Virtual and augmented reality

3D scanners are professional, structured-light systems that capture geometry with sub-millimeter accuracy, enabling the creation of virtual garment digital twins. However, these high-resolution scans produce dense and heavy meshes that overwhelm performance and storage capacities in immersive environments. This study presents a scalable workflow to generate lightweight yet realistic 3D garment models for Metaverse applications. The novelty lies in the proposal and validation, via 20 padded garment case study, of a process that uses Artec Studio 19 for scan consolidation, Blender for retopology and texture baking, and Unity Engine 3D for deployment, while examining acquisition limitations (e.g., occluded folds, reflective materials) and quantitatively characterizing the trade-off between visual fidelity and performance. Starting from meshes of approximately 13 million triangles, we apply a 10% decimation followed by quad-based remeshing to achieve ∼ 30,000 quads and produce FBX assets of only 18–25 MB without perceptible quality loss. Side-by-side renderings in Blender and Unity confirm indistinguishability, and these asset sizes satisfy the 40 MB guideline for a dedicated Metaverse platform, supporting under 4 s of Web-AR load times. Best-practice guidelines detailing acquisition parameters, post-processing workflows, and optimization settings provide a reproducible framework for creating digital fashion models in Metaverse applications.

Keywords: 3D Scanning , Fashion industry , Mesh optimization , Metaverse , Reverse engineering

This paper introduces a Unity-based Virtual Reality (VR) system designed for real-time, incremental acquisition, processing, and interactive spatial filtering of LiDAR-generated point clouds on the Meta Quest 3 platform. Using an Intel RealSense L515 sensor and SLAM-inspired alignment techniques, the system enables dynamic, user-defined spatial segmentation through bounding boxes to refine collected data. The proposed framework supports multi-pass acquisitions, merging, and cleaning of point clouds, effectively addressing the limitations of traditional batch processing workflows. Additionally, the system provides an efficient modular structure that integrates live visualization using the Pcx Unity asset and optimizes performance through binary PLY file conversion. A case study on capturing a Meta Quest 3 protective case demonstrates the system's robustness and ability to preserve geometric fidelity across incremental scans, with minimal redundancy and automatic alignment. The results highlight the potential for future expansion into real-time volumetric reconstruction, automated point cloud registration, and advanced spatial computing applications. By combining modular software architecture with accessible hardware configurations, this work contributes a practical framework for immersive 3D data handling, aligning with ongoing research in real-time 3D reconstruction, interactive VR applications, and advanced point cloud processing.

Keywords: 3D Scanning , Point Cloud Processing , Virtual Prototyping , Virtual Reality

This study aims to validate STAAR-TECH, an Augmented Reality (AR) authoring tool for technical documentation designed for end users without expertise in AR development. Previous research on AR authoring tools has primarily focused on simplifying interfaces and interactions to enhance usability. However, these tools are inadequate for applying the Minimal AR authoring approach, according to which the information provided through AR visual assets should be the minimum needed to accomplish the task. The focus of this study is to propose an authoring tool that comprehensively adheres to this approach, ensuring the selection and customization of visual assets and their properties, which are essential for optimally conveying all information types according to the literature. To validate its effectiveness, we conducted a comparative user study with Microsoft Dynamics 365 Guides as baseline, involving 32 participants using HoloLens. We measured the authoring performance, the perceived workload, and the user experience while using both tools. Our findings confirmed that STAAR-TECH is a highly suitable tool for AR manual creation. Participants appreciated its extensive visual asset customization and flexibility, reinforcing its potential as an effective solution for AR authoring.

Keywords: Augmented reality , Authoring tool , Minimal information , Technical documentation , Visual asset , Work instruction

Preoperative anxiety is a common condition that can negatively impact patient compliance, pain tolerance, and anesthesia management. Traditional pharmacological treatments include sedatives and anxiolytics, but these can cause adverse effects, such as respiratory issues. Non-pharmacological approaches like cognitive-behavioral therapy (CBT), aromatherapy, and music therapy have also been explored but they require pathways of variable duration that may delay surgery. Virtual reality (VR) is emerging as a promising alternative, allowing patients to engage in immersive experiences that distract them from anxiety-inducing stimuli. A prospective randomized controlled trial was conducted to assess the impact of VR on preoperative anxiety and postoperative pain in patients undergoing elective surgery. A total of 355 patients were randomized into two groups: Group A received entertainment videos via VR headset during the preoperative phase, while Group B received standard care. The primary outcome was the change in STAI (State-Trait Anxiety Inventory) scores at baseline, preoperatively, and postoperatively. Secondary outcomes included pain assessment using the Visual Analog Scale (VAS). Results showed no significant difference in baseline anxiety scores between the two groups. However, both preoperative and postoperative STAI scores were significantly lower in the VR group (p = 0.001 and 0.005, respectively). Additionally, 12 h post-surgery, patients in the VR group reported significantly lower pain scores (3.6 ± 1.3 vs. 5.6 ± 1.6, p = 0.001). No significant differences in pain scores were observed at 24 and 48 h post-surgery. VR could represent a useful aid in the management of preoperative anxiety.

