BiAffect 12‏+

Thank you for trying BiAffect. In this ResearchKit study, we would like to understand the relationship between mood and neurocognitive functioning in bipolar disorder using keystroke dynamics (such as typing speed and typing errors) and other passive sensor information (such as the accelerometer). You don't have to be a person with bipolar disorder to help us test this app—we also need healthy participants to use the app and serve as a control group.

Currently, diagnosis and treatment of bipolar disorder rely on careful history taking and examination by a clinician, at times aided by self-report or caretaker-informed questionnaires. In general, these reports have to be interpreted by providers in order to extract patterns that could indicate an imminent change in mood. Moreover, they do not necessarily represent objective psycho-physiological markers.

On the other hand, the pervasive use of mobile wireless devices has significantly shaped interpersonal communications in modern life. Indeed, as personal smartphone technology advances, people are increasingly interacting with one another via typed (rather than oral) communications. For this reason, we want to investigate if keyboard dynamics and sensor data from iPhone serve as more objective biomarkers or 'virtual mental-health footprints' of bipolar disorder and mood in general.