COGNITIVE LOAD AND SHORT TERM MEMORY EVALUATION BASED ON EEG TECHNIQUES
COGNITIVE LOAD AND SHORT TERM MEMORY EVALUATION BASED ON EEG TECHNIQUES

Summary/Abstract: The performance of learning process (standard system, e-learning or in a virtual environment) is associated with cognitive load and memory working activity. Working memory (or short-term memory) is the ability to hold multiple pieces of information in mind as you solve a problem. An example of short-term memory is a chess master who can explore several possible solutions mentally before choosing the one that will lead to checkmate. This ability to hold information temporarily to complete a task is specifically human. It causes frontal and pre-frontal lobe regions of the brain to become very active. It was proven that the frontal lobe also deals with higher-level cognitive functions like reasoning and judgment. Sometimes called executive function, it is associated with the pre-frontal cortex. The goal of our work is to study different approaches to assess and classify cognitive load and working memory activity along teaching activity. For this purpose, Electroencephalography (EEG) signals were acquired using Emotive EPOC+ neuroheadset and BrainProducts Amplifier with EasyCap helmet. The BrainProducts device offers high accuracy and possibility to investigate signals in Gamma range, but EPOC+ headset allows wireless acquisition that means user’s mobility. The EEG signals were acquired using OpenVibe software from users involved in N-back dual memory tests and some typical reasoning scenarios (math type in our case). The experimental setting involved the use of 16 electrodes among which 6 collected brain signals from frontal and prefrontal brain regions. The raw data were preprocessed to reject the artifacts and filtered to obtain the Delta, Theta, Alpha, Beta, and Gamma waves for further analysis and classification. Particular attention considers the beta wave that reflects active thinking, attention, solving real problems. A low power spectrum denotes relaxation, and it is most evident frontally. Gamma wave denotes mechanism of consciousness, associated with the formation of ideas, language and memory processing, and various types of learning. Alpha wave is also important in our study because it is related to positive and negative emotions, relaxation or responsiveness. For each wave of interest, the power spectrum and signal envelopes were obtained for relaxation state and playing N-back memory and reasoning tests. To classify cognitive load and working memory activity some well-known techniques for regression and classification were used like support vector machine and random forests.

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