Easy Screening for Mild Alzheimer's Disease and Mild Cognitive Impairment from Elderly Speech

2018 ◽  
Vol 15 (2) ◽  
pp. 104-110 ◽  
Author(s):  
Shohei Kato ◽  
Akira Homma ◽  
Takuto Sakuma
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Characteristic Curve ◽  
Linear Regression Analysis ◽  
Speech Sound ◽  
The Elderly ◽  
Speech Sounds ◽  
Mel Frequency Cepstral Coefficients

Objective: This study presents a novel approach for early detection of cognitive impairment in the elderly. The approach incorporates the use of speech sound analysis, multivariate statistics, and data-mining techniques. We have developed a speech prosody-based cognitive impairment rating (SPCIR) that can distinguish between cognitively normal controls and elderly people with mild Alzheimer's disease (mAD) or mild cognitive impairment (MCI) using prosodic signals extracted from elderly speech while administering a questionnaire. Two hundred and seventy-three Japanese subjects (73 males and 200 females between the ages of 65 and 96) participated in this study. The authors collected speech sounds from segments of dialogue during a revised Hasegawa's dementia scale (HDS-R) examination and talking about topics related to hometown, childhood, and school. The segments correspond to speech sounds from answers to questions regarding birthdate (T1), the name of the subject's elementary school (T2), time orientation (Q2), and repetition of three-digit numbers backward (Q6). As many prosodic features as possible were extracted from each of the speech sounds, including fundamental frequency, formant, and intensity features and mel-frequency cepstral coefficients. They were refined using principal component analysis and/or feature selection. The authors calculated an SPCIR using multiple linear regression analysis. Conclusion: In addition, this study proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection with receiver operating characteristic curve analysis and reports on the sensitivity and specificity of SPCIR for diagnosis (control vs. MCI/mAD). The study also reports discriminative performances well, thereby suggesting that the proposed approach might be an effective tool for screening the elderly for mAD and MCI.

Using Fractional Anisotropy Imaging to Detect Mild Cognitive Impairment and Alzheimer’s Disease among Mexican Americans and Non-Hispanic Whites: A HABLE Study

2021 ◽  
pp. 1-8
Author(s):  
James R. Hall ◽  
Leigh A. Johnson ◽  
Fan Zhang ◽  
Melissa Petersen ◽  
Arthur W. Toga ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Fractional Anisotropy ◽  
Mexican Americans ◽  
Diffusion Tensor ◽  
Characteristic Curve ◽  
Aging Brain ◽  
Community Based

<b><i>Introduction:</i></b> Alzheimer’s disease (AD) is the most frequently occurring neurodegenerative disease; however, little work has been conducted examining biomarkers of AD among Mexican Americans. Here, we examined diffusion tensor MRI marker profiles for detecting mild cognitive impairment (MCI) and dementia in a multi-ethnic cohort. <b><i>Methods:</i></b> 3T MRI measures of fractional anisotropy (FA) were examined among 1,636 participants of the ongoing community-based Health &amp; Aging Brain among Latino Elders (HABLE) community-based study (Mexican American <i>n</i> = 851; non-Hispanic white <i>n</i> = 785). <b><i>Results:</i></b> The FA profile was highly accurate in detecting both MCI (area under the receiver operating characteristic curve [AUC] = 0.99) and dementia (AUC = 0.98). However, the FA profile varied significantly not only between diagnostic groups but also between Mexican Americans and non-Hispanic whites. <b><i>Conclusion:</i></b> Findings suggest that diffusion tensor imaging markers may have a role in the neurodiagnostic process for detecting MCI and dementia among diverse populations.

scholarly journals Direct and indirect neurological, cognitive and behavioral effects of COVID-19 on the normal elderly, Mild-Cognitive-Impairment and Alzheimer’s Disease populations

2020 ◽  
Author(s):  
Francesco Iodice ◽  
Valeria Cassano ◽  
Paolo Maria Rossini
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Indirect Effects ◽  
Elderly Population ◽  
Health Resources ◽  
The Elderly ◽  
Recovery Phase ◽  
Healthy Elderly

