Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
Unobtrusive Monitoring of Affective Symptoms and Cognition using Keyboard Dynamics
批准号:
10542659
负责人:
Olusola A. Ajilore
金额:
$63.09万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-03-01 至 2024-12-31
关键词:
AddressAffective SymptomsAppleAttentionBiological MarkersBipolar DisorderBrainCellular PhoneClinicalClinical assessmentsCognitionCognitiveCollectionConsumptionCustomDataDevicesDiagnosticDiffusionDiseaseDisease remissionDysthymic DisorderEcological momentary assessmentEnvironmentFinancial costFunctional ImagingHealth Care CostsImageImpaired cognitionImpairmentImprove AccessIndividualLinkLiteratureManicMeasuresMediatingMethodsMonitorMood DisordersMoodsMotorNeuropsychological TestsNodalOutcomeParticipantPatientsPilot ProjectsPropertyRecurrenceResearchRestRisk FactorsSamplingSecureStructureSymptomsTabletsTechnologyTimeUnipolar DepressionUnited Statesassociated symptomclinically relevantcognitive functioncomputer human interactioncost effectivedepressive symptomsevidence basehandheld mobile deviceinterestkinematicsmood symptommultimodal neuroimagingnetwork dysfunctionneuroimagingnovelprocessing speedprospectivescreeningtreatment responsevirtualwhite matter
中文摘要
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英文摘要
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.
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财政年份:2009
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依托单位:
GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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资助金额:$0.68万
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财政年份:2009
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依托单位:
Brain Metabolites in Type 2 Diabetes and Major Depression Using MRS
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资助金额:$16.24万
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财政年份:2009
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依托单位:
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资助金额:$16.4万
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财政年份:2009
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依托单位:
Brain Metabolites in Type 2 Diabetes and Major Depression Using MRS
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财政年份:2009
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负责人:Olusola A. Ajilore
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依托单位:
Brain Metabolites in Type 2 Diabetes and Major Depression Using MRS
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资助金额:$16.55万
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财政年份:2009
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依托单位:
GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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财政年份:2008
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负责人:Olusola A. Ajilore
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依托单位:
GRAY MATTER DENSITY IN PATIENTS WITH TYPE 2 DIABETES AND MAJOR DEPRESSION
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依托单位:
海外基金