Abstract
Alzheimer's disease (AD) represents one of the greatest public health challenges worldwide nowadays, because it affects millions of people all over the world and it is expected that the disease will increase considerably in the near future. This study is the first application attempt of cepstral analysis on Electroencephalogram (EEG) signals to find new parameters in order to achieve a better differentiation between EEGs of AD patients and Control subjects. The results show that the methodology that uses a combined Wavelet (WT) Biorthogonal (Bior) 3.5 and cepstrum analysis was able to describe the EEG dynamics with a higher discriminative power than the other WTs/spectrum methodologies in previous studies. The most important significance figures were found in cepstral distances between cepstrums of theta and alpha bands (p=0.00006<0.05).
Original language | English |
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Pages (from-to) | 879-884 |
Number of pages | 6 |
Journal | Procedia Computer Science |
Volume | 64 |
DOIs | |
Publication status | Published - 2015 |
Externally published | Yes |
Event | Conference on ENTERprise Information Systems/International Conference on Project MANagement/Conference on Health and Social Care Information Systems and Technologies, CENTERIS 2015 - Vilamoura, Portugal Duration: 7 Oct 2015 → 9 Oct 2015 |
Keywords
- Alzheimer's Diasease
- Cepstrum
- Cesptral distances
- Electroencephalogram signals
- Wavelet Transform