Enhanced cognitive workload evaluation in 3D immersive environments with TOPSIS model

Research puts forward perception-based cognitive workload evaluation methods to help VR developers and users measuring their when playing with a application. Approaches measure based on biosensors have progressed significantly, while subjective still rely standard questionnaires such as the NASA-TLX table, Subjective Workload Assessment Technique Modified Cooper Harper scale. The pre-defined questions enable operators carry out experiments analyse data more easily than biofeedback. However, process can bias results because of unperceived internal changes unknown factors among users. It is therefore necessary method handle this uncertainty. We propose use for Order Performance by Similarity Ideal Solution (TOPSIS) model table overall user instead using classical weighted sum method. To show advantage TOPSIS approach, we performed experiment validate approach its application VR, considering including platform scenario density. Three different weighting methods, fuzzy Analytic Hierarchy Process (AHP) from logic, pairwise comparison uniform method, were tested see applicability model. consistent those other methods; significant reduction in coefficient variation (CV) was observed scores, indicating an enhanced precision Our work has potential designers experimenters compare conditions optimize settings.