Bertè, Francesco and Lamponi, Giuseppe and Calabrò, Rocco Salvatore and Bramanti, Placido (2014) Elman neural network for the early identification of cognitive impairment in Alzheimer’s disease. Functional Neurology, 29 (1). pp. 57-65. ISSN 1971-3274
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Abstract
Early detection of dementia can be useful to delay progression of the disease and to raise awareness of the condition. Alterations in temporal and spatial EEG markers have been found in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). Herein, we propose an automatic recognition method of cognitive impairment evaluation based on EEG analysis using an artificial neural network (ANN) combined with a genetic algorithm (GA). The EEGs of 43 AD and MCI patients (aged between 62 and 88 years) were recorded, analyzed and correlated with their MMSE scores. Quantitative EEGs were calculated using discrete wavelet transform. The data obtained were analyzed by the means of the combined use of ANN and GA to determine the degree of cognitive impairment. The good recognition rate of ANN fed with these inputs suggests that the combined GA/ANN approach may be useful for early detection of AD and could be a valuable tool to support physicians in clinical practice.
| Item Type: | Article |
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| Uncontrolled Keywords: | artificial neural network, dementia, EEG, genetic algorithm, MMSE |
| Subjects: | 600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici) |
| Depositing User: | Marina Spanti |
| Date Deposited: | 16 Dec 2015 16:50 |
| Last Modified: | 16 Dec 2015 16:50 |
| URI: | http://eprints.bice.rm.cnr.it/id/eprint/11096 |
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