About & Projects

About WIT

The Wearable and Implantable Technologies (WIT) group at Johns Hopkins develops open methods and software for using data from wearable and implantable technologies in health research. We study how sensor streams can describe everyday movement, sleep, physiology, and health, and build reproducible tools that make those analyses easier to perform and evaluate.

Our work connects data collected in daily life with rigorous statistical and clinical research. Alongside new analytical methods, we share software, documentation, and teaching materials so that research teams can inspect, reuse, and extend the work.

The WIT working group

WIT is one of the Johns Hopkins Department of Biostatistics working groups, led by Ciprian Crainiceanu, Vadim Zipunnikov, and John Muschelli.

The Wearable & Implantable Technology (WIT) Working Group is focused on adapting existing methods when possible and developing new methods when necessary to analyze data generated by wearable sensors used in health studies. Such sensors produce very large, high-resolution, and high-heterogeneity data that capture a variety of health-related characteristics including objectively measured physical activity, blood glucose, and blood pressure. Such data are increasingly integrated with ecological momentary assessment (fast recall-based information obtained from digital apps) and are changing both the scientific and biostatistics research environments.

— Johns Hopkins Department of Biostatistics working groups

Contact: Ciprian Crainiceanu (ccraini1@jhu.edu). See the People page for the group’s leaders, trainees, and alumni.

How the group works

In this short video from the Department of Biostatistics, Ciprian Crainiceanu describes how WIT came together:

  • Origins. WIT started more than a decade ago with a handful of students, when wearable technology was very new. Early questions were basic but hard: how to represent sensor data in a computer, whether an accelerometer can tell if someone is walking, and how to characterize the way they walk. The group grew from there as new people brought new questions.
  • Students first. The group’s primary goal is for students to get the best education possible and go on to the best jobs possible. Science and careers follow from that.
  • Close to the data. Students work directly with collaborators and see how data are collected, for example by observing cardiac surgery with clinical partners, so they understand that the data are connected to people’s lives. Lily Koffman and Marina Hernandez were central to bringing one such surgical collaboration together.
  • A flat structure. Ciprian Crainiceanu, Vadim Zipunnikov, and John Muschelli lead the group, but the hierarchy is kept as flat as possible, and the students drive the work.
  • Regular contact. The group meets weekly, and students meet with their advisers one or two more times each week.