Characterizing Alzheimer's Disease with INSPECDS: Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes
使用 INSPECDS 表征阿尔茨海默病:用于痴呆亚型内表型分类的综合神经认知和睡眠行为分析仪
基本信息
- 批准号:9345457
- 负责人:
- 金额:$ 53.85万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-07-15 至 2019-04-30
- 项目状态:已结题
- 来源:
- 关键词:AccelerometerAddressAdultAlgorithmsAlzheimer&aposs DiseaseArchitectureAutomatic Data ProcessingBehaviorBehavior assessmentBiological MarkersBlindedBrainCaliforniaCardiovascular DiseasesCause of DeathCharacteristicsChinClassificationClinicClinicalClinical ResearchClinical TrialsDataData AnalysesDatabasesDementiaDepressed moodDevicesDiagnosisDiseaseDisease ProgressionDrug IndustryEconomic BurdenElderlyElectrocardiogramElectroencephalographyElectrophysiology (science)EnrollmentEtiologyFrontotemporal DementiaFundingGeneral HospitalsGoalsHead MovementsHome environmentImpaired cognitionIndividualLewy Body DementiaMachine LearningMalignant NeoplasmsMassachusettsMeasuresMemoryMinorModificationMonitorNeurocognitiveNeurodegenerative DisordersNeurologicNeuropsychological TestsObstructive Sleep ApneaParkinson DiseaseParkinson&aposs DementiaPatientsPerformancePhaseProbabilityProcessREM Sleep Behavior DisorderReportingResearchResearch InfrastructureResearch PersonnelSamplingSecureSleepSleep ArchitectureSleep DeprivationSmall Business Innovation Research GrantStratificationStrokeStudy SubjectSystemTechnologyTechnology AssessmentTestingTimeTrainingUnited States National Institutes of HealthUniversitiesVascular DementiaWireless Technologyalertnessbasebrain behaviorcloud basedcognitive functioncohortcomputerizeddata acquisitiondiagnostic accuracygenetic associationhuman subjectlimb movementmild cognitive impairmentneurocognitive testrelating to nervous systemsynucleinopathytool
项目摘要
PROJECT SUMMARY AND ABSTRACT
It is estimated that Alzheimer's and other neurodegenerative diseases causing dementia will surpass
cancer as the leading cause of death by the year 2040. Alzheimer's is the leading cause of dementia, followed
by synucleinopathies, including dementia with Lewy bodies (DLB) and Parkinson's disease with dementia
(PDD), Fronto-temporal dementia and Vascular dementia. Among clinical researchers focused on
investigating the varying etiologies, genetic associations, biomarkers, and treatment options for Alzheimer's
disease, there is an urgent need for effective tools to aid in the classification of dementia subtypes, in the
earliest detectable stages of the pathophysiological process. To address this unmet need Advanced Brain
Monitoring (ABM) proposes to leverage day and night assessment technologies to create an Integrated
Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes
(INSPECDS) to profile Alzheimer's and other dementias. The core components of the INSPECDS platform will
be the Alertness and Memory Profiler (AMP), the Sleep Profiler, and integrated machine-learning, classification
algorithms, hosted on a secure, cloud-based, infrastructure for automated data processing, analysis, and
reporting. The AMP was developed and validated intially for the purpose of detecting the neurocognitive effects
of sleep deprivation in adults diagnosed with obstructive sleep apnea but has more recently been applied to
assess Alzheimer's and Parkinson's disease. The AMP is unique among neurocognitive testing platforms in
that it is the only one which integrates advanced, electrophysiological measures (e.g., 24-channel, wireless
EEG and ECG) during the performance of computerized neurocognitive tasks and has proven effective in
characterizing cognitive decline in Alzheimer's. This advanced capability permits researchers to explore real-
time relations between fluctuations in alertness, discrete cognitive functions, and specific neural processes
believed to subserve observed performance deficits in Alzheimer's and other dementias. The Sleep Profiler is
an FDA-cleared, easily applied, wireless-EEG device that was developed and validated to measure sleep
architecture for in-home sleep studies with submental (chin) EMG and wireless accelerometers to monitor
head and limb movements to quantify the characteristics of REM-sleep behavior disorder (RBD), considered to
be a prodromal expression of synucleinopathy. Furthermore, the application of sophisticated, machine-
learning, classification algorithms will streamline the processing and analyses of these data to derive statistical
probabilities of Alzheimer's and other dementia subtypes. The overarching goal of the current, Direct-to-Phase
II, SBIR project is to finalize implementation of a secure, cloud-based infrastructure to compile the data
obtained from the AMP and Sleep Profiler, train classification algorithms to discriminate among Alzheimer's
and other dementia subtypes, validate diagnostic accuracy, and integrate optimized classifiers within the cloud-
based architecture. Once completed, the INSPECDS system will be the first clinical research tool of its kind
and find immediate application in both university-based research settings and pharmaceutical industry clinical
trials to aid in the endophenotypic stratification of Alzheimer's and other dementias.
