The (ICE) component comprises a catheter with platinum sensors that, when inserted into the brain allows for recording directly from the cerebral cortex of patients with acute brain injury. The Artificial Intelligent (
see Machine learning) and Knowledge Discovery of neurological signals component was first derived from using Intracortical Electrodes in rats (
see Brain–computer interface) to predicting epilepsy seizures in rats by 6 seconds (
see Seizure prediction) [15]. These models used in the clinical environs of noisy domains,
spectral analysis,
knowledge discovery in databases (KDD), discrete finite automata and sequential and coincident power spectra are incorporated into the ICE component to read, learn and predict severe
Neurological disorders.
Clinical demand The prediction, detection and interpretation of abnormal brain electrical activity is an area wherein technological advancement is necessary in that current state-of-the-art methods for electroencephalography (EEG) are retrospective, prone to subjectivity and obviate real-time data interpretation that is often necessary to allow timely and accurate therapeutic intervention by neurologist and neurosurgeon. Intracortical encephalogram signal analysis is done by neurosurgeon clinical researchers and those who create artificial intelligent system for computing
signal analysis,
fourier transforms and Knowledge Discovery in Databases. == References ==