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Continuous glucose monitors (CGMs) provide important metrics about the health of study participants. They can provide a time-series of estimated glucose values, and metrics around hypoglycemia episodes (low blood sugar). However, CGMs may falsely read low glucose values and issue "low glucose" alerts when they are being depressed, commonly known as "compression lows." This articles explores some of the common causes and solutions.

Tools for business process automation, robotic process automation (RPA), data integration, and data pipelines (ETL / ELT) at University of Michigan and Michigan Medicine.

A listing of U-M and MM offices and research cores that provide data-related consultation services, including those with expertise with mobile data and mental health data.

Overview of the Sleep Data Automation code, a project developed by the Mobile Technologies Core and the Sleep & Circadian Rhythm Laboratory to automate the process of cleaning sleep data from Fitbit fitness trackers and comparing or joining it to self-reported sleep diary data.