As a member of the iDASH project (integrating Data for Analysis, Anonymization, and SHaring), Dr. Heintzman is lead for DMITRI 1.0 (Diabetes Management Integrated Technology Research Initiative).   The DMITRI project currently has a daily life, diabetes management data set from 16 subjects with diabetes over 72-96 hours.  It tracks data from wearable medical equipment, personal logs, nutritional logs, clinical history data, and questionnaires.  The DMITRI datasets are shared through the iDASH portal at the National Center for Biomedical Computing at UCSD. 
This dataset is unique in that it combines an extensive amount of on-body monitoring (insulin pump dosage logs; Dexcom continuous glucose monitor; SenseWear activity monitor with accelerometer, GSR, and skin temperature sensing; Polar heart monitor; Philips Actiwatch; and Zeo sleep monitor) with significant observational and self-report diaries.  For example, three images of each meal (top and side at start and top post-meal) are analyzed by a registered  dietitian and observers log participants’ activities during their days of structured training at a diabetes leadership camp.
One challenge Dr. Heintzman has in continuing this work is the labor-intensive nature of annotating and comparing data from the on-body monitoring, observational, and self-report logs. This problem is a “capture and access” problem similar to the issues GVU has addressed for soldiers, marine biologists, autism researchers, and educators in the past.  We propose to use our experience in pattern recognition and wearable sensing to help Dr. Heintzman reduce the burden of collecting this data for his subjects and analyzing the data for his researchers.  In addition, we hope to apply some of our pattern discovery work to suggest areas of interest in the database to Dr. Heintzman’s researchers.