Cognitive Load Measurement Based on EEG Signals

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Author(s): Tamanna Tasmi (Bangladesh University of Health Sciences, Bangladesh), Mohammad Parvez (Brac University, South Korea)and Jia Uddin (Woosong University, South Korea)
Copyright: 2023
Pages: 10
Source title: Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications
Source Author(s)/Editor(s): Emmanuel Oyekanlu (Drexel University, USA)
DOI: 10.4018/978-1-7998-7852-0.ch006

Keywords: Artificial Intelligence / Information Science Reference / Knowledge Management and Library Science / Manufacturing

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Abstract

Measurement of the cognitive load should be advantageous in designing an intelligent navigation system for visually impaired people (VIPs) when navigating unfamiliar indoor environments. Electroencephalogram (EEG) can offer neurophysiological indicators of the perceptive process indicated by changes in brain rhythmic activity. To support the cognitive load measurement by means of EEG signals, the complexity of the tasks of the VIPs during navigating unfamiliar indoor environments is quantified considering diverse factors of well-established signal processing and machine learning methods. This chapter describes the measurement of cognitive load based on EEG signals analysis with its existing literatures, background, scopes, features, and machine learning techniques.

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Cognitive Load Measurement Based on EEG Signals

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