项目概要和摘要
据估计,阿尔茨海默病和其他导致痴呆的神经退行性疾病将超过
到 2040 年,癌症将成为导致死亡的主要原因。阿尔茨海默病是导致痴呆症的主要原因,其次是
突触核蛋白病,包括路易体痴呆 (DLB) 和帕金森病伴痴呆
(PDD)、额颞叶痴呆和血管性痴呆。临床研究人员重点关注
研究阿尔茨海默病的不同病因、遗传关联、生物标志物和治疗方案
疾病,迫切需要有效的工具来帮助对痴呆亚型进行分类,
病理生理过程的最早可检测阶段。为了解决这一未满足的需求 Advanced Brain
监测(ABM)建议利用昼夜评估技术来创建一个综合的
用于痴呆亚型内表型分类的神经认知和睡眠行为分析仪
(INSPECDS) 来分析阿尔茨海默病和其他痴呆症。 INSPECDS 平台的核心组件将
警觉性和记忆分析器 (AMP)、睡眠分析器以及集成的机器学习、分类
算法,托管在安全的、基于云的基础设施上,用于自动数据处理、分析和
报告。 AMP 的开发和验证最初是为了检测神经认知效应
被诊断患有阻塞性睡眠呼吸暂停的成年人睡眠不足的情况,但最近被应用于
评估阿尔茨海默病和帕金森病。 AMP 在神经认知测试平台中是独一无二的
它是唯一一款集成了先进的电生理测量(例如 24 通道、无线
脑电图和心电图)在计算机化神经认知任务的执行过程中被证明是有效的
阿尔茨海默病认知能力下降的特征。这种先进的功能使研究人员能够探索真实的
警觉性波动、离散认知功能和特定神经过程之间的时间关系
据信可以改善阿尔茨海默氏症和其他痴呆症中观察到的表现缺陷。睡眠分析仪是
一种经 FDA 批准、易于使用的无线脑电图设备,专为测量睡眠而开发和验证
使用颏下(下巴)肌电图和无线加速度计进行监测的家庭睡眠研究架构
头部和肢体运动来量化快速眼动睡眠行为障碍 (RBD) 的特征,被认为是
是突触核蛋白病的前驱表现。此外,应用先进的机器
学习、分类算法将简化这些数据的处理和分析,以得出统计数据
阿尔茨海默病和其他痴呆亚型的概率。当前直接阶段的总体目标
II、SBIR项目将最终实现一个安全的、基于云的基础设施来编译数据
从 AMP 和睡眠分析器获得的数据,训练分类算法来区分阿尔茨海默病
和其他痴呆症亚型,验证诊断准确性,并在云中集成优化的分类器
基于架构。一旦完成,INSPECDS 系统将成为同类中第一个临床研究工具
并在大学研究环境和制药行业临床中立即得到应用
帮助阿尔茨海默病和其他痴呆症的内表型分层的试验。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Chris Berka其他文献
Chris Berka的其他文献
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{{ truncateString('Chris Berka', 18)}}的其他基金
CANNABIS IMPAIRMENT DETECTION APPLICATION (CIDA) (T163). SBIR PHASE II. POP: 9/20/2019-9/19/2021. N44DA-19-1218.
大麻损害检测申请(CIDA)(T163)。
- 批准号:
10044153 - 财政年份:2019
- 资助金额:
$ 53.85万 - 项目类别:
Multi-site longitudinal Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes (INSPECDS)
用于痴呆亚型内表型分类的多部位纵向综合神经认知和睡眠行为分析仪 (INSPECDS)
- 批准号:
10603714 - 财政年份:2016
- 资助金额:
$ 53.85万 - 项目类别:
Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes (INSPECDS)
用于痴呆亚型内表型分类的综合神经认知和睡眠行为分析仪 (INSPECDS)
- 批准号:
9360534 - 财政年份:2016
- 资助金额:
$ 53.85万 - 项目类别:
Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes (INSPECDS)
用于痴呆亚型内表型分类的综合神经认知和睡眠行为分析仪 (INSPECDS)
- 批准号:
9046620 - 财政年份:2016
- 资助金额:
$ 53.85万 - 项目类别:
Multi-site longitudinal Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes (INSPECDS)
用于痴呆亚型内表型分类的多部位纵向综合神经认知和睡眠行为分析仪 (INSPECDS)
- 批准号:
10707195 - 财政年份:2016
- 资助金额:
$ 53.85万 - 项目类别:
OTHER FUNCTIONS: QUANTIFICATION OF BEHAVIORAL AND PHYSIOLOGICAL EFFECTS OF DRUGS
其他功能:药物行为和生理影响的量化
- 批准号:
8563859 - 财政年份:2012
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A Novel Approach to Assessing Cognitive State During Real-World Tasks
评估现实世界任务中认知状态的新方法
- 批准号:
8934148 - 财政年份:2011
- 资助金额:
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A Novel Approach to Assessing Cognitive State During Real-World Tasks
评估现实世界任务中认知状态的新方法
- 批准号:
8847048 - 财政年份:2011
- 资助金额:
$ 53.85万 - 项目类别:
TAS::75 0893::TAS QUANTIFICATION OF BEHAVIORAL & PHYSIOLOGICAL EFFECTS OF DRUGS
TAS::75 0893::TAS 行为量化
- 批准号:
8338939 - 财政年份:2011
- 资助金额:
$ 53.85万 - 项目类别:
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7272213 - 财政年份:2007
- 资助金额:
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