EEG detection of early Alzheimer's disease using psychophysical tasks.

@article{Sneddon2005EEGDO,
  title={EEG detection of early Alzheimer's disease using psychophysical tasks.},
  author={Robert Sneddon and William Rodman Shankle and Junko Hara and Anthony Rodriquez and Donald Hoffman and Utpal Saha},
  journal={Clinical EEG and neuroscience},
  year={2005},
  volume={36 3},
  pages={141-50}
}
In this study, we hypothesized that a quantitative EEG (qEEG) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment (MCI) or mild dementia due to Alzheimer's Disease and Related Disorders (ADRD). The cross-sectional sample consisted of 48 subjects (32 normal aging and 16 ADRD: n = 3 mild dementia, n = 13 MCI FAST stage 3). During EEG recording, subjects performed two… CONTINUE READING

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In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
In this study , we hypothesized that a quantitative EEG ( qEEG ) method for measuring EEG variability combined with specific psychophysical tasks could improve the classification accuracy of subjects with normal aging vs. mild cognitive impairment ( MCI ) or mild dementia due to Alzheimer 's Disease and Related Disorders ( ADRD ) .
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