Fuzzy-TLX : using fuzzy integrals for evaluating human mental workload with NASA-Task Load indeX in laboratory and field studies

Objectives: In mental workload assessment 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 NASA-TLX subscales, in order to replace the standard pair-wise weighting technique (PWT).
Methods: Two empirical studies are reported. (1) In a laboratory experiment, age and task-related variables were investigated in 53 male volunteers; (2) In a field study, task and job-related variables were studied on aircrews during 48 commercial flights.
Results: 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; iv) subjective and objective measures can be used for the fuzzy aggregation of NASA-TLX subscales.