Approximate entropy: a new evaluation approach of mental workload under multitask conditions

Lei Yao; Xiaoling Li; Wei Wang; Yuanzhe Dong; Ying Jiang

doi:10.1117/12.2064063

16 April 2014 Approximate entropy: a new evaluation approach of mental workload under multitask conditions

Lei Yao, Xiaoling Li, Wei Wang, Yuanzhe Dong, Ying Jiang

Proceedings Volume 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014); 91590C (2014) https://doi.org/10.1117/12.2064063
Event: Sixth International Conference on Digital Image Processing, 2014, Athens, Greece

Abstract

There are numerous instruments and an abundance of complex information in the traditional cockpit display-control system, and pilots require a long time to familiarize themselves with the cockpit interface. This can cause accidents when they cope with emergency events, suggesting that it is necessary to evaluate pilot cognitive workload. In order to establish a simplified method to evaluate cognitive workload under a multitask condition. We designed a series of experiments involving different instrument panels and collected electroencephalograms (EEG) from 10 healthy volunteers. The data were classified and analyzed with an approximate entropy (ApEn) signal processing. ApEn increased with increasing experiment difficulty, suggesting that it can be used to evaluate cognitive workload. Our results demonstrate that ApEn can be used as an evaluation criteria of cognitive workload and has good specificity and sensitivity. Moreover, we determined an empirical formula to assess the cognitive workload interval, which can simplify cognitive workload evaluation under multitask conditions.

Citation Download Citation

Lei Yao, Xiaoling Li, Wei Wang, Yuanzhe Dong, and Ying Jiang "Approximate entropy: a new evaluation approach of mental workload under multitask conditions", Proc. SPIE 9159, Sixth International Conference on Digital Image Processing (ICDIP 2014), 91590C (16 April 2014); https://doi.org/10.1117/12.2064063

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available