Abstract This article reviews the main articles that have been published so far about the direct and indirect effects of the COVID-19 pandemic on a particularly fragile population represented by the healthy elderly people as well as those with Mild Cognitive Impairment and Alzheimer's disease. Such populations have been among the most affected in the early stages of the pandemic due to the direct effects of the virus and numerous indirect effects now emerge and will have to be carefully assessed over time. The pandemic associated to COVID-19 has shifted most of the health resources to the emergency area and has consequently left the three main medical areas that dealing with the elderly population (oncology, time-dependent diseases and degenerative disease) temporarily “uncovered”. In the phase following the emergency, it will be crucial to guarantee to each area the economic and organizational resources to quickly return to the level of support of the pre-pandemic state. The emergency phase represented an important moment of discussion on the possibilities of telemedicine which will inevitably become increasingly important but all the limits of its use in the elderly population have to be considered. In the post-lockdown recovery phase, alongside the classic medical evaluation, the psychological evaluation must become even more important for doctors caring about people with cognitive decline.

Electroencephalogram Signal Analysis in Alzheimer's Disease Early Detection

2021 ◽  
pp. 224-244
Author(s):  
Pedro Miguel Rodrigues ◽  
Diamantino Rui Freitas ◽  
João Paulo Teixeira ◽  
Dílio Alves ◽  
Carolina Garrett
Keyword(s):  
Alzheimer’S Disease ◽  
Neural Networks ◽  
Alzheimer's Disease ◽  
Artificial Neural Networks ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
The Elderly ◽  
Good Tool ◽  
Electroencephalogram Eeg ◽  
State Of Art

The World's health systems are now facing a global problem known as Alzheimer's disease (AD) that mainly affects the elderly. The goal of this work is to perform a classification methodology skilled with Artificial Neural Networks (ANN) to improve the discrimination accuracy amongst patients at AD different stages comparatively to the state-of-art. For that, several study features that characterized the Electroencephalogram (EEG) signals “slow-down” were extracted and presented to the ANN entries in order to classify the dataset. The classification results achieved in the present work are promising concerning AD early diagnosis and they show that EEG can be a good tool for AD detection (Controls (C) vs AD: accuracy 95%; C vs Mild-cognitive Impairment (MCI): accuracy 77%; MCI vs AD: accuracy 83%; All vs All: accuracy 90%).

Tactile Angle Discrimination Decreases due to Subjective Cognitive Decline in Alzheimer’s Disease

2020 ◽  
Vol 17 (2) ◽  
pp. 168-176
Author(s):  
Zhilin Zhang ◽  
Guanqun Chen ◽  
Jian Zhang ◽  
Tianyi Yan ◽  
Ritsu Go ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Characteristic Curve ◽  
Subjective Cognitive Decline ◽  
Elderly Subjects ◽  
Older Individuals ◽  
Angle Discrimination

Background: Subjective Cognitive Decline (SCD) is the early preclinical stage of Alzheimer's Disease (AD). Previous study provided an invaluable contribution by showing that a tactile angle discrimination system can be used to distinguish between healthy older individuals and patients with mild cognitive impairment and AD. However, that study paid little attention to the relationship between tactile angle discrimination and SCD. Therefore, a means of differentiating Normal Controls (NCs), elderly subjects with SCD, patients with amnestic Mild Cognitive Impairment (aMCI), and AD is urgently needed. Methods: In the present study, we developed a novel tactile discrimination device that uses angle stimulation applied to the index finger pad to identify very small differences in angle discrimination between the NC (n = 30), SCD (n = 30), aMCI (n = 30), and AD (n = 30) groups. Using a three-alternative forced-choice and staircase method, we analyzed the average accuracy and threshold of angle discrimination. Results: We found that accuracy significantly decreased while thresholds of angle discrimination increased in the groups in the following order: NC, SCD, aMCI, and AD. The area under the receiver operating characteristic curve also indicated that the tactile angle discrimination threshold was better than Mini-Mental State Examination scores in distinguishing NC individuals and SCD patients. Conclusion: These findings emphasize the importance of tactile working memory dysfunction in explaining the cognitive decline in angle discrimination that occurs in SCD to AD patients and offer further insight into the very early detection of subjects with AD.

