Diabetes Mellitus (DM) is a common, multifaceted condition affecting a vast number of individuals worldwide. Type-2 DM (T2D) comprises an estimated 90% of the patient population and is associated with substantial adverse health outcomes with the most important long-term DM-related disorders comprising chronic kidney disease (CKD), cardiovascular disease, and neuropathy and acute conditions such as ketoacidosis. The lack of facile diagnostic tools for the onset of DM-related comorbidities, particularly CKD and ketoacidosis, imposes intervention and treatment limitations. Although multiple biomolecular and biophysical markers have been proposed for DKD, ketoacidosis, and neuropathy, no standardized method or instrumentation currently exists. There is a critical need for improved measurement methods that will evaluate diabetes associated pathology in the home setting as easily as glucose is presently monitored. Here, the proposed work will develop a novel wearable system that integrates analysis of biochemical markers from eccrine sweat and biophysical activity sensing to establish a DM-relevant screening panel. Sweat contains a wealth of biomarkers relevant to health status, including electrolytes, metabolites, organic compounds, inflammatory/stress biomarkers, proteins and hormones. Aspects of sweat rate and composition have been used in assessing cystic fibrosis, drug use, physical fatigue, cognitive state, depression, and hypertension, among other conditions. This fully-integrated system represents a significant step towards improving the clinical assessment of the onset of DM-relevant complications and disease progression. The platform will house multi-use flexible electronics and a network of underlying microfluidic channels and biochemical assays for non-invasive collection and analysis of key sweat biomarkers. The microfluidics portion is a single use substrate that will have onboard colorimetric and electrochemical assays corresponding to identified bioanalytes for real-time analysis. The key biophysical and biochemical parameters monitored correspond to promising indicators of disease states for DKD, ketoacidosis, or neuropathy.