Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics

使用键盘动力学对情感症状和认知进行不引人注目的监测

• 批准号: 10406131
• 负责人: Olusola A. Ajilore
• 金额: $ 22.93万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10406131
• 关键词: 18 year old; Accelerometer; Administrative Supplement; Adolescent; Affective Symptoms; Apple; Behavior; Biological Markers; Biomedical Research; Bipolar Disorder; Brain; Cellular Phone; Clinical; Cognition; Cognitive; Collaborations; Collection; Computer software; Consent; Consultations; Custom; Data; Data Engineering; Data Science; Devices; Disease; Dysthymic Disorder; Emotions; Ensure; Environment; FAIR principles; Feasibility Studies; Female; Financial cost; Foundations; Funding; Future; Future Generations; Goals; Grant; Health; Health Care Costs; Impaired cognition; Impairment; Individual; Infrastructure; Link; Maintenance; Mental Depression; Mental Health; Metadata; Modernization; Monitor; Mood Disorders; Motor; Multiple Sclerosis; Operating System; Parents; Participant; Patients; Periodicity; Persons; Phenotype; Population; Postdoctoral Fellow; Property; Regulation; Research; Research Personnel; Sampling; Secure; Severities; Sleep; Strategic Planning; Sum; Technology; Time; U-Series Cooperative Agreements; Unipolar Depression; United States; United States National Institutes of Health; Update; base; brain health; circadian; clinically relevant; cognitive function; cost effective; dashboard; data analysis pipeline; data ecosystem; data standards; digital; fitness; improved; innovation; interest; interoperability; kinematics; mood symptom; neurobehavioral; neurosteroids; novel; open data; parent project; personalized medicine; precision medicine; prospective; smartphone Application; smartphone based assessment; software development; software infrastructure; suicidal risk; treatment response; virtual

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.

家长项目的目标是“情感症状和认知的低调监测”