Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics

家长项目的目标是“情感症状和认知的低调监测”

The goal of the parent project “Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics (UnMASCK)” is to develop digital biomarkers derived from smartphone typing dynamics and motor kinematics which can be used to predict alterations in brain network properties associated with cognitive dysfunction and prospective changes in clinical mood symptoms. The digital data is unobtrusively collected via a novel platform “BiAffect” in a transdiagnostic sample of subjects with mood disorders and health controls. The BiAffect platform collects metadata related to typing behaviors such as keypress types, timestamps, and accelerometry and uploads these data to the study server. Subject specific summary metrics are calculated locally and presented to the user via a dashboard. With this supplement our goal is to update the software infrastructure of the BiAffect platform in order to facilitate interoperability, collaboration with other researchers, and integration with the smartphone hardware and operating system upgrades. To achieve these goals, we plan to refactor the BiAffect codebase to enable more robust multi-developer collaboration and version control. We also plan to create standardized data processing pipelines to support collaborations with researchers who may have varying levels of capacity for data science and engineering.