基于脑电信号的认知负荷测量

Tasmi Tamanna, M. Parvez
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引用次数: 1

摘要

认知负荷的测量对视障人士在陌生室内环境中导航的智能导航系统设计具有重要的指导意义。脑电图(EEG)可以提供由脑节律性活动变化所指示的感知过程的神经生理指标。为了支持脑电信号的认知负荷测量,考虑了成熟的信号处理和机器学习方法的各种因素,量化了vip在陌生室内环境中导航任务的复杂性。本章介绍了基于脑电图信号分析的认知负荷测量方法的相关文献、背景、范围、特点和机器学习技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive Load Measurement Based on EEG Signals
Measurement of cognitive load should be advantageous in designing an intelligent navigation system for the visually impaired people (VIPs) when navigating unfamiliar indoor environments. Electroencephalogram (EEG) can offer neurophysiological indicators of 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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