Keywords: Anxiety , Postoperative pain , Preoperative management , Virtual reality

The use of immersive virtual reality (VR) technologies for ergonomic assessment is gaining increasing relevance as digital tools become integral to human-centered design processes. However, questions remain regarding the reliability and representativeness of postural evaluations conducted in virtual environments compared to those performed in the real world. This study explores the effectiveness of virtual ergonomic analysis by applying a structured, sensor-based protocol to two manual assembly tasks executed in both real and virtual settings. Full-body motion capture and the RULA method were employed to objectively assess postural risk, with consistent task sequences and workstation setups ensuring comparability across conditions. By analyzing and comparing results from both environments, the study provides insights into the strengths and current limitations of VR-based ergonomic evaluations. Findings indicate that immersive VR is a promising tool for early-stage ergonomic analysis. Nevertheless, limitations emerged in tasks involving high physical demands or requiring precise manual alignment, where the absence of physical feedback in VR may lead to an underestimation of postural risk. These observations underscore the need to improve interaction fidelity to enhance the validity and applicability of VR-based ergonomic assessments in industrial contexts.

Keywords: Digital Human Model , Ergonomics , Virtual Reality

Traditional design reviews often rely on static inspection of 3D CAD models and physical prototyping, approaches that are typically time-consuming, costly, and limited in interactivity. While Virtual Reality (VR) offers a promising, immersive, and cost-effective alternative, its adoption in industry remains limited due to the limitations of commercial solutions and their poor integration with CAD environments. To overcome these challenges, this paper introduces a flexible, VR-based framework aimed at enabling an automated scene setup and immersive design reviews for early-stage assembly validation, before physical prototyping begins without the constraints of proprietary platforms. The framework is composed of two interconnected applications: (1) Model Setup Application, which facilitates the import and conversion of CAD models, along with the definition of assembly sequences enriched with technical and safety alerts, and (2) Immersive Design Review Application, which provides an interactive VR environment for navigating assemblies, validating procedures, and annotating key steps. This approach supports collaborative, virtual exploration of assembly processes, enhancing early design communication, reducing development lead times, and improving knowledge retention. The framework is compatible with consumer-grade VR hardware and supports standalone operation, making it a scalable and accessible solution.

Keywords: Assembly Validation , Immersive Design Review , Virtual Assembly , Virtual Reality

The transition to Industry 5.0 emphasizes human-centric automation, prioritizing ergonomics, cognitive adaptability, and real-time collaboration between humans and machines. Traditional automation strategies have focused primarily on efficiency and standardization, often overlooking human operators' cognitive and physiological workload. This paper presents an AutomationML-based (AML) digital framework that integrates user experience (UX) approaches and human-in-the-loop methodologies to optimize human task design by harmonizing human cognitive states, physiological data, and real-time behavioral insights from industrial digital assets and the physical factory. The presented approach extends the recently defined AML standard by introducing a structured human taxonomy, a UX database architecture, and an enhanced task modeling and adaptation strategy based on the operators' feedback. An industrial use case about quality inspection is presented to validate the proposed framework, where an assisted inspection system integrates augmented reality visualization with human physiological monitoring using a sensorized wristband. This framework enables real-time task adaptation based on the estimate of the operator's workload, reducing cognitive overload and optimizing task allocation between humans and machines. Results on the use case suggest how UX-driven automation improves both process performance and workers' well-being, as well as the overall system flexibility. This research contributes to the development of ergonomic and cognitive-aware automation solutions that enhance collaboration between humans and machines.

