@article{ref1,
title="Fuzzy-TLX: using fuzzy integrals for evaluating human mental workload with NASA-Task Load indeX in laboratory and field studies",
journal="Ergonomics",
year="2013",
author="Mouzé-Amady, Marc and Raufaste, Eric and Prade, Henri and Meyer, Jean-Pierre",
volume="56",
number="5",
pages="752-763",
abstract="The aim of this study was to assess mental workload in which various load sources must be integrated to derive reliable workload estimates. We report a new algorithm for computing weights from qualitative fuzzy integrals and apply it to the National Aeronautics and Space Administration -Task Load indeX (NASA-TLX) subscales in order to replace the standard pair-wise weighting technique (PWT). In this paper, two empirical studies were reported: (1) In a laboratory experiment, age- and task-related variables were investigated in 53 male volunteers and (2) In a field study, task- and job-related variables were studied on aircrews during 48 commercial flights. The results found in this study were as follows: (i) in the experimental setting, fuzzy estimates were highly correlated with classical (using PWT) estimates; (ii) in real work conditions, replacing PWT by automated fuzzy treatments simplified the NASA-TLX completion; (iii) the algorithm for computing fuzzy estimates provides a new classification procedure sensitive to various variables of work environments and (iv) subjective and objective measures can be used for the fuzzy aggregation of NASA-TLX subscales. Practitioner Summary: NASA-TLX, a classical tool for mental workload assessment, is based on a weighted sum of ratings from six subscales. A new algorithm, which impacts on input data collection and computes weights and indexes from qualitative fuzzy integrals, is evaluated through laboratory and field studies. Pros and cons are discussed.<p /> <p>Language: en</p>",
language="en",
issn="0014-0139",
doi="10.1080/00140139.2013.776702",
url="http://dx.doi.org/10.1080/00140139.2013.776702"
}