EEGanalüüs

EEGanalüüs refers to the process of analyzing electroencephalogram (EEG) data. An EEG is a non-invasive neurophysiological monitoring method that records the electrical activity of the brain. This electrical activity is detected by electrodes placed on the scalp and is then amplified and displayed as waveforms. EEGanalüüs involves interpreting these waveforms to identify patterns, anomalies, and specific brain states.

The analysis can be performed both visually by trained neurologists and electrophysiologists, and computationally using specialized software. Visual inspection focuses on identifying characteristic EEG rhythms such as alpha, beta, theta, and delta waves, and their distribution across different brain regions. Clinicians look for abnormalities like epileptic discharges, slow waves indicative of brain dysfunction, or changes associated with sleep disorders.

Computational EEGanalüüs employs various signal processing techniques. These include filtering to remove artifacts (e.g., muscle movements or eye blinks), spectral analysis to quantify the power of different frequency bands, event-related potential (ERP) analysis to study brain responses to specific stimuli, and source localization to estimate the origin of brain activity. Machine learning algorithms are increasingly used in EEGanalüüs for automated detection of pathological patterns and for brain-computer interface applications. The goals of EEGanalüüs are diverse, ranging from diagnosing neurological conditions like epilepsy and encephalitis to monitoring anesthesia, studying cognitive processes, and developing assistive technologies.