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Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality
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Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: 15 September 2026 | Viewed by 6272

Special Issue Editor

Prof. Dr. M. Carmen Juan

E-Mail Website
Guest Editor
Instituto de Automática e Informática Industrial (ai2), Departamento de Sistemas Informáticos y Computación (DSIC), Universitat Politècnica de València (UPV), 46022 València, Spain
Interests: computer graphics; specifically augmented reality (AR); advanced user interfaces and their applications to psychology and education/edutainment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the integration of advanced sensors within Extended Reality (XR) environments (including Virtual Reality, Augmented Reality, and Mixed Reality). As XR technologies have become increasingly immersive, interactive, and responsive, the use of advanced sensors has become essential in bridging the physical and digital realms across a broad range of applications. Sensors enable the capture of expressive gestures, fine motor movements, spatial positioning, physiological responses (e.g., heart rate, muscle tension, brainwave activity), and environmental conditions. This multidimensional input enables real-time interaction, adaptive feedback, and dynamic visual and auditory experiences, enriching user engagement in education, training, healthcare, entertainment, design, and creative practices. These sensor-driven interactions also support gamified, participatory, and accessible XR experiences that are adaptable to diverse users and contexts. The potential of such systems lies in their ability to enhance immersion, personalize interactions, and support embodied learning and multisensory communication.

We welcome the submission of original research articles, discussions of technical developments, and interdisciplinary studies that explore the design, development, application, and evaluation of sensor-based systems for XR experiences. These submissions may discuss theoretical investigations, system architectures, user experience studies, creative applications, or experimental approaches. The topics of interest include, but are not limited to, the following: full-body motion capture; the use of biosensors to provide affective feedback; spatial tracking for audio-visual synchronization; wearable systems for gesture-based sound control; sensor fusion for immersive environments; and haptic interfaces for enhanced embodied interaction.

The goal of this Special Issue is to foster a deeper understanding of how advanced sensing technologies can transform human engagement in XR, shaping innovative paradigms and increasing inclusion and accessibility. Submissions from both academic researchers and industry practitioners are welcome. Interdisciplinary contributions that integrate scientific, technical, and creative perspectives are particularly encouraged.

Prof. Dr. M. Carmen Juan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • extended reality (XR)
  • virtual reality (VR)
  • augmented reality (AR)
  • mixed reality (MR)
  • advanced sensors
  • sensor fusion
  • wearable technologies
  • multisensory interfaces
  • user experience (UX) in XR
  • creative technologies

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Published Papers (6 papers)