Aggregation of Abnormal Memory Scores and Risk of Incident Alzheimer’s Disease Dementia: A Measure of Objective Memory Impairment in Amnestic Mild Cognitive Impairment

2020 ◽  
pp. 1-12
Author(s):  
Nicholas I. Bradfield ◽  
Kathryn A. Ellis ◽  
Greg Savage ◽  
Paul Maruff ◽  
Samantha Burnham ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Sex Education ◽  
Memory Impairment ◽  
Characteristic Curve ◽  
Imaging Biomarkers ◽  
Subjective Memory ◽  
Prognostic Stratification

Abstract Objectives: The criteria for objective memory impairment in mild cognitive impairment (MCI) are vaguely defined. Aggregating the number of abnormal memory scores (NAMS) is one way to operationalise memory impairment, which we hypothesised would predict progression to Alzheimer’s disease (AD) dementia. Methods: As part of the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing, 896 older adults who did not have dementia were administered a psychometric battery including three neuropsychological tests of memory, yielding 10 indices of memory. We calculated the number of memory scores corresponding to z ≤ −1.5 (i.e., NAMS) for each participant. Incident diagnosis of AD dementia was established by consensus of an expert panel after 3 years. Results: Of the 722 (80.6%) participants who were followed up, 54 (7.5%) developed AD dementia. There was a strong correlation between NAMS and probability of developing AD dementia (r = .91, p = .0003). Each abnormal memory score conferred an additional 9.8% risk of progressing to AD dementia. The area under the receiver operating characteristic curve for NAMS was 0.87 [95% confidence interval (CI) .81–.93, p < .01]. The odds ratio for NAMS was 1.67 (95% CI 1.40–2.01, p < .01) after correcting for age, sex, education, estimated intelligence quotient, subjective memory complaint, Mini-Mental State Exam (MMSE) score and apolipoprotein E ϵ4 status. Conclusions: Aggregation of abnormal memory scores may be a useful way of operationalising objective memory impairment, predicting incident AD dementia and providing prognostic stratification for individuals with MCI.

scholarly journals False Memory and Alzheimer’s Disease Pathology in Patients with Amnestic Mild Cognitive Impairment: A Study with Amyloid PET

2021 ◽  
pp. 172-180
Author(s):  
Eun-Ji Choi ◽  
Bum Joon Kim ◽  
Hyung-Ji Kim ◽  
Miseon Kwon ◽  
Noh Eul Han ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Logistic Regression ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
False Memory ◽  
Visual Recognition ◽  
Characteristic Curve ◽  
Amnestic Mild Cognitive Impairment ◽  
Amyloid Pet

<b><i>Introduction:</i></b> False memory, observed as intrusion errors or false positives (FPs), is prevalent in patients with Alzheimer’s disease, but has yet to be thoroughly investigated in patients with amnestic mild cognitive impairment (a-MCI) with Alzheimer’s disease pathology (ADP). We analyzed false versus veridical memory in individuals with a-MCI and measured the utility of false memory for ADP discrimination. <b><i>Methods:</i></b> Patients with a-MCI who received neuropsychological testing and amyloid PET were included. Patients were categorized into “with” and “without ADP” groups according to PET results. Memory tests assessed veridical and false memory, and the verity of patient responses was analyzed. A logistic regression model was used to evaluate false memory efficiency in discriminating ADP, and the sensitivity and specificity at the optimal level were estimated using the receiver-operating characteristic curve. <b><i>Results:</i></b> Thirty-seven ADP and 46 non-ADP patients were enrolled. The ADP group made more FPs in the recognition tests, and their response verity was significantly lower in every delayed memory test. No group difference, however, was observed in the veridical memory. The logistic regression analysis demonstrated that as the FPs increased, the risk of ADP increased 1.31 and 1.36 times in the verbal and visual recognition tests, respectively. The discriminatory accuracy of the FPs was estimated “low” to “moderate” in the visual and verbal recognition, respectively, with an optimal cutoff above 2.5. <b><i>Conclusion:</i></b> Increased false memory was the only feature to discriminate ADP from non-ADP in individuals with a-MCI. Further studies regarding false memory and its mechanism are warranted.

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