In order to prepare for a future home study, the ability to detect, grade, and classify physical activity so as to appropriately adjust system parameters is vital in helping to prevent exercise induced hypoglycemia in the home setting. Currently, our closed-loop system transmits heart rate and accelerometry outputs from a Zephyrlife BioPatch monitoring device to a Nexus 5 smart phone master controller via Bluetooth. The algorithm then converts the heart rate and accelerometry data into modified estimated energy expenditure - accounting for age, weight, height, sex, resting and sitting heart rates - to determine if exercise is present. However, further data collection is needed to hone the specificity and sensitivity of the detection algorithm to account for a wide variety of subject characteristics and activities.