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14 pages, 3018 KB  
Article
Optimized Haptic Feedback and Natural Prehension System for Robotics and Virtual Reality Applications
by Eve Hirel, Odin Le Morvan, Marwan Mahdouf, Prune Picot, Matteo Quinquis and Christophe Delebarre
Sensors 2026, 26(7), 2222; https://doi.org/10.3390/s26072222 - 3 Apr 2026
Viewed by 559
Abstract
As robotics prehension systems and virtual reality applications are in constant evolution, the need for high-fidelity haptic interaction increases. This helps ensure and enhance user immersion and handling precision. While commercial haptic interfaces offer high performance, their prohibitive cost limits their widespread adoption [...] Read more.
As robotics prehension systems and virtual reality applications are in constant evolution, the need for high-fidelity haptic interaction increases. This helps ensure and enhance user immersion and handling precision. While commercial haptic interfaces offer high performance, their prohibitive cost limits their widespread adoption in general-purpose robotics. Furthermore, many low-cost solutions suffer from limited transparency, where the operator constantly fights the friction of the actuator even during free motion. This article presents the design and development of an innovative, cost-effective master–slave robotic system aimed at democratizing efficient haptic feedback devices. The solution is intended for remote manipulation of objects with a maximum mass of 1 kg, while limiting the gripping force to 50 N, thus ensuring the integrity of objects being manipulated. The device includes a master haptic module in the form of a clamp that reproduces the thumb–index–middle finger gripping motion performed by the user. The system relies on a custom haptic interface measuring the angular position of the master gripper, which is transmitted in real time to the slave gripper, so as to adjust the position of the clamp accordingly, thus optimizing the grasping control loop. As soon as an object is detected, using a force sensor integrated into the slave gripper, the master motor renders a resistive force, preventing the user from closing the haptic module. The other part of the system is the slave mechanical gripper with three fingers, each with three phalanges based on human anatomy, allowing the clamp to mechanically conform to irregular object geometries with a single actuator. The last but not least innovative aspect lies in the implementation of a current sensor, which provides the haptic feedback. The force applied by the user is reproduced by the slave gripper using current sensors, eliminating the need for expensive force-torque sensors while maintaining a responsive feedback loop. Full article
(This article belongs to the Special Issue Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality)
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15 pages, 536 KB  
Article
Development of a Virtual Reality Program for Internationally Standardized Non-Face-to-Face Nursing Practicum Education: Design and Validation of a Sensor-Integrated XR System
by Ji Won Oak
Sensors 2026, 26(6), 1843; https://doi.org/10.3390/s26061843 - 14 Mar 2026
Viewed by 427
Abstract
Extended reality (XR) has increasingly been applied to nursing practicum education; however, most systems rely on controller-based interfaces that limit precise capture of continuous fine motor performance and objective assessment. This study developed and validated a sensor-integrated, controller-free XR nursing practicum system (Smart [...] Read more.
Extended reality (XR) has increasingly been applied to nursing practicum education; however, most systems rely on controller-based interfaces that limit precise capture of continuous fine motor performance and objective assessment. This study developed and validated a sensor-integrated, controller-free XR nursing practicum system (Smart Nursing v1.0) grounded in continuous precision sensing. Based on internationally standardized intravenous injection protocols, the system integrated optical hand tracking and speech recognition to quantify hand kinematics, spatial accuracy, procedural sequencing, and verbal compliance. A three-phase validation framework was implemented. Internal technical verification confirmed stable real-time performance (≥60 FPS) and consistent action recognition. In a user-based study involving 63 undergraduate nursing students, XR-based automated scores demonstrated high agreement with expert instructor ratings (ICC = 0.932, 95% CI = 0.91–0.96, p < 0.001). XR baseline scores significantly predicted post-training performance (β = 0.632, p < 0.001) and showed significant incremental validity beyond instructor pre-training scores (ΔR2 = 0.186, p < 0.001). Independent verification confirmed high recognition accuracy (100%) and system stability. These findings indicate that precision sensing enables XR environments to function as reliable performance measurement systems, supporting standardized non-face-to-face nursing practicum education. Full article
(This article belongs to the Special Issue Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality)
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20 pages, 2153 KB  
Article
Fusing Prediction and Perception: Adaptive Kalman Filter-Driven Respiratory Gating for MR Surgical Navigation
by Haoliang Li, Shuyi Wang, Jingyi Hu, Tao Zhang and Yueyang Zhong
Sensors 2026, 26(2), 405; https://doi.org/10.3390/s26020405 - 8 Jan 2026
Cited by 1 | Viewed by 682
Abstract
Background: Respiratory-induced target displacement remains a major challenge for achieving accurate and safe augmented-reality-guided thoracoabdominal percutaneous puncture. Existing approaches often suffer from system latency, dependence on intraoperative imaging, or the absence of intelligent timing assistance; Methods: We developed a mixed-reality (MR) surgical navigation [...] Read more.
Background: Respiratory-induced target displacement remains a major challenge for achieving accurate and safe augmented-reality-guided thoracoabdominal percutaneous puncture. Existing approaches often suffer from system latency, dependence on intraoperative imaging, or the absence of intelligent timing assistance; Methods: We developed a mixed-reality (MR) surgical navigation system that incorporates Adaptive Kalman-filter-based respiratory prediction module and visual gating cues. The system was evaluated using a dynamic respiratory motion simulation platform. The Kalman filter performs real-time state estimation and short-term prediction of optically tracked respiratory motion, enabling simultaneous compensation for MR model drift and forecasting of the end-inhalation window to trigger visual guidance; Results: Compared with the uncompensated condition, the proposed system reduced dynamic registration error from (3.15 ± 1.23) mm to (2.11 ± 0.58) mm (p < 0.001). Moreover, the predicted guidance window occurred approximately 142 ms in advance with >92% accuracy, providing preparation time for needle insertion; Conclusions: The integrated MR system effectively suppresses respiratory-induced model drift and offers intelligent timing guidance for puncture execution. Full article
