摘要
Obtaining mental workload levels during task performance is a difficult procedure. The workload level experienced by an operator can affect task performance. This effect can be caused by either excessive or reduced mental workload. Thus, estimating workload levels can help isolate sources that affect performance. Several techniques can be used to measure operator workload. Psychophysiological measurements using electroencephalograms (EEGs) have been used with much success. However, EEG machines are not the most portable, practical, or ubiquitous devices, which constrains their usefulness in experiments. Obtaining physiological mental workload data is a nontrivial task, and there has been a large amount of work on designing lightweight and portable workload measuring devices (Kramer, 1991). Workload assessment techniques should possess the following properties: sensitivity, diagnostic capabilities, selectivity, low intrusiveness, reliability, and ease of implementation (Eggemeier, 1988). The NASA Task Load Index (TLX) has been shown to meet these criteria (Rubio, Diaz, Martin, & Puente, 2004). It is a subjective workload assessment technique that relies on a multidimensional construct to derive an overall workload score based on a weighted average of ratings on six subscales: mental demand, physical demand, temporal demand, performance, effort, and frustration level. The use of these six subscales to compute an overall workload score has been found to reduce variability among subjects, relative to a unidimensional workload rating, while providing diagnostic information about workload sources (Hart & Staveland, 1988). Specific sources of mental workload imposed by different tasks are an important determinant of workload experiences. Three of the subscales relate to the demands imposed on the subject (mental, physical, and temporal demand), whereas the other subscales focus on the interaction of the subject with the task (performance, effort, and frustration level). Descriptions of the six subscales are