Clinical Research Directory

Resection and Defect Repair of Oral Cancer Aided by Mixed Reality Technology

The objective of this exploratory clinical trial is to apply Unreal Engine 5 (UE5)-based Mixed Reality (MR) technology to achieve real-time stereoscopic visualization of surgical planning, personalized free flap harvest and defect reconstruction, accurate oral cancer resection, and precise morphological and volumetric matching of the reconstructed free flap to the defect site. Researchers adopted a parallel controlled design, with participants randomized into three groups: Experimental Group 1 (undergoing Mixed Reality \[MR\] technology-assisted surgery), Experimental Group 2 (undergoing virtual surgical guide-assisted surgery), and Control Group (undergoing conventional surgery). A total of 30 participants will be recruited, with 10 cases in each group. The primary purpose is to confirm the effectiveness of MR technology in assisting oral cancer resection, free flap design, harvest, and defect reconstruction. Allocation concealment will be implemented via the sealed envelope method.

Validity and Reliability of Mixed Reality-Based Mobility Tests in Multiple Sclerosis

Multiple sclerosis (MS) is a demyelinating and neurodegenerative disease of the central nervous system, with common symptoms including muscle weakness, balance impairments, gait difficulties, and fatigue. These symptoms significantly affect individuals' functional mobility, independence, and quality of life. In individuals with MS, reduced lower extremity muscle strength leads to decreased walking speed and loss of balance, resulting in substantial limitations in activities of daily living. Conventional clinical assessment tools, such as the Timed Up and Go (TUG), Five-Repetition Sit-to-Stand Test (5xSTS), and the Timed 25-Foot Walk (T25FW), have been widely used for many years to evaluate functional mobility in individuals with MS. However, these tests typically rely on unidimensional measurement parameters and may demonstrate subjective variability depending on the testing environment and the examiner's experience. Advances in measurement technologies now allow these clinical tests to be transformed into more objective, standardized, and interactive assessment tools. Virtual reality (VR) provides a new perspective for the assessment of motor performance by enabling three-dimensional and interactive simulations of real-world scenarios. VR-based applications allow for the simultaneous evaluation of both motor and cognitive components while also increasing individuals' motivation and engagement. Previous studies have demonstrated that VR technology is effective in neurological rehabilitation, particularly in improving balance, walking speed, and functional mobility in the MS population. In contrast to VR, mixed reality (MR) is a technology that allows individuals to maintain interaction with the real environment while integrating virtual objects into the physical space. The existing literature reveals a notable gap in research focusing on the validity and reliability of VR or MR-based functional tests in individuals with multiple sclerosis. However, no studies to date have investigated the adaptation of lower extremity functional tests (TUG, 5xSTS, and T25FW) to a mixed reality environment. Therefore, the primary rationale of this study is to evaluate the digital applicability of commonly used functional tests in individuals with MS on the Meta Quest 3 virtual reality platform and to determine the validity and reliability of these tests. Additionally, this study aims to examine the relationships between data obtained from the virtual tests and fatigue (Modified Fatigue Impact Scale, MFIS), walking performance (12-Item Multiple Sclerosis Walking Scale: MSWS-12), and knee extensor muscle strength in order to establish the convergent validity of this novel approach. The findings of this study are expected to contribute to the development of an objective, standardized, safe, and innovative digital assessment tool for functional evaluation in individuals with multiple sclerosis. Furthermore, the results will strengthen the scientific foundation for remote monitoring of the rehabilitation process and for the development of personalized treatment programs.