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The early detection of diabetic peripheral neuropathy: the development and validation of a novel smartphone application
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Thesis/Dissertation
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2025-12
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Health and Rehabilitation Sciences
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Abstract
The dissertation project developed and validated a novel smartphone application capable of measuring postural instability in individuals with Type 2 Diabetes (T2D) and Diabetic Peripheral Neuropathy (DPN). DPN is a common complication of T2D and is associated with impaired balance and increased risk of falls. Conventional diagnostic methods often rely on subjective reports or expensive equipment, limiting accessibility in many clinical and at-home settings. Given the widespread use of smartphones, this project explored whether a novel smartphone application using built-in sensors could detect subtle postural changes associated with DPN.
By leveraging smartphone accelerometers, Aim 1 demonstrated both construct and criterion-related validity of a custom application in relation to force plate center of pressure (COP) and motion capture system center of mass (COM) postural data. Participants completed quiet stance tasks under varying visual (eyes open/closed) and surface (firm/foam) conditions. The application demonstrated strong test-retest reliability within and across devices as well as high criterion-related validity. It was sensitive to changes in postural control across sensory conditions; however, no differences were found between each device when synchronously collecting postural data, supporting its use as a reliable, accessible measurement tool.
Aim 2 examined whether the application could detect differences in postural control between healthy individuals, individuals with T2D, and those with DPN. The smartphone successfully demonstrated the feasibility of using a validated application capable of detecting subtle postural changes across different diagnostic groups, specifically differentiating individuals with and without DPN using postural outcome measures. Measures such as sway area and sway velocity were especially sensitive, highlighting the progressive impact of diabetic symptoms on balance and the critical role of multisensory integration.
Building on these findings, Aim 3 evaluated the application’s diagnostic performance relative to the Utah Early Neuropathy Scale (UENS). By comparing the postural outcome measures for diagnostic performance against the established UENS in a “known groups” analysis, this investigation provides evidence supporting postural instability, particularly under sensory-challenging conditions, as a viable biomarker for early neuropathic dysfunction. Sway velocity emerged as a robust metric, capable of distinguishing between groups even in the early stages of neuropathy.
The findings suggest that postural sway metrics collected through a widely available and low-cost device could offer a practical solution for early screening and remote monitoring. This work laid the foundation for broader implementation of balance assessments in diabetic care, especially in underserved or resource-limited settings, with the goal of enabling earlier intervention, enhancing clinical judgment, and improving patient outcomes.
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