Type 2 Diabetes Mellitus (T2DM) is a multifaceted metabolic disease associated not only with impaired glycemic control but also with reductions in muscle strength, balance, functional mobility, and walking performance. Individuals with T2DM may experience impairments in lower extremity function, postural control, and overall functional performance, which can negatively affect activities of daily living and quality of life. Therefore, the assessment of functional performance using reliable and valid methods is important for clinical monitoring and rehabilitation planning.
The 6-Minute Walk Test (6MWT), Timed Up and Go Test (TUG), and Five-Repetition Sit-to-Stand Test (5xSTS) are widely used clinical assessments for evaluating walking capacity, functional mobility, lower extremity function, and physical performance in individuals with T2DM. Previous studies have demonstrated that these tests provide reliable and clinically meaningful measurements in this population.
In recent years, virtual and mixed reality technologies have provided opportunities to conduct assessments in a more objective, standardized, and user-friendly manner. These technologies also offer important advantages, including real-time data collection, enhanced user interaction, and potential integration into future remote assessment applications. However, evidence regarding the measurement properties of mixed reality-based adaptations of commonly used functional performance tests in individuals with T2DM remains limited.
The aim of this study is to evaluate the validity and reliability of mixed reality-based adaptations of the 6-Minute Walk Test, Timed Up and Go Test, and Five-Repetition Sit-to-Stand Test developed using the Meta Quest 3 platform. In addition, convergent validity will be examined by investigating the relationships between outcomes obtained from the mixed reality-based assessments and measures of knee extensor muscle strength and handgrip strength.
The findings of this study are expected to contribute to the development of innovative, safe, standardized, and digital approaches for assessing functional performance in individuals with Type 2 Diabetes Mellitus. Furthermore, the results may provide a scientific foundation for future digital health applications and remote assessment strategies.