PhD Defense: Enhancing Usability Testing with Functional Near Infrared Spectroscopy
Usability researchers attempt to formalize and quantify the process whereby an interface is evaluated, and to measure precisely the degree to which an interface meets the goals of its intended audience. Although one can measure the accuracy with which users complete tasks and the time it takes to complete a task with an interface, measuring subjective factors such as workload, frustration, and enjoyment is more difficult. These factors are often “measured” by qualitatively observing participants or by administering subjective surveys to participants. These surveys can inadvertently elicit participant biases, as participants often attempt to please experiment investigators in their responses. Additionally, surveys are often administered after a task has been completed, lacking insight into the users’ changing experiences as they work with an interface.
This dissertation research addresses these evaluation challenges with respect to mental workload. I use a non-invasive brain sensing technique called functional near infrared spectroscopy (fNIRS) to record real time, objective measurements of users’ workload while working with user interfaces. The fNIRS device is comfortable, portable, and relatively robust to noise, making it very useful for use within the human-computer interaction (HCI) domain.
Using brain measurement to quantify the level of workload experienced by computer users is a difficult task because “workload” is actually an umbrella term. In practice, there is no single area of the brain that is activated when users experience workload. Indeed, when we compute mental arithmetic, compose a poem, or carry on a conversation with a friend, we are experiencing some form of workload. However, for each task that we take part in, we may use different (and often overlapping) cognitive resources. With these challenges in mind, this work provides two primary research contributions to the field of HCI:
1) I attempt to bridge the gap between HCI and cognition research by introducing techniques to non-invasively measure a range of low level cognitive workload states that have particular implications within the HCI realm.
2) I demonstrate ways that fNIRS brain measurement can be used to enhance usability testing by measuring a range of workload states objectively and in real time. This additional information can yield a more thorough, comprehensive understanding about an interface design than could be achieved with standard usability testing. Furthermore, I describe extensions of this work for adaptive system design.
While the fNIRS device holds great promise for non-invasive brain measurement in usability testing, there are several challenges that must be addressed in order to achieve this high level goal. In this dissertation, I discuss several interdisciplinary research challenges, stemming from the fields of cognitive psychology, biomedical engineering, machine learning, and HCI, that must be addressed in order to use fNIRS for the enhancement of usability testing. I present several experiments designed to overcome these research challenges. I then present an experiment that was conducted to use fNIRS in a realistic usability testing scenario. During this usability experiment I measured the mental load placed on the cognitive resources in users’ brains, and I made connections between users’ mental workload and the designs of four user interfaces. During the usability test, the fNIRS brain measurement yielded real-time, unbiased information about the users’ experience while working with the interface designs. This information enhanced the usability test, and it could not have been acquired with traditional usability metrics alone.