(This article belongs to the Special Issue Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality)
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19 pages, 4626 KB  
Article
Optimizing the Interaction System for Treadmill Video Games Using a Smartphone’s Front Camera
by Micaela Yanet Martin, Carlos Marín-Lora, María Beatriz Villar-López and Miguel Chover
Sensors 2026, 26(1), 20; https://doi.org/10.3390/s26010020 - 19 Dec 2025
Viewed by 856
Abstract
This paper introduces a lightweight and accessible interaction system for treadmill-based video games, relying solely on facial tracking via a smartphone’s front camera. The system enables real-time estimation of running cadence and directional control through natural head movements, providing an immersive and hands-free [...] Read more.
This paper introduces a lightweight and accessible interaction system for treadmill-based video games, relying solely on facial tracking via a smartphone’s front camera. The system enables real-time estimation of running cadence and directional control through natural head movements, providing an immersive and hands-free gaming experience. A key contribution is the implementation of a FFT-based cadence estimation method that achieves accuracy errors below 5% using only 128 frames, enabling real-time feedback. Preliminary evaluations with 11 participants demonstrate that the FFT-based approach outperforms traditional peak detection in both accuracy and robustness across multiple running speeds. These results position the system as a practical, efficient, and scalable solution for fitness-oriented human–computer interaction, with promising implications for digital health and exergaming. Full article
(This article belongs to the Special Issue Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality)
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24 pages, 5975 KB  
Article
The Impact of Physical Props and Physics-Associated Visual Feedback on VR Archery Performance
by Zhenyu Liu, Haojun Xu, Mengyang Tu and Feng Tian
Sensors 2025, 25(22), 6991; https://doi.org/10.3390/s25226991 - 15 Nov 2025
Cited by 1 | Viewed by 988
Abstract
Most existing virtual reality exergames rely on generic VR devices, which can limit the physical exertion in VR-based exercises. In contrast, physical props can enhance exercise intensity, yet their impact on users’ performance and experience remains understudied, particularly in skill-based tasks. Meanwhile, physical [...] Read more.
Most existing virtual reality exergames rely on generic VR devices, which can limit the physical exertion in VR-based exercises. In contrast, physical props can enhance exercise intensity, yet their impact on users’ performance and experience remains understudied, particularly in skill-based tasks. Meanwhile, physical props offer richer tactile and kinesthetic feedback, which, combined with the visual effects of head-mounted displays, presents a potential solution for improving user experience in VR. To explore this, this study developed a sensor-driven experimental framework for investigating high-skill VR tasks. By integrating vision sensors with standard VR devices, we constructed a VR archery system that enables objective quantification of motor performance. Leveraging the sensor-driven framework, we investigate the effects of physical props and physics-associated visual feedback on players’ performance and experience in VR tasks through an experiment involving 33 participants. By objectively quantifying performance, we reveal a dual-pathway mechanism: physical props significantly increased hand tremor, which in turn impaired aiming accuracy, but this negative effect was effectively moderated by time and physics-associated visual feedback that enabled real-time sensorimotor compensation. While complex physical props reduced task performance, they substantially enhanced enjoyment and presence, particularly demonstrating a synergistic effect on users’ flow experience when combined with physics-associated visual feedback. These findings elucidate the complex interplay between physical prop interfaces and visual feedback in high-skill VR tasks, providing valuable insights for designing VR experiences which balance performance requirements and engagement enhancement. Full article
(This article belongs to the Special Issue Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality)
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24 pages, 7850 KB  
Article
Enhancing Musical Learning Through Mixed Reality: A Case Study Using PocketDrum and Meta Quest 3 for Drum Practice
by Mariano Banquiero, Gracia Valdeolivas and M.-Carmen Juan
Sensors 2025, 25(22), 6836; https://doi.org/10.3390/s25226836 - 8 Nov 2025
Cited by 1 | Viewed by 1862
Abstract
This work presents a mixed reality application for drum learning that combines the PocketDrum virtual drumming device with the Meta Quest 3 headset, integrating hand tracking to provide an immersive, responsive experience without the need for a physical drum set. The system features [...] Read more.
This work presents a mixed reality application for drum learning that combines the PocketDrum virtual drumming device with the Meta Quest 3 headset, integrating hand tracking to provide an immersive, responsive experience without the need for a physical drum set. The system features a modular architecture for real-time strike detection, visual guidance synchronized with music, spatial calibration, and audio rendering. The system additionally makes use of the headset’s color Passthrough during the calibration stage to align the virtual drum kit with the player’s position. To evaluate the system’s performance, a technical analysis was conducted to measure latency, jitter, and sampling rate across the technologies involved. Additionally, a functional validation experiment assessed how spatial hand tracking from Meta Quest 3 improved PocketDrum’s classification accuracy. Results showed that the fused system corrected 19.1% of drum assignment errors made by the inertial-only setup, enhancing consistency in complex rhythmic patterns. These findings demonstrate the effectiveness of sensor fusion for immersive percussion training and support its potential use in accessible, feedback-rich musical learning environments. Full article
(This article belongs to the Special Issue Advanced Sensors in Extended Reality: Virtual, Augmented and Mixed Reality)
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