Human factors usability testing applies what is known about human behavior to the design of UI design systems, including our abilities and limitations. There has been limited application of advanced human factors knowledge and methods to usability testing, although it is steadily increasing.
The goal is to use neuroscience-based human factors research to improve the observational methodologies of usability testing. These observational methodologies includes task-based observation, having participants think out loud to describe their thought processes, and interviews afterwards with moderators. Combining these methods with neuroscience-based systems that capture data and information from users in an objective manner can lead to more thorough testing results.
Some neuroscience-based testing methods include Learning Transfer Analysis, which determines if changes to an existing user interface design will have a negative impact on previous users of the system. Usability Heuristics can provide nuanced data on any errors and confusion that may not be captured or expressed through observational testing. Also, Cognitive Workload Analysis can determine the cognitive workload level experienced when users interact with devices. This is especially beneficial in connection to medical devices, as the results are grouped by specific patient demographics.
With insight into everything from determining users’ emotional responses to device designs to advanced eye tracking that details the visual attention differences of users between design concepts, neuroscience-based testing methods are a long-overdue propel forward in usability testing.