Keywords: Augmented Reality , AutomationML , Human-Centered Design , Human-In-The-Loop (HITL) , Industry 5.0 , User Experience

Central vision loss (CVL) is an increasingly prevalent condition that significantly affects essential daily activities such as reading and visual search. This study simulates a central scotoma in a controlled experimental setting using the Microsoft HoloLens 2 augmented reality (AR) headset, enabling the investigation of compensatory mechanisms when the foveal region is compromised. Thirty-three participants performed a reading task (Task 1) and a visual search task (Task 2) under both normal vision and AR-simulated defect conditions, while eye-tracking data were recorded to analyze differences in visual behaviour and compensatory strategies. Key performance metrics included error rates, task completion times, and eye movement metrics such as the number and duration of fixations and saccades. Results showed that simulated central vision loss induced a more effortful visual exploration strategy, with an increased number of fixations and saccades, as well as longer total fixation duration, while saccadic timing remained stable. Specifically, the mean number and total duration of fixations during the reading task were approximately 14 and 8 s under normal vision, and 18 and 11 s under CVL condition, respectively. These findings demonstrate the potential of AR-based methods to replicate visual impairments in research settings. Future work could expand on the use of extended reality technologies for assistive and rehabilitative applications in individuals with central vision deficits.

Keywords: AR , Augmented Reality , Central vision loss , Eye-tracking , HoloLens 2 , Scotoma , Visual impairment

Objective: Joint replacement surgery, also known as arthroplasty, is a common procedure that restores mobility and relieves pain in patients with severe joint pathologies. Despite being considered routine, arthroplasties are complex interventions with potential complications and variable clinical outcomes. Accurate evaluation of replaced joint mobility to ensure implant stability within the patient's functional range of motion (ROM) is a major challenge in postoperative care. However, the reliability of current assessment methods is limited due to their lack of standardized and quantitative tools. This study presents a patient-specific Mixed Reality (MR) framework designed to enhance postoperative evaluation in joint replacement with a focus on total hip arthroplasty (THA). Methods: The proposed system enables objective quantification and MR visualization of prosthesis biomechanics by integrating ROM simulation and 3D modeling, promoting explainability and interpretability of surgery outcomes. A retrospective analysis of 67 THAs was performed to compare simulated ROM results with clinical assessments and literature benchmarks. Additionally, surgeons evaluated the system's clinical relevance and usability through a preliminary study, including completion of the System Usability Scale (SUS). Results: Simulated ROM measurements showed good agreement with both clinical assessments and established literature reference values across ten movements commonly examined in orthopedic practice. The MR tool demonstrated high accuracy, repeatability, and potential to support postoperative decision-making, with usability testing yielding a favorable median SUS score of 82.5, indicating strong acceptance among clinicians. Conclusion: The patient-specific MR framework provides a reliable, quantitative, and interpretable method for assessing prosthetic joint performance after replacement, supporting its integration into postoperative workflows for improved surgical outcome assessment.

Keywords: Computer-aided surgery , Human-computer interaction , Joint replacement , Mixed reality , Orthopedic surgery , Total Hip arthroplasty

Cutting guides are widely used in cranio-maxillofacial surgery by providing mechanical references for precise bone resections and reducing intraoperative variability. Nevertheless, their rigid and patient-specific design requires dedicated CAD modeling and fabrication, making them time-consuming to produce and difficult to adapt when anatomical conditions or bone surfaces change. This work presents a hybrid surgical cutting guide that combines a physically adjustable device with Augmented Reality (AR) feedback to support intraoperative alignment in maxillofacial osteotomies. The concept merges the tactile reliability of conventional guides with the adaptability of digital visualization, enabling surgeons to fine-tune the cutting plane directly through AR tracking. Registration was performed using cephalometric landmarks and an inside-out tracking approach with HoloLens 2, allowing precise superimposition of virtual cutting planes onto 3D-printed mandibular models. The system was evaluated by both expert and novice operators under three feedback conditions: no AR, holographic overlay, and real-time distance guidance. Results showed that AR feedback was associated with improved positional accuracy, with mean linear deviations of 1.27±0.71mm and angular errors of 4.46±3.27°. Operator experience influenced overall performance, yet enhanced feedback compensated part of this variability. Combining physical and digital guidance can yield more adaptable, precise, and reusable osteotomy tools, paving the way for flexible surgical assistance in clinical settings.

