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）：需要在临床实践和研究中进行筛查和监测老年患者的更有效的方法，但是临床办公室的访问昂贵 许多老年患者受到流动或运输的限制。阿尔茨海默氏病合作研究（ADCS）正在评估几个技术平台，以远程监测家里的患者状况。玛丽·萨诺（Mary Sano）博士领导了这项基于家庭的评估（HBA）研究，该研究几年前完成了患者招聘，现在正在完成最终的参与者随访。在研究基准的医学专业人员的诊断访谈中，对所有参与者进行了全面评估，并在研究结束时（或怀疑临床状况变化时）正在完成类似的评估。 由Mundt博士的研究团队开发的交互式语音响应（IVR）技术，具有语音支持的计算机自动化电话系统是HBA研究的一部分。一些IVR评估记录了语言分析的语音样本，没有分析语音模式的声学特征，而这样做的资源也不包括在HBA研究预算中。 最近的研究表明，言语中声音声学特征的分析可以提供与大抑郁症相关的中枢神经系统的可靠生物标志物。临床抑郁症与早期阿尔茨海默氏病之间的症状相似之处已经注意到了很多年，但是重叠和紧急症状的时间测序的程度仍未解决。中枢神经系统功能障碍的客观，基于生理的生物标志物可能为诊断和管理阿尔茨海默氏症患者提供新的见解。提出的研究是支持对临床实践中可用于鉴别诊断的潜在筛查措施的开发和验证，因为 以及为具有多种慢性病的老年人的创新评估和管理方法提供基础。 该申请建议合并从全国HBA调查站点获得的不可识别的临床结果措施和医学诊断，并与CPC开发的IVR系统记录的语音样本的音频文件合并。语音样本将通过MIT的林肯实验室的信号处理工程师进行分析，以反映与CNS疾病（如阿尔茨海默氏症，帕金森氏症和抑郁症）相关的基于生理的生物标志物。通过ADCS数据库获得的临床和诊断信息将用于开发和验证多元统计模型，以改善疾病进展的诊断筛查，无创监测和/或疾病之间的差异诊断。 公共卫生相关性：老年患者的限制流动性限制了研究参与并获得治疗提供者的机会，因此认知能力下降常常在更长的时间内未被发现。使用自动电话系统远程监测患者的有效方法可以改善评估程序，减少访问障碍，促进多元文化的非英语互动，并增强患者的保留率 以最小的成本。基于ADC的家庭评估研究已招募了214名老年人的全国代表性样本，并纵向监视了他们4年，以观察到Amnestic MCI的出现以及MCI转化为轻度痴呆。自动电话系统用于记录研究参与者的语音样本，提供了一个独特的机会，可以识别和开发新的，客观地量化的CNS功能障碍的生物标志物，反映在语音录音的声学特征中。这种生物标志物将具有基于人群的认知筛查以及对接受记忆障碍治疗的患者的远程纵向监测的潜力。