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

基本信息

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
项目类别：
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

项目摘要

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.

父母项目的目标“对情感症状和认知的监测不引人注目使用键盘动力学（UNMASCK）”是为了开发来自的数字生物标志物智能手机打字动力学和运动运动学，可用于预测变化与认知功能障碍和前瞻性变化相关的大脑网络特性临床情绪症状。数字数据是通过新型平台毫不显眼地收集的在具有情绪障碍和健康控制的受试者的转诊样本中，“ Biaffect”。这 Biaffect平台收集与打字行为（例如按键类型）相关的元数据，时间戳，加速度计并将这些数据上传到研究服务器。特定于主题摘要指标是在本地计算的，并通过仪表板向用户呈现。有了这种补充，我们的目标是更新Biaffect平台的软件基础架构为了促进互操作性，与其他研究人员合作，并与智能手机硬件和操作系统升级。为了实现这些目标，我们计划重构Biaffect代码库，以启用更强大的多开发器协作和版本控制。我们还计划创建标准化的数据处理管道以支持协作与可能具有不同水平的数据科学和工程能力的研究人员。