ABSTRACT
At the heart of neuroergonomics are sensor technologies available to measure activity within the brain. A number of different sensor technologies are available that provide either direct or indirect indices of the brain’s activity. These include measures taken from the brain such as electroencephalographic (EEG) activity, functional near-infrared imaging, transcranial Doppler sonography, magnetoencephalography, functional magnetic resonance imaging, and indirect physiological measures of brain activity related to sympathetic/parasympathetic nervous system activity such as pupillometry, heart rate, heart rate variability, and electrodermal activity including skin conductance and galvanic skin response. The advantages of each of these methods can be assessed along three criteria including spatial resolution, temporal resolution, and ease of use (Parasuraman and Wilson 2008). Of these sensor technologies, EEG has been the most widely used for
CONTENTS
8.1 Overview of Topic .............................................................................................................. 183 8.2 Introduction to EEG Methods .......................................................................................... 184
8.2.1 What EEG Is and Is Not ........................................................................................ 185 8.2.2 Recording Sites and the International 10/20 System ........................................ 185 8.2.3 Spectral Analysis ................................................................................................... 186 8.2.4 Event-Related Potentials ....................................................................................... 186 8.2.5 Minimal versus Dense-Array EEG ...................................................................... 187
8.3 EEG and Workload ............................................................................................................ 187 8.4 Working Memory and Learner Engagement ................................................................. 189 8.5 EEG, Workload, and Engagement ................................................................................... 191 8.6 Theoretical Frameworks for Adaptive Interfaces .......................................................... 192 8.7 Classification Strategies .................................................................................................... 193 8.8 Prestimulus Alpha ............................................................................................................. 194 8.9 Challenges ........................................................................................................................... 194
8.9.1 Individual Differences .......................................................................................... 195 8.9.2 Artifact..................................................................................................................... 195
8.10 Alternative Applications ................................................................................................... 195 8.11 The Road Ahead: Research Needs .................................................................................. 196 References ..................................................................................................................................... 197
real-time assessment because of its fine-grained temporal resolution and ease of use. For this reason, the present chapter will focus primarily on advances made with respect to the use of EEG metrics for assessing workload and engagement.