Keywords: Adjustable surgical guide , Augmented Reality , Cranio-maxillofacial surgery , Hololens 2 , Hybrid surgical guide , Pose estimation

Early and reliable identification of vertebral metastases on computed tomography remains a major challenge in oncologic imaging due to the morphological complexity of metastatic lesions and the high inter-patient variability of spinal anatomy. In this study, an end-to-end interpretable radiomic-based framework was developed to automatically distinguish healthy from metastatic vertebrae using segmented DICOM data, coupled with an interactive virtual reality (VR) visualization module implemented in Unity 3D. The proposed framework integrates radiomic feature extraction and selection, informed undersampling to address class imbalance, and automatic machine learning-based classification. To facilitate interpretation, patient-specific 3D models with overlapped classifier outputs were integrated into a VR desktop application, enabling advanced exploration of patient-specific spinal models, with color-coded visualization of algorithmic predictions and expert-defined suspicious lesions. The final classification model, trained using a Random Forest algorithm and optimized via stratified 5-fold cross-validation, achieved an overall accuracy of 0.86, an Area Under the Receiver Operating Characteristic Curve of 0.91, and an F1-score of 0.81 for the metastatic class on the independent test set, achieving competitive diagnostic performance while preserving transparency and clinical interpretability. This study represents a foundational step toward intelligent, interactive, and clinically interpretable tools for the diagnosis and follow-up of spinal metastatic disease.

Keywords: automatic lesion classification , bone lesions , machine learning , medical 3D visualization , spinal metastases , virtual reality

Tracking systems are essential in various fields, such as health and manufacturing industries, enabling mapping between the real and digital worlds. Amongst others, Augmented Reality Tracking Systems (ARTS) are more recent and less explored. This work proposes a quantitative metrological methodology to evaluate ARTS tooltip tracking performance, facilitating benchmarking, parameter optimization, and system selection for specific tasks. A specific 3D-printed measuring artifact is proposed to guide tooltip positioning. Tracking accuracy and precision are estimated, highlighting the effects of influence factors. The methodology was tested with two commercial state-of-the-art ARTSs using marker-based tooltips, i.e., a Microsoft HoloLens 2 and a stereo camera system equipped with Intel RealSense SR305 cameras. Metrological characteristics are evaluated, and the Euclidean distance expanded uncertainty at a conventional 95% confidence level is estimated as 5.071mm for the HoloLens 2 and 6.800mm for the stereo system, resulting in a superior metrological performance of HoloLens 2 under the specified conditions. This study provides a standardized approach for quantitatively comparing AR tracking systems, offering valuable insights for optimizing their use in specific applications and, innovatively in the context of ARTS, associates measurement uncertainty with tracked distance values.

Keywords: Augmented reality , Design of experiments , Measurement uncertainty , Metrological characteristics , Tooltip tracking

Background: In recent years, the growing adoption of Virtual Reality (VR) and 3D printing technologies has revolutionized surgical training by providing innovative opportunities for hands-on education. This study investigates the combined use of VR and 3D printed personalized anatomical models and cutting guides within the field of oral and maxillofacial oncologic surgery. Materials and methods: A mandibular tumour case was developed using the proposed approach, integrating both virtual and physical tools. Feedback was gathered from twelve surgical residents regarding their understanding of the case, the effectiveness of the immersive and three-dimensional technologies, and their overall satisfaction with the training experience. Results: Participants reported enhanced comprehension of complex surgical scenarios and valued the practical utility of the VR simulator combined with 3D printed models. The immersive environment facilitated skill acquisition in a risk-free setting. Conclusion: The findings underscore the significant added value of integrating VR and 3D printing technologies in surgical training, preparation, and simulation. This approach offers a safe, effective training platform that improves readiness for complex procedures in oncologic surgery and has the potential to be extended to other branches of maxillofacial surgery.

Keywords: fibula free flap , mandibular reconstruction , maxillofacial surgery , surgical education , three-dimensional printing , user-centered design , virtual reality

