Análisis de señales en el neuromonitoreo
Abstract
In recent years, technological advances have allowed improving procedures in the neurological field. Functional monitoring research has grown considerably because of the new hardware and software possibilities towards online computerization in the operating room. The main approach to improve neurosurgical and anesthetic procedures is neurophysiological monitoring, research in this field is mainly concerned with electroencephalogram (EEG) analysis. Recording the EEG signal is particularly helpful to measure the functioning of the central nervous system and assess anesthetic depth during surgical procedures, or to prevent neurological damage in endovascular embolization or to detect epileptic foci whether a patient with intractable epilepsy is undergoing a surgical resection. Today, there exist some effective signal processing algorithms applying in neurophysiological signals. We can be mentioned spectral analysis, correlation methods, temporal characteristics, Time-Frequency Distributions, topographic brain mapping by interpolation techniques, or multiresolution analysis using wavelet transform. The main subject in this report is reviews some of the most powerful and effective algorithms used in the signal processing to get online electroencephalogram signal analysis.
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