Abstract
For an establishment of a skill evaluation method for human support systems, development of an estimating equation of the machine operational skill is presented. Factors of the eye movement such as frequency, velocity, and moving distance of saccade were computed using the developed eye gaze measurement system, and the eye movement features were determined from these factors. The estimating equation was derived through an outlier test (to eliminate nonstandard data) and a principal component analysis (to find dominant components). Using a cooperative carrying task (cc-task) simulator, the eye movement and operational data of the machine operators were recorded, and effectiveness of the derived estimating equation was investigated. As a result, it was confirmed that the estimating equation was effective strongly against actual simple skill levels (r=0.56–0.84). In addition, effects of internal condition such as fatigue and stress on the estimating equation were analyzed. Using heart rate (HR) and coefficient of variation of R-R interval (Cvrri). Correlation analysis between these biosignal indexes and the estimating equation of operational skill found that the equation reflected effects of stress and fatigue, although the equation could estimate the skill level adequately.
Highlights
With the development of science and technology in several decades, we have had more opportunities to operate various types of machines in our daily life
After computing Li for six operators using (6) from raw data of factors of eye movement, correlation analysis found the strong correlation between Li and the simple skill level which is the number of trial i (r = −0.84 ∼ −0.56)
After extracting valid data which satisfy statistical normality, the standard estimating equation of the operational skill level based on the eye-movement data was derived
Summary
With the development of science and technology in several decades, we have had more opportunities to operate various types of machines in our daily life. Utilizing this property, many studies evaluating such internal status from the measurement of eye motion are reported [15, 16]. In this paper, the following three steps which were required to establish the skill evaluation method for HAM were treated. Derivation of an equation to estimate a skill level of a machine operation using the measurement of eye motion. Using the measured biosignal, adequacies of methods to evaluate fatigue and stress are verified (for Step 2).
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