Speech-based biomarkers of CNS dysfunction associated with early Alzheimers disea

与早期阿尔茨海默病相关的中枢神经系统功能障碍的基于语音的生物标志物

• 批准号: 8464336
• 负责人: JAMES C. MUNDT
• 金额: $ 15.38万
• 依托单位: CENTER FOR PSYCHOLOGICAL CONSULTATION
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-30 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8464336
• 关键词: Acoustics; Address; Algorithms; Alzheimer disease prevention; Alzheimer' s Disease; Alzheimer' s disease risk; Appearance; Basic Science; Biological Markers; Budgets; California; Central Nervous System Diseases; Characteristics; Clinical; Clinical Research; Cognition; Cognitive; Communities; Computers; Data; Databases; Dementia; Development; Diagnosis; Diagnostic; Differential Diagnosis; Disease; Disease Progression; Early Diagnosis; Elderly; Endogenous depression; Engineering; Evaluation; Foundations; Functional disorder; Health Personnel; Health Services Accessibility; Home environment; Impaired cognition; Independent Living; Individual; Internet; Interview; Laboratories; Linguistics; Longitudinal Studies; Mails; Major Depressive Disorder; Measurement; Measures; Medical; Medical Staff; Memory impairment; Mental Depression; Methods; Monitor; National Institute of Environmental Health Sciences; National Institute on Aging; Nervous System Physiology; Neuraxis; Neurologic; Outcome Assessment; Outcome Measure; Paper; Parkinson Disease; Participant; Patient Monitoring; Patient Recruitments; Patients; Pattern; Persons; Presenile Alzheimer Dementia; Prevention Research; Procedures; Production; Property; Questionnaires; Recruitment Activity; Research; Resources; Sampling; Sampling Studies; Screening procedure; Site; Speech; Statistical Models; Symptoms; System; Technology; Technology Transfer; Telephone; Telephone Interviews; Testing; Time; Transportation; Treatment outcome; U-Series Cooperative Agreements; Universities; Validation; Visit; Voice; base; clinical practice; computerized data processing; cooperative study; cost; data collection evaluation; follow-up; improved; innovation; insight; instrument; member; mild neurocognitive impairment; multiple chronic conditions; new technology; novel; older patient; population based; programs; relational database; response; speech recognition; touchscreen

DESCRIPTION (provided by applicant): More efficient methods to screen and monitor elderly patients in clinical practice and research are needed, but visits to clinical offices are expensive and many older patient are restricted by mobility or transportation access. The Alzheimer's Disease Cooperative Study (ADCS) is evaluating several technology platforms for remotely monitoring patient status at home. Dr. Mary Sano leads this Home-Based Assessment (HBA) study, which completed patient recruitment several years ago and is now completing the final participant follow-up visits. All participants were comprehensively evaluated in diagnostic interviews by medical professionals at study baseline, and are completing similar evaluations at the end of the study (or when a change in clinical status is suspected). A speech-enabled, computer-automated telephone system using interactive voice response (IVR) technology, developed by Dr. Mundt's research team, is one component of the HBA study. Several of the IVR assessments record speech samples for linguistic analysis, acoustic characteristics of the speech patterns are not being analyzed and resources to do so are not included in the HBA study budget. Recent studies have demonstrated that analysis of vocal acoustic characteristics in speech can provide reliable, physiologically-based biomarkers of CNS functioning associated with major depression. Symptomatic similarities between clinical depression and early Alzheimer's disease have been noted for many years, but the extent of overlap and temporal sequencing of emergent symptoms remains unresolved. Objective, physiologically-based biomarkers of CNS dysfunction may provide new insights for diagnosing and managing Alzheimer's patients. The research proposed is to support the development and validation of potential screening measures that could be used for differential diagnosis in clinical practice, as well as provide a foundation for innovative assessment and management approaches for older persons with multiple chronic conditions. This application proposes to merge non-identifiable clinical outcomes measures and medical diagnoses obtained from HBA investigative sites across the nation with audio files of speech samples recorded by the IVR system developed by CPC. The speech samples will be analyzed by signal processing engineers at MIT's Lincoln Laboratory for acoustic properties reflecting physiologically-based biomarkers associated with CNS disorders such as Alzheimer's, Parkinson's, and depression. The clinical and diagnostic information available through the ADCS database will be used to develop and validate multivariate statistical models to improve diagnostic screening, noninvasive monitoring of disease progression, and/or differential diagnoses between conditions. PUBLIC HEALTH RELEVANCE: Restricted mobility of older patients limits research participation and access to treatment providers, so cognitive decline often goes undetected for longer periods than necessary. Efficient methods to remotely monitoring patients from home using automated telephone systems can improve assessment procedures, reduce access barriers, facilitate multicultural non-English speaking interactions, and enhance patient retention at minimal cost. The ADCS Home-Based Assessment Study has recruited a nationally-representative sample of 214 seniors and is monitoring them longitudinally for 4 years to observe emergence of amnestic MCI and conversion of MCI to mild dementia. An automated telephone system is used to record speech samples from study participants, providing a unique opportunity to identify and develop new, objectively- quantifiable biomarkers of CNS dysfunction reflected in the acoustic characteristic of the speech recordings. Such biomarkers would have the potential for population-based cognitive screening as well as remote longitudinal monitoring of patients being treated for memory impairment disorders.

