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EEG SignalAnalysis

AI / ML · Signal Processing · Research

Characterization of Working Memory Alterations Using EEG Spectral Analysis

A research-oriented project exploring working-memory-related changes using EEG spectral analysis and feature extraction.

Year
2025
Role
Researcher
Status
Research
Duration
4 months

01 / Context

EEG recordings are analyzed to investigate changes associated with working-memory tasks.

02 / Problem

Raw EEG data is noisy and complex; meaningful patterns have to be extracted carefully before drawing conclusions about cognitive state.

03 / Approach

The project explores spectral analysis, frequency-domain features and classification approaches to characterize working-memory-related changes.

04 / System

Raw EEG data → pre-processing → spectral analysis → feature extraction → classification experiments

05 / Result

A research pipeline that documents EEG processing and explores spectral-domain characterization with machine-learning methods.

06 / Limitations

Results are exploratory and depend on dataset quality, preprocessing choices and the limits of the current validation setup.

07 / Next

Strengthen the feature pipeline and compare multiple classification strategies with clearer validation practices.

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