Background and objective Three-dimensional (3D) augmented reality (AR) and artificial intelligence (AI) technologies have recently been introduced to enhance guidance during robot-assisted radical prostatectomy (RARP). By overlaying virtual and real-time images, this approach helps accurately localize hidden lesions during surgery, enabling the execution of tailored procedures. This study aimed to evaluate whether 3D-AI-AR guidance reduces positive surgical margins (PSMs) compared with standard tw0-dimensional (2D) magnetic resonance imaging (MRI)-based interventions. Methods In this prospective, multicenter randomized controlled trial (NCT06318559), 133 patients with extracapsular extension or bulging at preoperative MRI were enrolled and randomized (2:1) to either 2D MRI-guided ( n = 84) or 3D-AI-AR–guided RARP ( n = 49). All the patients underwent nerve-sparing RARP. Intraoperative selective biopsies were then performed at the level of the preserved neurovascular bundle (NVB): cognitive in the MRI group and AR guided in the 3D group. The primary outcomes included PSM rate. Prostate-specific antigen (PSA) levels, continence, and potency recovery were assessed during the 12 mo of follow-up. The use of postoperative radiotherapy was recorded. Biochemical recurrence (BCR) was defined as PSA >0.4 ng/ml. All the analyses were conducted with SAS Statistics Software v.9.4. Key findings and limitations Baseline and intraoperative characteristics were similar between the groups. While PSMs on prostate surface were comparable ( p = 0.8), 3D-guided excisional biopsies had a significantly higher positivity rate (52% vs 13%; p = 0.001), allowing an improved margin control. The 3D group had a lower overall PSM rate (22% vs 39%; p = 0.047), required less postoperative RT (18% vs 35%; p = 0.046), and showed higher continence at 12 mo (91% vs 71%; p = 0.03). Potency and BCR rates were similar. Conclusions and clinical implications The execution of a 3D-AI-AR–guided biopsy at the level of preserved NVBs during nerve-sparing RARP allows correct identification of the tumor with subsequent improvement of margin control. Longer follow-up is required to assess the functional and long-term oncological outcomes of this approach.

Keywords: Artificial intelligence , Augmented reality , Prostate cancer , Radical prostatectomy , Three-dimensional model

Over the years, technology has continued to improve and evolve, along with the virtual representation of real-world environments. These reconstructions serve various fields of research and beyond. The focus of this work is to transfer a real-world road segment into a driving simulation software, aiming to achieve a high level of graphical fidelity. The study is based on the reconstruction of a section of roadway located within the University of Salerno's Fisciano campus. This was made possible through a methodology involving laser scanner surveying of the circuit, subsequent import into modeling software, refinement of any imperfections, and final validation of the resulting model. The last phase took place at the Virtual Reality Laboratory of the Department of Industrial Engineering, where, according to the main goal of the workflow, test drives were carried out to assess the accuracy of the modeled track compared to the real one. After several iterations aimed at ensuring correct compatibility with the driving simulation software and fixing missing points resulting from the scans, the validity of the proposed model was confirmed.

Keywords: 3D Modeling , Driving Simulation , Laser Scanning , Virtual Reality

Background: Public Speaking Anxiety (PSA) is a form of social anxiety spread among university students, negatively affecting both academic performance and overall psychological well-being. Virtual Reality (VR)–based interventions combined with Cognitive Behavioral Therapy (CBT) represent a promising approach for treating PSA, as they enable gradual and controlled exposure to feared social situations by simulating realistic audiences and environments. The primary aim of this study is to evaluate whether the use of VR as a support to standard psychotherapy is effective in managing anxiety and PSA in university students who access the University Psychological Counseling Service (UPCS). Methods: This article outlines the study protocol for a randomized controlled trial (RCT). Participants will be divided into two groups: (1) a control group receiving psychological counseling, and (2) an experimental group that receives psychological counseling integrated with VR interventions based on 360° video scenarios. The intervention will include two VR-based modules: a VR–Exposure and Response Prevention (ERP) module, designed to provide graded immersive exposure to anxiety-provoking scenarios, and a VR–Acceptance and Commitment Training (ACT) module, aimed at enhancing mindfulness and psychological flexibility through guided experiential practice. Psychological and physiological data collected during the sessions will be analyzed to compare the effectiveness of VR-integrated psychotherapy with traditional counseling alone. Discussion: This study will introduce a novel VR-based ERP and ACT training protocol designed to reduce public speaking anxiety in university students by integrating innovative, immersive VR scenarios within a psychological counseling context. The proposed approach may be particularly relevant for university settings, as it offers a scalable, standardized, and controllable VR-supported counseling protocol aimed at reducing PSA, enhancing students' academic functioning (e.g., oral exams and presentations), and strengthening the overall effectiveness of university psychological counseling services. Trial registration: This protocol was registered at the Clinical Trials.gov (Identifier: NCT07351409) on January 16, 2026.

