LOCATION

The study is based at the University of Illinois Chicago (UIC). Participation is fully remote/ online participants use the BiAffect app on their own iPhone as part of their everyday routine.

DURATION OF RECRUITMENT

Ongoing (citizen science open-ended)

TYPES OF BIPOLAR DISORDER INCLUDED

Bipolar I

Bipolar II

Cyclothymia

Bipolar Spectrum

At-Risk for Bipolar Disorder

IRB APPROVAL

This study has been IRB-approved


THE SCIENTIFIC QUESTION BEING STUDIED

BiAffect investigates whether passive smartphone keyboard dynamics, including typing speed, error rates, backspace frequency, and inter-keystroke intervals, can unobtrusively track brain health and predict mood states in people with and without bipolar disorder. The study uses deep learning algorithms to model the relationship between typing behavior and neuropsychological functioning, circadian rhythms, and cognitive changes associated with mood episodes.

This study is being conducted by the BiAffect research team, led by Alex Leow, MD, PhD (Principal Investigator), and Peter C. Nelson, PhD at University of Illinois Chicago (UIC).

For more information, you can message the team on their Instagram @BiAffect_Health or shoot them an email 
at Hello@BiAffect.com.

BiAffect is now compliant with the EU’s GDPR, the most stringent international data privacy standard. The app is available for free on the Apple App Store: https://apps.apple.com/us/app/biaffect/id1355144276. BiAffect has been featured in the Chicago Tribune, Forbes, the Wall Street  Journal, Rolling Stone, CBS News, TEDxChicago, IEEE spectrum, and many others.