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Wireless Communications and Mobile Computing
Volume 2018 (2018), Article ID 8971206, 9 pages
Research Article

Cognitive Load Assessment from EEG and Peripheral Biosignals for the Design of Visually Impaired Mobility Aids

1Audio Communication Group, Technical University of Berlin, Berlin, Germany
2Data Science Lab, Institute for Scientific Interchange (ISI Foundation), Turin, Italy

Correspondence should be addressed to Charalampos Saitis

Received 23 September 2017; Revised 10 January 2018; Accepted 30 January 2018; Published 28 February 2018

Academic Editor: Tao Gu

Copyright © 2018 Charalampos Saitis et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Reliable detection of cognitive load would benefit the design of intelligent assistive navigation aids for the visually impaired (VIP). Ten participants with various degrees of sight loss navigated in unfamiliar indoor and outdoor environments, while their electroencephalogram (EEG) and electrodermal activity (EDA) signals were being recorded. In this study, the cognitive load of the tasks was assessed in real time based on a modification of the well-established event-related (de)synchronization (ERD/ERS) index. We present an in-depth analysis of the environments that mostly challenge people from certain categories of sight loss and we present an automatic classification of the perceived difficulty in each time instance, inferred from their biosignals. Given the limited size of our sample, our findings suggest that there are significant differences across the environments for the various categories of sight loss. Moreover, we exploit cross-modal relations predicting the cognitive load in real time inferring on features extracted from the EDA. Such possibility paves the way for the design on less invasive, wearable assistive devices that take into consideration the well-being of the VIP.