Abstract
In this paper, a comparison of the application of neural networks and a first order Markov process amplitude model are reported for the modelling of electoencephalography (EEG) signals recorded from a controlled experimental setup of rodent brain injury with hypoxic-ischemic cardiac arrest. The NN model was found to be superior in modeling the nonlinearities of EEG signal variations.
| Original language | English |
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| Title of host publication | Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings |
| Pages | 2451-2454 |
| Number of pages | 4 |
| Volume | 3 |
| Publication status | Published - 2003 |
| Event | A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Cancun, Mexico Duration: 17 Sept 2003 → 21 Sept 2003 |
Conference
| Conference | A New Beginning for Human Health: the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
|---|---|
| Country/Territory | Mexico |
| City | Cancun |
| Period | 17/09/03 → 21/09/03 |
Keywords
- Brain Injury
- Cardiac Arrest
- EEG
- Markov
- Modeling
- Neural Networks