Computerized assessment of linguistic indicators of lucidity in Alzheimer's Disease dementia
阿尔茨海默病痴呆症语言清醒度指标的计算机化评估
基本信息
- 批准号:10093304
- 负责人:
- 金额:$ 44.26万
- 依托单位:
- 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:2020-09-15 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAffectAlzheimer&aposs DiseaseAuditory HallucinationBrainCaregiversCharacteristicsCognitiveCollectionCommunicationComputational LinguisticsConfusionDataData SetDementiaDetectionEtiologyEventFeasibility StudiesFrequenciesGoalsHealth ProfessionalHealth care facilityHumanIndividualIntentionInvestigationLanguageLinguisticsManualsMeasuresMethodsMonitorNatureNerve DegenerationNeurobehavioral ManifestationsNeuronsObservational StudyOutputPatient MonitoringPatientsPersonsProductionReportingResearchSamplingSemanticsSpeechSystemTechnologyTestingTextTherapeutic InterventionTranscriptVideo RecordingWorkadvanced dementiaautomated analysisautomated speech recognitionbaseclear speechcognitive abilitycomputerizeddeep learningevidence baseexperiencelong term memoryprospectiverelating to nervous systemstemtool
项目摘要
The focus of the proposed project is to enable automated detection and analysis of episodes of unexpected
lucidity in individuals with late-stage dementia in which the individual long thought to have succumbed to
dementia and lost most of his or her cognitive abilities temporarily regains the ability to communicate in a clear
and coherent fashion. Currently, the evidence for the existence of these episodes is mostly anecdotal, stemming
from reports by caregivers and healthcare professionals. According to these reports, clear speech and language
are the most prominent features of episodes of cognitive lucidity. The very low frequency and unexpected nature
of these episodes make it challenging to capture objective evidence in the form of audio or video recordings of
these events needed to enable systematic and comprehensive investigations. Thus, it is necessary to develop
technological solutions for automated linguistic analysis that can be used for long-term continuous monitoring of
individuals in late stages of dementia. In this feasibility project, we will develop technology to address two
challenging issues: a) accurate conversion of continuous speech to text, and b) automated analysis of the text
to measure the degree of coherence. Without robust solutions for these problems, our ability to detect and fully
capture and analyze coherent speech in a long-term monitoring setting will remain limited. We will address these
problems by developing and testing a robust automatic speech recognition solution based on deep learning
technology that can operate autonomously (without sending data to external servers). We will also adapt existing
and develop new measures of semantic coherence that are able to work on imperfect transcripts resulting from
automatic speech recognition. In order to develop and validate these tools and approaches, we will use existing
datasets of spontaneous conversational speech by persons with mild and moderate dementia as well as healthy
controls available as part of the Carolina Conversations Collection and Dementia Bank.
拟议项目的重点是实现对意外事件的自动检测和分析
长期被认为已经死亡的晚期痴呆症患者的清醒状态
痴呆症患者失去了大部分认知能力,暂时恢复了清晰的交流能力
和连贯的时尚。目前,这些事件存在的证据大多是轶事,
来自护理人员和医疗保健专业人员的报告。根据这些报道,清晰的言辞和语言
是认知清醒发作的最显著特征。非常低的频率和意想不到的性质
这些事件的发生使得以音频或视频记录的形式捕获客观证据变得具有挑战性
这些事件需要能够进行系统和全面的调查。因此,有必要发展
自动化语言分析的技术解决方案,可用于长期连续监测
痴呆症晚期的个体。在这个可行性项目中,我们将开发技术来解决两个问题
具有挑战性的问题:a)连续语音到文本的准确转换,以及b)文本的自动分析
来衡量连贯性的程度。如果这些问题没有强大的解决方案,我们检测和充分
在长期监测环境中捕获和分析连贯的语音仍将受到限制。我们将解决这些问题
开发和测试基于深度学习的健壮自动语音识别解决方案存在的问题
能够自主运行的技术(无需向外部服务器发送数据)。我们还将调整现有的
并开发新的语义连贯措施,能够处理由以下原因导致的不完美的文本
自动语音识别。为了开发和验证这些工具和方法,我们将使用现有的
轻、中度痴呆症患者和健康人自发会话言语的数据集
作为卡罗莱纳对话集合和痴呆症银行的一部分提供的控制。
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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Trevor Cohen其他文献
Trevor Cohen的其他文献
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{{ truncateString('Trevor Cohen', 18)}}的其他基金
DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLP
DeconDTN:为临床 NLP 解构深度 Transformer 网络
- 批准号:
10626888 - 财政年份:2022
- 资助金额:
$ 44.26万 - 项目类别:
Professional to Plain Language Neural Translation: A Path Toward Actionable Health Information
专业到通俗语言的神经翻译:通向可行健康信息的道路
- 批准号:
10349319 - 财政年份:2022
- 资助金额:
$ 44.26万 - 项目类别:
Professional to Plain Language Neural Translation: A Path Toward Actionable Health Information
专业到通俗语言的神经翻译:通向可行健康信息的道路
- 批准号:
10579898 - 财政年份:2022
- 资助金额:
$ 44.26万 - 项目类别:
DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLP
DeconDTN:为临床 NLP 解构深度 Transformer 网络
- 批准号:
10467107 - 财政年份:2022
- 资助金额:
$ 44.26万 - 项目类别:
DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLP
DeconDTN:为临床 NLP 解构深度 Transformer 网络
- 批准号:
10711315 - 财政年份:2022
- 资助金额:
$ 44.26万 - 项目类别:
Using Biomedical Knowledge to Identify Plausible Signals for Pharmacovigilance
利用生物医学知识识别药物警戒的合理信号
- 批准号:
8914098 - 财政年份:2013
- 资助金额:
$ 44.26万 - 项目类别:
Using Biomedical Knowledge to Identify Plausible Signals for Pharmacovigilance
利用生物医学知识识别药物警戒的合理信号
- 批准号:
8727094 - 财政年份:2013
- 资助金额:
$ 44.26万 - 项目类别:
Encoding Semantic Knowledge in Vector Space for Biomedical Information
在生物医学信息的向量空间中编码语义知识
- 批准号:
8138564 - 财政年份:2010
- 资助金额:
$ 44.26万 - 项目类别:
Encoding Semantic Knowledge in Vector Space for Biomedical Information
在生物医学信息的向量空间中编码语义知识
- 批准号:
7977263 - 财政年份:2010
- 资助金额:
$ 44.26万 - 项目类别:
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