Changes in Speech Chunking in Reading Aloud is a Marker of Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease
Changes in Speech Chunking in Reading Aloud is a Marker of Mild Cognitive Impairment and Mild-to-Moderate Alzheimer's Disease
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DOI：
10.2174/1567205015666180404165017
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发表时间：
2018-01-01
影响因子：
2.1
通讯作者：
Reilly, Richard B.
中科院分区：
文献类型：
--
作者：
De Looze, Celine;Kelly, Finnian;Reilly, Richard B.
背景：言语和语言障碍通常归因于词汇语义缺陷，已在轻度认知障碍 (MCI) 和阿尔茨海默病 (AD) 中得到记录。本研究调查了朗读中言语的时间组织（反映言语产生计划）与认知障碍的关系，特别是 MCI 和 AD 中的工作记忆和注意力缺陷。还评估了从新设计的朗读语音任务中提取的时间特征的辨别能力，以检测 MCI 和 AD。 方法：16 名 MCI 患者、18 名轻度至中度 AD 患者和 36 名健康对照 (HC) 接受了一系列神经心理学测试，并阅读了一组认知负荷不同的句子，通过操纵句子长度和句法复杂性进行探测。结果：我们的结果表明，轻度至中度 AD 与普遍的言语缓慢有关，归因于较多的言语块、无声停顿和失调，以及较慢的言语和发音速度。高认知语言需求背景下的言语分块似乎是 MCI 的一个信息标志，特别与工作记忆和注意力的早期缺陷有关。此外，线性判别分析显示，使用这些语音特征识别 MCI 与 HC、MCI 与 AD 和 AD 与 HC 的 ROC AUC（接收者操作特征曲线下面积）分别为 0.75、0.90 和 0.94。 结论：在临床和社区环境中实施基于语音的互联技术可以为 MCI 和 AD 的早期检测提供更多信息。
Background: Speech and Language Impairments, generally attributed to lexico-semantic deficits, have been documented in Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). This study investigates the temporal organisation of speech (reflective of speech production planning) in reading aloud in relation to cognitive impairment, particularly working memory and attention deficits in MCI and AD. The discriminative ability of temporal features extracted from a newly designed read speech task is also evaluated for the detection of MCI and AD.Method: Sixteen patients with MCI, eighteen patients with mild-to-moderate AD and thirty-six healthy controls (HC) underwent a battery of neuropsychological tests and read a set of sentences varying in cognitive load, probed by manipulating sentence length and syntactic complexity.Results: Our results show that Mild-to-Moderate AD is associated with a general slowness of speech, attributed to a higher number of speech chunks, silent pauses and dysfluences, and slower speech and articulation rates. Speech chunking in the context of high cognitive-linguistic demand appears to be an informative marker of MCI, specifically related to early deficits in working memory and attention. In addition, Linear Discriminant Analysis shows the ROC AUCs (Areas Under the Receiver Operating Characteristic Curves) of identifying MCI vs. HC, MCI vs. AD and AD vs. HC using these speech characteristics are 0.75, 0.90 and 0.94 respectively.Conclusion: The implementation of connected speech-based technologies in clinical and community settings may provide additional information for the early detection of MCI and AD.