# Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics

> **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2021 · $229,293

## Abstract

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.

## Key facts

- **NIH application ID:** 10406131
- **Project number:** 3R01MH120168-02S1
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Olusola A. Ajilore
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $229,293
- **Award type:** 3
- **Project period:** 2020-03-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10406131

## Citation

> US National Institutes of Health, RePORTER application 10406131, Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics (3R01MH120168-02S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10406131. Licensed CC0.

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