Gestures analysis during a picture description task: Capacity to discriminate between healthy controls, mild cognitive impairment, and Alzheimer's disease

2022 ◽  
Vol 61 ◽  
pp. 101038
Author(s):  
Sandra Geladó ◽  
Isabel Gómez-Ruiz ◽  
Faustino Diéguez-Vide
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Healthy Controls ◽  
Picture Description ◽  
Description Task

scholarly journals Assessing visuo-constructive functions in patients with subjective cognitive decline, mild cognitive impairment and Alzheimer’s disease with the Vienna Visuo-Constructional Test 3.0 (VVT 3.0)

2021 ◽  
Author(s):  
Noel Valencia ◽  
Johann Lehrner
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Multinomial Logistic Regression ◽  
Subjective Cognitive Decline ◽  
Healthy Controls ◽  
Considerable Potential ◽  
Multinomial Logistic Regression Analysis

Summary Background Visuo-Constructive functions have considerable potential for the early diagnosis and monitoring of disease progression in Alzheimer’s disease. Objectives Using the Vienna Visuo-Constructional Test 3.0 (VVT 3.0), we measured visuo-constructive functions in subjective cognitive decline (SCD), mild cognitive impairment (MCI), Alzheimer’s disease (AD), and healthy controls to determine whether VVT performance can be used to distinguish these groups. Materials and methods Data of 671 participants was analyzed comparing scores across diagnostic groups and exploring associations with relevant clinical variables. Predictive validity was assessed using Receiver Operator Characteristic curves and multinomial logistic regression analysis. Results We found significant differences between AD and the other groups. Identification of cases suffering from visuo-constructive impairment was possible using VVT scores, but these did not permit classification into diagnostic subgroups. Conclusions In summary, VVT scores are useful indicators for visuo-constructive impairment but face challenges when attempting to discriminate between several diagnostic groups.

Cystatin C Levels are Positively Correlated with both Aβ42 and Tau Levels in Cerebrospinal Fluid in Persons with Alzheimer's Disease, Mild Cognitive Impairment, and Healthy Controls

2010 ◽  
Vol 21 (2) ◽  
pp. 471-478 ◽  
Author(s):  
Johan Sundelöf ◽  
Johan Sundström ◽  
Oskar Hansson ◽  
Maria Eriksdotter-Jönhagen ◽  
Vilmantas Giedraitis ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cerebrospinal Fluid ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cystatin C ◽  
Healthy Controls

scholarly journals Attention and inhibition in Mild Cognitive Impairment and Alzheimer's Disease

2013 ◽  
Vol 6 (3) ◽  
pp. 43-50
Author(s):  
Clara Zancada-Menéndez ◽  
Patricia Sampedro-Piquero ◽  
Azucena Begega ◽  
Laudino López ◽  
Jorge Luis Arias
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Reaction Time ◽  
Alzheimer Disease ◽  
Neuropsychological Test ◽  
Reaction Times ◽  
Stop Signal Task ◽  
Healthy Controls

Mild cognitive impairment is understood as a cognitive deficit of insufficient severity to fulfil the criteria for Alzheimer’s disease. Many studies have attempted to identify which cognitive functions are most affected by this type of impairment and which is the most sensitive neuropsychological test for early detection. This study investigated sustained and selective attention, processing speed, and the inhibition process using a sample of people divided into three groups mild cognitive impairment, Alzheimer disease and cognitively healthy controls selected and grouped based on their scores in the Mini Mental State Examination and Cambridge Cognitive Examination-revised. Three tests from the Cambridge Neuropsychological Test Automated Battery (Motor Screening Task, Stop Signal Task and Reaction time) were used as well as the d2 attention test. The results show that that participants with mild cognitive impairment and Alzheimer disease showed lower levels of concentration compared with the cognitively healthy controls group in the d2 test and longer reaction times in the Cambridge Neuropsychological Test Automated Battery, although the differences were not marked in the latter test. The impairments in basic cognitive processes, such as reaction time and sustained attention, indicate the need to take these functions into account in the test protocols when discriminating between normal aging and early and preclinical dementia processes.

[P3-444]: THE STICK DESIGN TEST (SDT): CAN A VISUOCONSTRUCTION TEST HELP DISCRIMINATE HEALTHY CONTROLS (HC), MILD COGNITIVE IMPAIRMENT (MCI) AND ALZHEIMER's DISEASE (AD)?

2017 ◽  
Vol 13 (7S_Part_23) ◽  
pp. P1139-P1140
Author(s):  
Eduardo Sturzeneker Trés ◽  
Diane da costa Miranda ◽  
Sonia Maria Dozzi Brucki ◽  
Maira O. Oliveira ◽  
Mario Amore Cecchini ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Healthy Controls

scholarly journals Linguistic Parameters of Spontaneous Speech for identifying Mild Cognitive Impairment and Alzheimer’s Disease

2021 ◽  
pp. 1-34
Author(s):  
Veronika Vincze ◽  
Martina Katalin Szabó ◽  
Ildikó Hoffmann ◽  
László Tóth ◽  
Magdolna Pákáski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Spontaneous Speech ◽  
Healthy Controls ◽  
Demographic Information ◽  
Linguistic Features ◽  
Significance Level ◽  
Speech Transcripts

Abstract In this paper, we seek to automatically identify Hungarian patients suffering from mild cognitive impairment (MCI) or mild Alzheimer’s Disease (mAD) based on their speech transcripts, focusing only on linguistic features. In addition to the features examined in our earlier study, we introduce syntactic, semantic and pragmatic features of spontaneous speech that might affect the detection of dementia. In order to ascertain the most useful features for distinguishing healthy controls, MCI patients and mAD patients, we will carry out a statistical analysis of the data and investigate the significance level of the extracted features among various speaker group pairs and for various speaking tasks. In the second part of the paper, we use this rich feature set as a basis for an effective discrimination among the three speaker groups. In our machine learning experiments, we will analyze the efficacy of each feature group separately. Our model which uses all the features achieves competitive scores, either with or without demographic information (3-class accuracy values: 68–70%, 2-class accuracy values: 77.3–80%). We also analyze how different data recording scenarios affect linguistic features and how they can be productively used when distinguishing MCI patients from healthy controls.

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