In this work we show that haptic feedback in upper limb motor therapy improves performance and generates a lower mental workload. To demonstrate this, two groups of participants (healthy adults and elders with hand motor problems) used a low-cost haptic device (Novint Falcon) and a non-robotic device (Leap Motion Controller). Participants conducted the same rehabilitation task by using a non-immersive virtual environment. Results show significant differences for all participants regarding precision on the use of the haptic feedback device. Additionally, participants in the older adult group demonstrated a lower mental workload while using the haptic device (Novint Falcon). Finally, qualitative results show that participants preferred to conduct their therapy exercises by using the haptic device, as they found it more useful, easier to use and easier to learn.

Digital fringe projection profilometry (DFPP) is a widely used technique for full-field, non-contact 3D surface measurement, offering precision from the sub-micrometer-to-millimeter scale depending on system geometry and fringe design. This review provides a consolidated synthesis of advances reported between 2022 and 2025, covering projection and imaging architectures, phase formation and unwrapping strategies, calibration approaches, high-speed implementations, and learning-based reconstruction methods. A central contribution of this review is the integration of these developments within a metrological perspective, explicitly relating phase–height transformation, fringe parameters, system geometry, and calibration to dominant uncertainty sources and error propagation. Recent progress highlights trade-offs between sensitivity, robustness, computational complexity, and applicability to non-ideal surfaces, while learning-based and hybrid optical–computational approaches demonstrate substantial improvements in reconstruction reliability under challenging conditions. Remaining challenges include measurements on reflective or transparent surfaces, dynamic scenes, environmental instability, and real-time operation. The review outlines emerging research directions such as physics-informed learning, digital twins, programmable optics, and autonomous calibration, providing guidance for the development of next-generation DFPP systems for precision metrology.

Small-animal phobias has been treated using in vivo exposure therapies (IVET) and virtual reality exposure therapies (VRET). Recently, augmented reality for exposure therapies (ARET) has also been presented and validated as a suitable tool. In this work we identified an ensemble of feedback factors that affect the user experience of patients using ARET systems for the treatment of small-animal phobias, and propose a taxonomy to characterize this kind of applications according to the feedback factors used in the application. Further, we present a customized version of the taxonomy by considering factors/attributes specific to the visual stimuli. To the best of our knowledge, no other work has identified nor provided an explicit classification or taxonomy of factors that affect the user experience of patients using this kind of systems for the treatment of small-animal phobias. Our final aim is to two-fold: (i) provide a tool for the design, classification and evaluation of this kind of systems, and (ii) inspire others to conduct further work on this topic.