This system automatically and quantitatively monitors electrical activity in the brain in real-time. The electroencephalograph (EEG) is an important clinical tool for the evaluation and diagnosis of neuropathology. The EEG allows doctors to non-invasively evaluate changes in brain electrical activity that may be associated with neurological disorders. EEGs are used in the diagnosis or monitoring of epilepsy, coma, stroke, as well as metabolic and sleep disorders. Most notably EEGs play a particularly vital role in detecting seizures and other neurological disabilities in newborn infants. While EEGs provide doctors with a wealth of valuable information, analyzing and interpreting the data is often challenging even for neurophysiologists. Further, data is often evaluated hours after the neurological event took place, which can delay timely and accurate medical decisions. Researchers at the University of Florida have developed a real-time brain monitoring system that enables changes in brain electrical activity to be quantitatively measured. This technology allows doctors to be immediately alerted if their patient exhibits changes in brain electrical activity falling outside of a normal range.
This technology employs powerful linear and nonlinear mathematical algorithms in order to quantitatively measure deviations in brain activity from a normal state. EEGs of patients are analyzed in real-time and compared to an optimal normal range. Physicians will be automatically alerted if the patent's brain activity falls above or below this normal range. Once alerted, the physician can then evaluate the patient's brain activity, as well as a host of other physiological parameters such as heart rate, muscle tone, oxygenation, cerebral perfusion, arterial pressure, and lung tidal volume, recorded in the critical periods before during and after the neurological event.
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important clinical tool
accurate medical decisions
nonlinear mathematical algorithms
lung tidal volume
quantitatively measure deviations