Gamma Frequency Sensory Stimulation in Probable Mild Alzheimer’s Dementia Patients: Results of a Preliminary Clinical Trial

2021 ◽  
Author(s):  
Diane Chan ◽  
Ho-Jun Suk ◽  
Brennan L. Jackson ◽  
Noah Pollak Milman ◽  
Danielle Stark ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Sensory Stimulation ◽  
Alzheimer’S Dementia ◽  
Alzheimer's Dementia ◽  
Preliminary Clinical Trial ◽  
Gamma Frequency ◽  
Dementia Patients

scholarly journals GRIP PERFORMANCE AGILITY MEASURED WITH A NEW DYNAMOMETER IN SUBJECTS OF ALZHEIMER’S DEMENTIA PATIENTS

2017 ◽  
Vol 1 (suppl_1) ◽  
pp. 1095-1095
Author(s):  
Y. Matsui ◽  
R. Fujita ◽  
A. Harada ◽  
T. Sakurai ◽  
T. Nemoto ◽  
...  
Keyword(s):  
Alzheimer’S Dementia ◽  
Alzheimer's Dementia ◽  
Dementia Patients

Wandering in Alzheimer's Dementia Patients

1993 ◽  
Vol 2 (2) ◽  
pp. 160-175 ◽  
Author(s):  
Mary Lucero ◽  
Sally Hutchinson ◽  
Sue Leger-Krall ◽  
Holly Skodol Wilson
Keyword(s):  
Alzheimer’S Dementia ◽  
Alzheimer's Dementia ◽  
Dementia Patients

scholarly journals Recognition of Alzheimer’s Dementia From the Transcriptions of Spontaneous Speech Using fastText and CNN Models

2021 ◽  
Vol 3 ◽  
Author(s):  
Amit Meghanani ◽  
C. S. Anoop ◽  
Angarai Ganesan Ramakrishnan
Keyword(s):  
Spontaneous Speech ◽  
Alzheimer’S Dementia ◽  
Mel Frequency Cepstral Coefficients ◽  
Text Data ◽  
Alzheimer's Dementia ◽  
Dementia Patients ◽  
Input Sentence ◽  
N Gram ◽  
Mean Square Errors ◽  
State Examination

Alzheimer’s dementia (AD) is a type of neurodegenerative disease that is associated with a decline in memory. However, speech and language impairments are also common in Alzheimer’s dementia patients. This work is an extension of our previous work, where we had used spontaneous speech for Alzheimer’s dementia recognition employing log-Mel spectrogram and Mel-frequency cepstral coefficients (MFCC) as inputs to deep neural networks (DNN). In this work, we explore the transcriptions of spontaneous speech for dementia recognition and compare the results with several baseline results. We explore two models for dementia recognition: 1) fastText and 2) convolutional neural network (CNN) with a single convolutional layer, to capture the n-gram-based linguistic information from the input sentence. The fastText model uses a bag of bigrams and trigrams along with the input text to capture the local word orderings. In the CNN-based model, we try to capture different n-grams (we use n = 2, 3, 4, 5) present in the text by adapting the kernel sizes to n. In both fastText and CNN architectures, the word embeddings are initialized using pretrained GloVe vectors. We use bagging of 21 models in each of these architectures to arrive at the final model using which the performance on the test data is assessed. The best accuracies achieved with CNN and fastText models on the text data are 79.16 and 83.33%, respectively. The best root mean square errors (RMSE) on the prediction of mini-mental state examination (MMSE) score are 4.38 and 4.28 for CNN and fastText, respectively. The results suggest that the n-gram-based features are worth pursuing, for the task of AD detection. fastText models have competitive results when compared to several baseline methods. Also, fastText models are shallow in nature and have the advantage of being faster in training and evaluation, by several orders of magnitude, compared to deep models.

Depression, anxiety, burden and coping mechanisms in the family caregivers of Alzheimer's dementia patients in a turkish sample

2014 ◽  
Vol 22 (3) ◽  
pp. S124
Author(s):  
Ozlem Erden Aki ◽  
Yildiz Kaya ◽  
Sedat Isikli ◽  
Seda Kibaroglu ◽  
Eda Derle Ciftci ◽  
...  
Keyword(s):  
Family Caregivers ◽  
Coping Mechanisms ◽  
Alzheimer’S Dementia ◽  
Alzheimer's Dementia ◽  
Dementia Patients ◽  
The Family ◽  
And Coping

scholarly journals Enhanced proteasome-dependent degradation of the CDK inhibitor p27kip1 in immortalized lymphocytes from Alzheimer's dementia patients

2008 ◽  
Vol 29 (10) ◽  
pp. 1474-1484 ◽  
Author(s):  
Úrsula Muñoz ◽  
Fernando Bartolomé ◽  
Félix Bermejo ◽  
Ángeles Martín-Requero
Keyword(s):  
Alzheimer’S Dementia ◽  
Cdk Inhibitor ◽  
Alzheimer's Dementia ◽  
Dementia Patients

scholarly journals On Which Abilities Are Category Fluency and Letter Fluency Grounded A Confirmatory Factor Analysis of 53 Alzheimer's Dementia Patients

2013 ◽  
Vol 3 (1) ◽  
pp. 179-191 ◽  
Author(s):  
Ilaria Bizzozero ◽  
Stefania Scotti ◽  
Francesca Clerici ◽  
Simone Pomati ◽  
Marcella Laiacona ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Alzheimer’S Dementia ◽  
Alzheimer's Dementia ◽  
Dementia Patients ◽  
Confirmatory Factor ◽  
Category Fluency
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