Duchenne Muscular Dystrophy (DMD) is an X-linked disorder that causes muscle wasting, cardiopulmonary failure, and premature death. Heart failure is a leading cause of death in DMD, but substantial knowledge gaps exist regarding predisposing risk factors. In the general population, hyperglycemia, insulin resistance, and decreased heart rate variability (HRV; reflecting autonomic dysfunction) are associated with cardiomyopathy (CM). It is unclear whether these factors are associated with DMD-CM. Closing this knowledge gap may lead to novel screening and therapeutic strategies to delay progression of DMD related CM. Despite risk factors for hyperglycemia, including the use of glucocorticoids, low muscle mass, obesity, and reduced ambulation, little is known regarding glucose abnormalities in DMD. Some of these same risk factors, along with the distance needed to travel for specialty care, present significant barriers to research participation and clinical care for individuals with DMD. Remote wearable technology may improve research participation in this vulnerable population. Therefore, this study will leverage remote wearable technologies to overcome these barriers and define the relationship between dysglycemia and DMD-CM. In this Aim of the study, the investigators will assess the utility of remote wearable technology to predict changes in traditional metrics of metabolism and cardiac function. In this pilot study, 10 individuals with DMD will undergo cardiac magnetic resonance imaging (CMR) and oral glucose tolerance tests (OGTTs) at baseline and two years. The investigators will remotely assess glycemia (using continuous glucose monitors), HRV (using extended Holter monitors), and activity (using accelerometers) every 6 months over the 2 years and evaluate if changes in wearable metrics predict changes in CMR and OGTT.