Keywords: Clinical Trial , Psychological Counseling , Public Speaking Anxiety , User studies , Virtual Reality

This paper, in the frame of the Tectonic project (TEchnological Consortium TO develop sustaiNabIlity of underwater Cultural heritage), presents recent results obtained from the work on the shipwreck of the 19th Century schooner Emma, one of the selected submerged archaeological pilot sites. The wreck of Emma is located in Chubut province, Patagonia, Argentina. The main task consisted of the development of a 3D photogrammetric model to be integrated into a virtual reality (VR) end product. The technique employed in the process is described, noting the necessary adjustments required for its application in an underwater environment. Finally, the potential of this type of technique is discussed as a means of promoting tourism as well as underwater heritage management and protection, particularly important in the context of the characteristics of the remote Patagonian region.

Keywords: Patagonia , Photogrammetry , Shipwrecks , Underwater cultural heritage , Virtual reality

Projection-based spatial augmented reality (P-SAR) supports appearance-oriented design evaluation by projecting digital materials onto physical mock-ups, but the projected result may deviate from the intended screen-rendered appearance in both colour distribution and normal-induced shading. This paper proposes a screen-referenced, measurement-driven appearance optimisation framework in which a calibrated monitor serves as the visual reference and the projected mock-up as the optimisation target. The workflow combines controlled Unity rendering, colourimetric measurement, D65 CIE Lab analysis, and MATLAB (R2024b)-based iterative update, and separates the problem into albedo appearance optimisation and shading appearance optimisation. The albedo branch uses dominant-colour grouping and CIEDE2000-guided group-wise correction, while the shading branch uses a lightness-contrast descriptor derived from flat and normal-modulated renderings to update the normal-map-driven shading response. Experiments on ten material textures showed that all 23 identified colour groups converged below the adopted (Formula presented.) threshold of 2.3; the mean texture-level colour difference decreased from 6.24 to 1.36, corresponding to an average reduction of 77.43%. Comparative evaluation showed that the proposed group-wise optimisation outperformed global neutral-grey and global Lab-offset correction baselines. For shading, the mean residual (Formula presented.) decreased from 1.164 to 0.264 (Formula presented.) units, and all ten normal-map cases satisfied the 1.0 (Formula presented.) tolerance. A comparison with a global luminance-contrast baseline further supported the benefit of material-level normal-map update over image-domain contrast adjustment. Additional analyses examined the sensitivity to the number of dominant colour groups and clarified the rationale and scope of the adopted thresholds. Integrated photographic examples provided qualitative illustrations of the overall appearance tendency after the complete workflow, while the quantitative assessment was based on colourimetric and lightness-domain measurements. The full workflow required approximately 26 min per material case, indicating practical feasibility for controlled or semi-controlled P-SAR material appearance preparation and design-review scenarios.

Keywords: appearance optimisation , colourimetric measurement , material textures , projection-based spatial augmented reality

This workshop explores the relationship between eXtended Reality (XR), Artifcial Intelligence, and Human Factors, focusing on the fundamental principles of Human-Computer Interaction within the Intelligent User Interfaces topic. With the increasing integration of large language models, conversational agents, and autonomous AI services into everyday interactions, XR ofers embodied environments that blend language, gesture, gaze, touch, and spatial context. The workshop examines how AI can enable real-time personalization of immersive interfaces, the design of intuitive multimodal interactions with AI agents, and methods for assessing and optimizing human factors such as cognitive load, emotional engagement, and trust. Additional topics include accessibility by design and the social dynamics of AI-enhanced multi-user XR spaces. Positioning XR as both an application domain and a gateway to AI, the workshop fosters research on intelligent, user-centric, and inclusive immersive interfaces.

Keywords: Artifcial Intelligence , Extended Reality , Human Factor , Human-Computer Interaction

The emergence of Industry 4.0 and 5.0 is reshaping the manufacturing landscape, including human-centric approaches that harmonize human intelligence with machine efficiency. In this context, evaluating cognitive workload is essential to ensure operator well-being and optimize productivity. The Human Digital Twin (HDT) framework presents a promising solution, enabling the virtual simulation of human behavior within industrial environments. When integrated with Immersive Virtual Reality (IVR) and physiological monitoring technologies, HDTs can support the ergonomic and cognitive optimization of workstation design. This paper presents the development of a custom IVR application designed to analyze how different cognitive support conditions impact user performance and psychophysiological responses during simulated industrial assembly tasks. The system incorporates multi-modal data collection, including task performance metrics, eye-tracking data, ECG, and electrodermal activity, complemented by validated subjective questionnaires. The experimental protocol is designed to compare traditional instruction-based interfaces with visually guided support systems within a highly immersive environment.

Keywords: Immersive Virtual Reality , Industrial Tasks , Physiological Parameters , Unity Application Development