Comparative Study of Oral and Written Picture Description in Patients with Alzheimer's Disease

Croisile, Bernard; Ska, Bernadette; Brabant, Marie-Josee; Duchêne, A.; Lepage, Yves; Aimard, G; Trillet, M

doi:10.1006/brln.1996.0033

Cited by 176 publications

(210 citation statements)

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“…The semantic content of the elicited speech can then be scored by counting the hsICUs present in the description. Previous studies found that, even in the earliest stages, descriptions by those with AD are less informative compared to those of healthy older adults, producing fewer information units out of a pre-defined list of units, and having less relevant content and lower efficiency (Hier et al, 1985;Croisile et al, 1996;Giles et al, 1996;Ahmed et al, 2013a).…”

Section: Introductionmentioning

confidence: 99%

Vector-space topic models for detecting Alzheimer's disease

Yancheva¹,

Rudzicz²

2016

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Semantic deficit is a symptom of language impairment in Alzheimer's disease (AD). We present a generalizable method for automatic generation of information content units (ICUs) for a picture used in a standard clinical task, achieving high recall, 96.8%, of human-supplied ICUs. We use the automatically generated topic model to extract semantic features, and train a random forest classifier to achieve an F-score of 0.74 in binary classification of controls versus people with AD using a set of only 12 features. This is comparable to results (0.72 F-score) with a set of 85 manual features. Adding semantic information to a set of standard lexicosyntactic and acoustic features improves F-score to 0.80. While control and dementia subjects discuss the same topics in the same contexts, controls are more informative per second of speech.

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Section: Introductionmentioning

confidence: 99%

Vector-space topic models for detecting Alzheimer's disease

Yancheva¹,

Rudzicz²

2016

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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“…Croisile et al (1996) found "simplified but relatively correct syntax" in a picture description task provided by patients with pAD compared to controls, though the effect was more pronounced in written than oral descriptions. Hier et al (1985) studied oral descriptions obtained from a mixed group, consisting of patients with pAD and dementia due to vascular brain damage.…”

Section: Connected Speech Analysismentioning

confidence: 77%

“…Our initial aim was to quantify the semantic content of discourse produced by patients through the analysis of semantic units, defined as "a relevant, truthful and non-redundant fact or plausible inference about the stimulus picture" (Bayles et al 1989). Production of semantic units can be quantified using a checklist of key elements represented in the picture description task, an approach that has consistently revealed differences between samples of connected speech produced by pAD patients and controls (Croisile et al 1996;Hier et al 1985;Tomoeda/Bayles 1993;Vuorinen et al 2000). Secondly, we aimed to establish whether semantic units were reduced globally, or whether there was a disproportionate reduction of specific classes of information.…”

Section: Lexico-semantic Processing In Early Alzheimer's Diseasementioning

confidence: 99%

“…Following the classification of Croisile et al (1996) semantic unit identification was scored overall and for four subclasses of information from the picture description task: subjects, locations, objects (noun units) and actions (verb units). Idea density and efficiency of language were also calculated.…”

Section: Lexico-semantic Processing In Early Alzheimer's Diseasementioning

confidence: 99%

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Spoken discourse in Alzheimer' disease: a review

Ahmed

Garrard

2012

linguistica

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In its typical form, Alzheimer’s disease (AD) manifests with early impairment in episodic memory. Evidence suggests that language deficits also occur early on in the disease process, and can be detected at the preclinical stage, suggesting that language could constitute an important diagnostic marker for disease. Additionally, a number of variant clinical presentations of AD are recognised, due to an atypical distribution of pathology at onset, including a minority of patients presenting with a slowly progressive language impairment. We review language performance in typical and atypical presentations of AD, and describe a series of recent, novel findings examining the language phenotype of typical AD.

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“…• Revisions: This feature is measured as the count of pause positions where the patient retraced a preceding error and then made a correction (MacWhinney, 2000;de Lira et al, 2011;Croisile et al, 1996).…”

Section: Lexical Featuresmentioning

confidence: 99%

Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

2014

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ii Introduction Mental health problems are among the costliest challenges we face, in every possible sense of cost. The numbers are staggering: to cite just a few, in the United States mental health spending accounted for $33 billion in 1986, $100 billion in 2003, and is projected to increase to $203 billion for 2014; some 25 million American adults will have an episode of major depression this year; and suicide is the third leading cause of death for people between 10 and 24 years old. The importance of clinical psychology as a problem space cannot be overstated.For clinical psychologists, language plays a central role in diagnosis. Indeed, many clinical instruments fundamentally rely on what is, in effect, manual annotation of patient language. Applying language technology in this domain, e.g. in language-based assessment, could potentially have an enormous impact, because many individuals are motivated to underreport psychiatric symptoms (consider active duty soldiers, for example) or lack the self-awareness to report accurately (consider individuals involved in substance abuse who do not recognize their own addiction), and because many people -e.g. those without adequate insurance or in rural areas -cannot even obtain access to a clinician who is qualified to perform a psychological evaluation. Bringing language technology to bear on these problems could potentially lead to inexpensive screening measures that could be administered by a wider array of healthcare professionals, which is particularly important since the majority of individuals who present with symptoms of mental health problems do so in a primary care physician's office. Given the burden on primary care physicians to diagnose mental health disorders in very little time, the American Academy of Family Physicians has recognized the need for diagnostic tools for physicians that are "suited to the realities of their practice".Although automated language analysis connected with mental health conditions goes back at least as far as the 1990s, it has not been a major focus for computational linguistics compared with other application domains. However, recently there has been noticable uptick in research activity on this topic. One recent shared task brings together research on the Big-5 personality traits, and another involved research on identification of emotion in suicide notes. Research has been done on language analysis in the context of, for example, autistic spectrum disorders, dementia, depression, post-partum depression, general life satisfaction , and suicide risk. This increase in attention is consistent with, and gains power from, the recent rise in computational linguistics activity connected with computational social science more broadly.With computational linguistics research on this topic moving toward critical mass, one key goal of this workshop was to bring together researchers to discuss the current state of the art, share methods, and set directions for the future. The workshop had a second goal also, though: to directly engage cli...

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Comparative Study of Oral and Written Picture Description in Patients with Alzheimer's Disease

Cited by 176 publications

References 0 publications

Vector-space topic models for detecting Alzheimer's disease

Vector-space topic models for detecting Alzheimer's disease

Spoken discourse in Alzheimer' disease: a review

Proceedings of the Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality

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