Severity of Alzheimer’s disease and language features in picture descriptions

Kavé, Gitit; Dassa, Ayelet

doi:10.1080/02687038.2017.1303441

Cited by 51 publications

(56 citation statements)

References 46 publications

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“…On the contrary, lexical features that examine lexical knowledge and retrieval, were poorly modified during the cognitive decline, with the notable exception of vocabulary frequency. While the detection of MCI based on POS has been well-established in the literature of Indo-European languages (e.g., [14,38,39]), the present study did not provide evidence for a reduced proportion of open-class words (i.e., nouns, verbs, adjectives, and adverbs) and an increased proportion of closed-class (grammatical function) words in the connected speech produced by Chinese speakers with MCI. Besides, features concerning lexical richness were rather contradictory, as lower Honoré's index suggests lower lexical diversity in the MCI group, while a decreasing Brunét's index indicates richer vocabulary in the MCI group.…”

Section: Acousticcontrasting

confidence: 81%

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Towards the Speech Features of Mild Cognitive Impairment: Universal Evidence from Structured and Unstructured Connected Speech of Chinese

Wang

Lian

Pan³

et al. 2019

Interspeech 2019

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Language impairment is a sensitive biomarker for the detection of cognitive decline associated with mild cognitive impairment (MCI). Recently, knowledge about distinctive linguistic features identifying language deficits in MCI has progressively been enriched and accumulated. However, the employment of a single speech task to elicit connected speech (e.g., structured vs. spontaneous conversations) might limit the generalization of salient linguistic features associated with MCI. Not to mention the scarcity of reports on analysis of extended speech of Chinese. The present study aimed to examine if connected speech production in both situational picture description and spontaneous self-introduction tasks could be used to distinguish individuals with psychometric evidence of MCI and those who were cognitively intact. Speech samples produced by 75 elderly native speakers of Mandarin Chinese, including 19 with MCI and 56 healthy controls were obtained. Macrostructural aspects of language, including lexico-semantic, syntactic, speech fluency, and acoustics were analyzed by applying the linear mixed-effect regression model. Our study revealed decreasing linear trends in semantic contents and syntactic complexity, as well as significantly greater signs of disfluency and reduced speech production in participants with MCI. The findings extended what was reported in the literature, and carry important implications to the screening and diagnosis of suspected MCI.

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Section: Acousticcontrasting

confidence: 81%

“…Semantic Total words/characters [16] Semantic units [19,34] POS rate [14] Idea density [37] Content density [14] Idea efficiency [37] Type-token ratio [14,38,39] Brunét's index [14,38] Syntactic Honoré's index [14,38] Utterance length [16,21] Word/Vocabulary frequency Dependent elements linked to [39] the noun [37]…”

Section: Lexicalmentioning

confidence: 99%

Towards the Speech Features of Mild Cognitive Impairment: Universal Evidence from Structured and Unstructured Connected Speech of Chinese

Wang

Lian

Pan³

et al. 2019

Interspeech 2019

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“…In their picture descriptions, AD patients tend to use more high-frequency words than controls. In the studies surveyed, this effect appeared in overall lexical content [93] and specifically in verbs a matter of debate [16]. Alternatively, discourse efficiency has also been linked to executive function [117], which is known to be impaired in AD [118].…”

mentioning

confidence: 97%

Connected Speech Features from Picture Description in Alzheimer’s Disease: A Systematic Review

Slegers

Filiou

Montembeault

et al. 2018

JAD

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The language changes that occur over the course of Alzheimer's disease (AD) can impact communication abilities and have profound functional consequences. Picture description tasks can be used to approximate everyday communication abilities of AD patients. As various methods and variables have been studied over the years, current knowledge about the most affected features of AD discourse in the context of picture descriptions is difficult to summarize. This systematic review aims to provide researchers with an overview of the most common areas of impairment in AD discourse as they appear in picture description tasks. Based on the 44 articles fulfilling inclusion criteria, our findings reflect a multidimensional pattern of changes in the production (speech rate), syntactic (length of utterance), lexical (word-frequency and use of pronouns), fluency (repetitions and word-finding difficulties), semantic (information units), and discourse (efficiency) domains. We discuss our findings in the light of current research and point to potential scientific and clinical uses of picture description tasks in the context of AD.

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“…The description and analysis of these features are provided in the following subsections. LexicoSyntactic: Our lexicosyntactic processing investigated several features, among which a few features had been explored previously and seen to deteriorate in people with dementia (PwD), including the word count from Orimaye et al [39], type-token ratio (TTR) evaluated by Kave and Dassa [58] as well as content density evaluated by Roark et al [30]. Besides, we proposed and investigated new lexicosyntactic features, namely open and closed class ratios, noun to verb index, verb to noun index, active proposition density, and passive proposition density.…”

Section: ) Feature Engineeringmentioning

confidence: 99%

Predicting Prodromal Dementia Using Linguistic Patterns and Deficits

Alkenani

et al. 2020

IEEE Access

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Language deficiency is evident in the onset of several neurodegenerative disorders yet has barely been investigated when first occurs on the continuum of cognitive impairment for the purpose of early diagnoses. Alzheimer's disease (AD) is a neurodegenerative pathology that develops years prior to clinical manifestations and typically preceded by prodromal stages such as Mild Cognitive Impairment (MCI). Currently, the manual diagnostic procedures of both types are time consuming, following certain clinical criteria and neuropsychological examinations. Our study aims to establish state-of-the-art performance in the automatic identification of different dementia etiologies, including AD, MCI, and Possible AD (PoAD), and to determine whether patients with initial cognitive declines exhibit language deficits through the analysis of language samples deduced with the cookie theft picture description task. Data were derived from the cookie theft picture corpus of DementiaBank, from which all language samples of the identified etiologies were used, with a random subsampling technique that handles the skewness of the classes. Several original lexical and syntactic (i.e., lexicosyntactic) features were introduced and used alongside previously established lexicosyntactics to train machine learning (ML) classifiers against these etiologies. Further, a statistical analysis was conducted to uncover the deficiency across these etiologies. Our models resulted in benchmarks for differentiating all the identified classes with accuracies ranging between 95 to 98% and corresponding F1 values falling between 94 and 98%. The statistical analysis of our lexicosyntactic biomarkers shows that linguistic deviations are associated with prodromal as well as advanced neurodegenerative pathologies, being greatly impacted as cognitive decline increases and suggesting that language biomarkers may aid the early diagnosis of these pathologies.

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Severity of Alzheimer’s disease and language features in picture descriptions

Cited by 51 publications

References 46 publications

Towards the Speech Features of Mild Cognitive Impairment: Universal Evidence from Structured and Unstructured Connected Speech of Chinese

Towards the Speech Features of Mild Cognitive Impairment: Universal Evidence from Structured and Unstructured Connected Speech of Chinese

Connected Speech Features from Picture Description in Alzheimer’s Disease: A Systematic Review

Predicting Prodromal Dementia Using Linguistic Patterns and Deficits

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