Patients with upper limb disorders are limited in their activities of daily living and impose an important healthcare burden due to the repetitive rehabilitation they require. A way to reduce this burden is through home-based therapy using virtual reality solutions, since they are readily available, provide immersion, and enable accurate motion tracking, and custom applications can be developed for them. However, there is lack of guidelines for the design of effective VR rehabilitation applications in the literature, particularly for bimanual training. This work introduces a VR telerehabilitation system that uses off-the-shelf hardware, a real-time remote setup, and a bimanual training application that aims to improve upper extremity motor function. It is made of six activities and was evaluated by five physiotherapists specialised in (2) neuromotor disorders and (3) functional rehabilitation and occupational therapy. A descriptive analysis of the results obtained from the System Usability Scale test of the application and a collection of qualitative assessments of each game have been carried out. The application obtained a mean score of 86.25 (±8.96 SD) in the System Usability Scale, and the experts concluded that it accurately reproduces activities of daily living movements except for wrist and finger movements. They also offer a set of design guidelines.

Background: Neck pain, one of the most common musculoskeletal diseases, affects 222 million people worldwide. The cervical range of motion (CROM) is a tool used to assess the neck’s state across three movement axes: flexo-extension, rotation, and lateral flexion. People with neck pain often have a reduced CROM, and they feel pain at the end-range and/or accompany neck movements with compensatory trunk movements. Virtual reality (VR) setups can track the movement of the head and other body parts in order to create the sensation of immersion in the virtual environment. Using this tracking position information, a CROM assessment can be performed using a VR setup that may be carried out autonomously from the user’s home. The objectives of this study were to develop a VR experience that could be used to perform a CROM assessment, and to evaluate the intra-rater and inter-rater reliability of the CROM measures guided by this VR experience. To the best of our knowledge, a study of this type has not been carried out before. Materials & Methods: A total of 30 asymptomatic adults were assessed using a VR device (HTC Vive Pro Eye™). Two raters provided support with the VR setup, and the participants were guided by the VR experience as they performed the movements. Each rater tested each subject twice, in random order. In addition to a head-mounted display (HMD), a tracker located on the subject’s back was used to measure trunk compensatory movements. The CROM was estimated using only the HMD position and this measurement was corrected using the tracker data. The mean and standard deviation were calculated to characterize the CROM. To evaluate the reliability, the interclass correlation coefficients (ICC) were calculated for intra-rater and inter-rater analysis. The standard error of measurement and minimum detectable change were also calculated. The usability of the VR system was measured using the Spanish version of the System Usability Scale. Results: The mean CROM values in each axis of movement were compatible with those described in the literature. ICC values ranged between 0.86 and 0.96 in the intra-rater analysis and between 0.83 and 0.97 in the inter-rater analysis; these values were between good and excellent. When applying the correction of the trunk movements, both the intra-rater and inter-rater ICC values slightly worsened except in the case of the lateral flexion movement, where they slightly improved. The usability score of the CROM assessment/VR system was 86 points, which is an excellent usability score. Conclusion: The reliability of the measurements and the usability of the system indicate that a VR setup can be used to assess CROM. The reliability of the VR setup can be affected by slippage of the HMD or tracker. Both slippage errors are additive, i.e., only when the sum of these two errors is less than the compensatory movement do the measurements improve when considering the tracker data.

Cervical pain is a highly prevalent musculoskeletal condition, affecting an estimated 222 million people globally. There is a clear need for novel technologies that enable more accessible and affordable care delivery for this population. Assessing the Cervical Range of Motion (CROM) of the patient is a necessary step before designing a treatment plan, and periodically during treatment to monitor patient progress. This study analyzes the use of three VR setups (HTC Vive Pro Eye, HP Reverb G2, and Meta Quest 2) for CROM assessment, representing high-end, mid-range, and low-end devices. 94 individual assessment sessions were conducted by the same rater using a custom-designed VR application. This application simulates a medical environment and guides users through the required neck movements while storing tracking data for later analysis. Intra-rater reliability, measured by the Intraclass Correlation Coefficient, ranged from good to excellent for all setups: 0.81 $$-$$ 0.96 for HTC Vive Pro Eye, 0.92 $$-$$ 0.93 for Meta Quest 2, and 0.89 $$-$$ 0.94 for HP Reverb G2. The low-cost options presented slightly higher ICC than the high-end setup, although this difference was not statistically significant. The HMD physical design, weight distribution, and gripping mechanisms had a larger impact on the reliability than the tracking technology used. An anonymous survey showed high usability scores for all three devices. These findings support VR technology as a reliable and user-friendly tool for CROM assessment and show that low-cost devices can be used without compromising reliability or usability.

Neck pain is a significant global health concern and a leading cause of disability. Conventional clinical neck assessments often rely on maximal Cervical Range of Motion (CROM) measurements, which may not accurately reflect functional limitations experienced during activities of daily living (ADLs). This study introduces a novel approach to evaluate neck functional status by employing a virtual reality (VR) environment to simulate an apple-harvesting task. Three-dimensional head kinematics were continuously recorded in 60 participants (30 with clinically significant neck pain and 30 asymptomatic) as they performed the task. Spectral analysis of the data revealed that individuals with neck pain exhibited slower head rotation speed, particularly in the transverse and frontal planes, compared to the pain-free group, as evidenced by higher spectral power in the low-frequency band [0, 0.1] Hz and lower power in the [0.1, 0.5] Hz band. Furthermore, participants with neck pain required significantly more time to complete the apple-harvesting task. The VR system demonstrated high usability (SUS score = 84.21), and no adverse effects were reported. These findings suggest that VR-based assessment during simulated ADLs can provide valuable information about the functional impact of neck pain beyond traditional CROM measurements, potentially enabling remote evaluation and personalized telerehabilitation strategies.

Virtual Reality (VR) setups connected to a computer offer a more realistic experience compared to standalone devices. However, these setups require high-performance hardware, making them expensive and less portable. A more cost-effective and portable alternative involves leveraging shared cloud or edge resources to render VR experiences. This work introduces NajVR, an architecture for remote rendering of VR applications that requires only commodity hardware on the client and includes LHE, a codec designed to minimize latency and resistant to packet loss that uses the user’s gaze data to improve the encoding process. NajVR does not require any modifications to the VR applications or their runtime environment. In NajVR an application on the client captures pose data and events generated by the VR hardware and transmits them to the server. On the server, a driver processes these data, simulating the VR hardware as if it were connected directly to it. This driver also captures the images to be displayed on the Head Mounted Display (HMD), encodes them, and transmits them to the client. NajVR supports an arbitrary number of trackers and takes advantage of the user’s gaze data to improve the perceived quality. The architecture round-trip latency was measured, and the LHE codec was compared with four different configurations of two commercially available codecs. The tests were carried out on both high-bandwidth and resource-constrained networks and in WAN setups. In the best-case scenario, latencies of just over 20 ms were achieved.