Quantitative EEG (QEEG) was originally introduced in the 1970s, coinciding with the computer revolution in EEG. The mathematical analysis of digitally recorded EEG in order to highlight specific waveform components or correlate numerical results with the EEG data for comparison is known as QEEG.

The raw EEG data is recorded and goes through a preprocessing stage that includes re-reference, filtering, segmentation, and artefact rejection. QEEG introduced novel EEG feature extraction techniques, such as frequency band analysis, signal complexity analysis, connection analysis, and network analysis.

The purpose of QEEG is to supplement other examinations, generate more objective evidence for an accurate diagnosis, and facilitate patient outcome assessment. QEEG may give biomarkers for connection diseases or seizure detection, diagnostic methods in neuropsychiatric disorders, or patterns in clinical outcome assessments as a low-cost functional neuroimaging method.

Furthermore, it can be used as a brain activity assessment tool for disorders like encephalopathies, dementia, and even TBI. A pre-interventional role (e.g., pre-surgical evaluation of drug-resistant epilepsy) has also been established.

Regarding the facilities that our QEEG Laboratory possesses, we use a v32 amplifier EEG System, offering a high level of flexibility. The system provides a large variety of modern features, including photic stimulation, timed hyperventilation, data re-montaging, digital video options, spike, and seizure detection, and sleep analysis.

The data exported from the EEG system is then processed using BrainVision Analyzer software (version 2.2.1), where processes like Independent Component Analysis (ICA), Fast Fourier Transformation (FFT) or Segmentation are occurring, acquiring parameters like Coherence, Correlation, or Spectral Power.

Despite the extensive literature on QEEG, it is not frequently employed, and there are several scholarly and contentious discussions concerning its use in the diagnosis of neurological and psychiatric illnesses.

We aim to use QEEG as a tool to improve and enrich the neuroscience research field with novel ideas and discoveries.