) Results: Formative usability indicators: task completeness effectiveness ranged from 40% to 100% in the first- and second-stage tasks. Completed task efficiency time: Stage 1, from 4.2 s (SD 1.3) to 88.8 s (SD 19.8); Stage 2, from 7.2 s (SD 1.9) to 9.6 s (SD 2.1). Satisfaction was assessed by the SUS system user group with 76 points (SD 7.42), which indicates “good” satisfaction; (4) Conclusions: formative usability indicators showed the need for technical improvements to the smart textile sock pressure sensor system. The SUS results indicate “good” satisfaction with the smart textile sock pressure sensor system and its application. 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

e-Health may enhance self-management of pelvic floor muscle training (PFMT) to treat stress urinary incontinence (SUI). It is crucial to involve patients in planning, developing and monitoring the optimal e-Health solution. This research aims to describe patient-centered innovation in an early developmental stage of the WOMEN-UP solution. We conducted a qualitative study through a self-developed questionnaire in 22 women with SUI, to define system requirements from a patient’s perspective. The first prototype of the WOMEN-UP solution was developed. It was tested by 9 patients in a usability study (think-aloud protocol and retrospective interviews). Patient preferences regarding the possible use of an e-Health solution with serious games for PFMT were: (1) to receive feedback about PFMT; (2) convenient home-use; (3) increasing motivation; (4) available in medical centers. Identified usability aids (31) reassured our design-development plan, which considered the biofeedback and serious games as key factors. Patient’s perspective detected some unexpected issues related to the calibration and serious games, involving a change in the ongoing development to get an improved WOMEN-UP solution; the value of patient-centered innovation during the development of an e-Health solution for PFMT (WOMEN-UP solution). To identify patients’ unmet needs, we proposed a longitudinal approach for the future eHealth-related patient-centered innovations. Full article

The adjunctive use of biofeedback systems with exoskeletons may accelerate post-stroke gait rehabilitation. Wearable patient-oriented human-robot interaction-based biofeedback is proposed to improve patient-exoskeleton compliance regarding the interaction torque’s direction (joint motion strategy) and magnitude (user participation strategy) through auditory and vibrotactile cues during assisted gait training, respectively. Parallel physiotherapist-oriented strategies are also proposed such that physiotherapists can follow in real-time a patient’s motor performance towards effective involvement during training. A preliminary pre-post controlled study was conducted with eight healthy participants to conclude about the biofeedback’s efficacy during gait training driven by an ankle-foot exoskeleton and guided by a technical person. For the study group, performance related to the interaction torque’s direction increased during (p-value = 0.07) and after (p-value = 0.07) joint motion training. Further, the performance regarding the interaction torque’s magnitude significantly increased during (p-value = 0.03) and after (p-value = 68.59 × 10⁻³) user participation training. The experimental group and a technical person reported promising usability of the biofeedback and highlighted the importance of the timely cues from physiotherapist-oriented strategies. Less significant improvements in patient–exoskeleton compliance were observed in the control group. The overall findings suggest that the proposed biofeedback was able to improve the participant-exoskeleton compliance by enhancing human-robot interaction; thus, it may be a powerful tool to accelerate post-stroke ankle-foot deformity recovery. Full article

Individuals with lower-limb amputation often have gait deficits and diminished mobility function. Biofeedback systems have the potential to improve gait rehabilitation outcomes. Research on biofeedback has steadily increased in recent decades, representing the growing interest toward this topic. This systematic review highlights the methodological designs, main technical and clinical challenges, and evidence relating to the effectiveness of biofeedback systems for gait rehabilitation. This review provides insights for developing an effective, robust, and user-friendly wearable biofeedback system. The literature search was conducted on six databases and 31 full-text articles were included in this review. Most studies found biofeedback to be effective in improving gait. Biofeedback was most commonly concurrently provided and related to limb loading and symmetry ratios for stance or step time. Visual feedback was the most used modality, followed by auditory and haptic. Biofeedback must not be obtrusive and ideally provide a level of enjoyment to the user. Biofeedback appears to be most effective during the early stages of rehabilitation but presents some usability challenges when applied to the elderly. More research is needed on younger populations and higher amputation levels, understanding retention as well as the relationship between training intensity and performance. Full article

The majority of wearable sensor-based biofeedback systems used in exercise rehabilitation lack end-user evaluation as part of the development process. This study sought to evaluate an exemplar sensor-based biofeedback system, investigating the feasibility, usability, perceived impact and user experience of using the platform. Fifteen patients participated in the study having recently undergone knee replacement surgery. Participants were provided with the system for two weeks at home, completing a semi-structured interview alongside the System Usability Scale (SUS) and user version of the Mobile Application Rating Scale (uMARS). The analysis from the SUS (mean = 90.8 [SD = 7.8]) suggests a high degree of usability, supported by qualitative findings. The mean adherence rate was 79% with participants reporting a largely positive user experience, suggesting it offers additional support with the rehabilitation regime. Overall quality from the mean uMARS score was 4.1 out of 5 (SD = 0.39), however a number of bugs and inaccuracies were highlighted along with suggestions for additional features to enhance engagement. This study has shown that patients perceive value in the use of wearable sensor-based biofeedback systems and has highlighted the benefit of user-evaluation during the design process, illustrated the need for real-world accuracy validation, and supports the ongoing development of such systems. Full article

This publication presents a complete description of a technological solution system for the physical and cognitive rehabilitation of elderly people through a biofeedback system, which is combined with a Lego robot. The technology used was the iOS’s (iPhone Operating System) Objective-C programming language and its XCode programming environment; and SQLite in order to create the database. The biofeedback system is implemented by the use of two biosensors which are, in fact, a Microsoft band 2 in order to register the user’s heart rate and a MYO sensor to detect the user’s arm movement. Finally, the system was tested with seven elderly people from La Santa y Real Casa de la Misericordia nursing home in Bilbao. The statistical assessment has shown that the users are satisfied with the usability of the system, with a mean score of 79.29 on the System Usability Scale (SUS) questionnaire. Full article