# Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics

> **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2021 · $579,372

## Abstract

PROJECT SUMMARY
Cognitive dysfunction in the context of mood disorders has been associated with poorer treatment response
and is a key risk factor for recurrence after remission. Thus, accurate, objective assessment of cognitive
function in patients with mood disorders is of paramount clinical utility. The proposed study will use a novel
smartphone technology (“BiAffect”) that uses typing dynamics and motor kinematics to unobtrusively, securely,
and passively monitor cognitive function in a transdiagnostic sample of participants with mood disorders
(unipolar depression, bipolar disorder type I/II, dysthymia). The core technology of BiAffect is a custom-built
smartphone virtual keyboard that replaces the native default keyboard, allowing the collection of real-time data
of real and potential clinical relevance while individuals interact with their device as usual within their natural
environment. BiAffect will be used in the sample to predict 1) altered brain network properties associated with
cognitive dysfunction in mood disorders and 2) prospective changes in clinical mood symptoms in a
transdiagnostic sample of participants with mood disorders.

## Key facts

- **NIH application ID:** 10115131
- **Project number:** 5R01MH120168-02
- **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:** $579,372
- **Award type:** 5
- **Project period:** 2020-03-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10115131

## Citation

> US National Institutes of Health, RePORTER application 10115131, Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics (5R01MH120168-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10115131. Licensed CC0.

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