Title :
Incorporating GOMS analysis into the design of an EEG data visual analysis tool
Author :
Hua Guo ; Tran, Duke ; Laidlaw, David H.
Author_Institution :
Dept. of Comput. Sci., Brown Univ., Providence, RI, USA
Abstract :
In this paper, we present a case study where we incorporate GOMS (Goals, Operators, Methods, and Selectors) [2] task analysis into the design process of a visual analysis tool. We performed GOMS analysis on an Electroencephalography (EEG) analyst´s current data analysis strategy to identify important user tasks and unnecessary user actions in his current workflow. We then designed an EEG data visual analysis tool based on the GOMS analysis result. Evaluation results show that the tool we have developed, EEGVis, allows the user to analyze EEG data with reduced subjective cognitive load, faster speed and increased confidence in the analysis quality. The positive evaluation results suggest that our design process demonstrates an effective application of GOMS analysis to discover opportunities for designing better tools to support the user´s visual analysis process.
Keywords :
cognition; data analysis; data visualisation; electroencephalography; medical signal processing; EEG data visual analysis tool design; GOMS analysis; analysis quality; data analysis strategy; electroencephalography analyst; goal-operator-method-selector task analysis; subjective cognitive load; Brain modeling; Data visualization; Electrodes; Electroencephalography; Mathematical model; Standards; Visualization; Human factors; user-centered design;
Conference_Titel :
Visual Analytics Science and Technology (VAST), 2012 IEEE Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4673-4752-5
DOI :
10.1109/VAST.2012.6400542