描述（由申请人提供）：在临床实践和研究中需要更有效的方法来筛查和监测老年患者，但前往临床办公室的费用昂贵 许多老年患者受到行动或交通的限制。阿尔茨海默病合作研究 (ADCS) 正在评估多种用于远程监控患者在家状态的技术平台。 Mary Sano 博士领导了这项基于家庭的评估 (HBA) 研究，该研究在几年前完成了患者招募，目前正在完成最终的参与者随访。所有参与者均在研究基线时由医学专业人员进行诊断访谈进行全面评估，并在研究结束时（或怀疑临床状态发生变化时）完成类似的评估。 由 Mundt 博士的研究团队开发的采用交互式语音响应 (IVR) 技术的语音计算机自动化电话系统是 HBA 研究的一个组成部分。一些 IVR 评估会记录用于语言分析的语音样本，但不会分析语音模式的声学特征，并且 HBA 研究预算中不包含用于分析的资源。 最近的研究表明，对语音声学特征的分析可以提供与重度抑郁症相关的中枢神经系统功能的可靠的、基于生理学的生物标志物。多年来人们已经注意到临床抑郁症和早期阿尔茨海默病之间的症状相似性，但重叠的程度和出现的症状的时间顺序仍未解决。客观的、基于生理学的中枢神经系统功能障碍生物标志物可能为诊断和治疗阿尔茨海默病患者提供新的见解。拟议的研究旨在支持开发和验证可用于临床实践中鉴别诊断的潜在筛查措施，例如 并为患有多种慢性病的老年人的创新评估和管理方法奠定基础。 该应用程序建议将从全国 HBA 调查站点获得的不可识别的临床结果测量和医疗诊断与 CPC 开发的 IVR 系统记录的语音样本音频文件合并。麻省理工学院林肯实验室的信号处理工程师将分析语音样本的声学特性，以反映与阿尔茨海默病、帕金森病和抑郁症等中枢神经系统疾病相关的生理生物标志物。通过 ADCS 数据库提供的临床和诊断信息将用于开发和验证多变量统计模型，以改进诊断筛查、疾病进展的无创监测和/或病情之间的鉴别诊断。 公共卫生相关性：老年患者的活动能力受到限制，限制了研究参与和接触治疗提供者的机会，因此认知能力下降往往在比必要的时间更长的时间内未被发现。使用自动电话系统在家中远程监控患者的有效方法可以改进评估程序，减少访问障碍，促进多元文化的非英语互动，并提高患者保留率 以最低的成本。 ADCS 家庭评估研究招募了 214 名老年人作为全国代表性样本，并对他们进行为期 4 年的纵向监测，以观察遗忘性 MCI 的出现以及 MCI 向轻度痴呆的转变。自动电话系统用于记录研究参与者的语音样本，为识别和开发新的、客观可量化的中枢神经系统功能障碍生物标志物提供了独特的机会，这些标志物反映在语音记录的声学特征中。此类生物标志物将具有基于人群的认知筛查以及对正在接受记忆障碍障碍治疗的患者进行远程纵向监测的潜力。