This post is part of a special “Meet the Semi-Finalists” series, featuring Q&As with the five semi-finalists of the Mood Challenge for ResearchKit.

Our final “Meet the Semi-Finalists” post features Mood Toolkit, a ResearchKit study that will provide mental health researchers with a configurable toolkit to study daily emotional health and wellbeing through the ResearchKit framework. The study will combine biometric data from external sensors such as heart rate monitors, with user surveys and machine learning to generate and validate personalized insights and interventions to improve emotional health.

Mood Toolkit is one of five semi-finalists competing to become a finalist and receive $100,000 to develop their designs into prototypes to be piloted with iPhone users. Stay tuned for the finalist announcement in October!

Tell us about your team’s background.
The team leaders of Mood Toolkit are Tim Trull (Professor of Psychological Sciences, MU; studies mood, mood dysregulation, ambulatory assessment, addictions) and Yi Shang (Professor of Computer Science, MU; mobile computing, machine learning). Additional team members include Will Morrison (MU Computer Science), Sean Lane (Assistant Professor of Psychological Sciences, Purdue), Nick Wergeles (MU Computer Science), Peng Sun (MU Computer Science), Zeshan Peng (MU Computer Science), and Luke Guerdan (MU Computer Science).

Why is this Challenge important to you? What inspired your proposal for a ResearchKit study?
We have worked as a team for four years on several projects targeting emotion dysregulation and addictions, building our own apps (Android), integrating sensor data, and conducting analyses. The Mood Challenge inspired us to build an app using ResearchKit, which we had not done previously. Many aspects of the ResearchKit platform allow us to address important questions and issues in the emotion and mood research field. We also used the opportunity to build an app that can be used by many other mood, emotion, and psychological researchers in their own studies.

What have been the biggest challenges and successes in developing your study thus far?
The biggest challenge has been to explore and determine the feasibility of some of our ideas. The ResearchKit platform allows for the collection of massive amounts of data from different channels, but one must keep in mind participant burden and acceptability. Our biggest success is developing some working prototypes and adding some design features that we were introduced to during Boot Camp and in consultation with experts.

You’ve entered the Virtual Accelerator phase, which includes expert mentorship and participation in a live Boot Camp. What’s the biggest insight you’ve uncovered through this process so far?
The importance of good design, participant engagement, and the power of ResearchKit.