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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：
10115131
负责人：
Olusola A. Ajilore
金额：
$ 57.94万
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/10115131
关键词：
Address Affective Symptoms Apple Attention Biological Markers Bipolar Disorder Brain Cellular Phone Clinical Clinical assessments Cognition Cognitive Collection Consumption Custom Data Devices Diffusion Disease Disease remission Dysthymic Disorder Ecological momentary assessment Environment Financial cost Functional Imaging Health Care Costs Image Impaired cognition Impairment Improve Access Individual Link Literature Manic Measures Mediating Methods Monitor Mood Disorders Moods Motor Neuropsychological Tests Nodal Outcome Participant Patients Pilot Projects Property Recurrence Research Rest Risk Factors Sampling Secure Structure Symptoms Tablets Technology Time Unipolar Depression United States associated symptom base clinically relevant cognitive function computer human interaction cost effective depressive symptoms evidence base handheld mobile device interest kinematics mood symptom multimodality network dysfunction neuroimaging novel processing speed prospective screening treatment response virtual white matter

项目摘要

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.

项目概要情绪障碍背景下的认知功能障碍与较差的治疗反应有关是缓解后复发的关键危险因素。因此，准确、客观的认知评估情绪障碍患者的功能具有重要的临床实用性。拟议的研究将使用一种新颖的智能手机技术（“BiAffect”）利用打字动力学和运动运动学，不显眼地、安全地、并被动监测情绪障碍参与者的跨诊断样本的认知功能（单相抑郁症、I/II 型双相情感障碍、心境恶劣）。 BiAffect的核心技术是定制的智能手机虚拟键盘取代原生默认键盘，允许收集实时数据当个人在其自然范围内像往常一样与设备进行交互时，具有真实和潜在的临床相关性环境。 BiAffect 将在样本中用于预测 1) 与以下相关的大脑网络特性的改变情绪障碍中的认知功能障碍以及 2) 临床情绪症状的前瞻性变化患有情绪障碍的参与者的跨诊断样本。