Pilot's visual attention allocation modeling under fatigue

Distracted worker: Using pupil size and blink rate to detect cognitive load during manufacturing tasks

This study sets out to extend the use of blink rate and pupil size to the assessment of cognitive load of completing common automotive manufacturing tasks. Nonoptimal cognitive load is detrimental to safety. Existing occupational ergonomics approaches come short of measuring dynamic changes in cognitive load during complex assembling tasks. Cognitive demand was manipulated by having participants complete two versions of the n-back task (easy, hard). Two durations of the physical task were also considered (short, long). Pupil size and blink rate increased under greater cognitive task demand. High cognitive load also resulted in longer task completion times, and higher ratings of mental and temporal demand, and effort. This exploratory study offers relevant insights on the use of ocular metrics for cognitive load assessment in occupational ergonomics. While the existing eye-tracking technology may yet limit their adoption in the field, they offer advantages over the more popular expert-based and self-reported techniques in measuring changes in cognitive load during dynamic tasks.

Surgeons Maintain Better Focus Working 12-Hour Shifts Compared to 24-Hour Calls

BACKGROUND

In this quality improvement project, we analyzed surgeon focus and attention utilizing a visual tracking device. We hypothesized that surgeons maintained better focus working 12-hour shifts compared to 24-hour calls.

MATERIALS AND METHODS

A prospective, quality improvement project was performed on surgery residents, medical students, and attending physicians working at a busy, tertiary referral, safety-net hospital with Level 1 trauma and burn centers. A visual tracking system was used to measure visual attention before and after a 12-hour, in-house shift and a 24-hour, surgical in-house call. A pupil tracker was utilized to measure attention impairment. Individual performance was rated on a scale of 0 to 6: Severely Impaired- 0; Impaired- 1; Low Average- 2; Average- 3; Above Average- 4; High Average- 5; Superior- 6. Data were analyzed for homogeneity. The Wilcoxon Ranked Sum was used to assess for statistically significant differences between focus scores in the same group of individuals before and after shifts and/or calls. The Mann-Whitney U test was used to compare differences in focus between 12 and 24 hour in-house shifts and/or calls.

RESULTS

A total of 21 surgeons provided a total of 61 visual tracking tests for analysis. Results were found to be nonhomogeneous. The project population was 46% men with a median age of 31 years IQR (28-33). General surgery residents accounted for 48 tests, medical students for 2, and attending surgeons for 11. Average hours of self-reported sleep before the shift/call was 6 (IQR; 6-7). There was almost no overall change in focus in individuals before and after a 12-hour, in-house shift -0.06 (SD 1.9), while after a 24- hour, in-house call, focus decreased by almost 2 full grades -1.8 (SD 1.6) (p = 0.013). There was no statistically significant difference in focus found between 12-hour day shift and 12-hour night shift.

CONCLUSIONS

Twelve-hour shifts appear to preserve focus in surgeons better compared with 24- hour, in-house calls. More research is needed to establish the optimal time of surgeon focus maintenance and shift duration.

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

INTRODUCTION

Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices.

METHOD

This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.

Supervisors' Visual Attention Allocation Modeling Using Hybrid Entropy

With the improvement in automation technology, humans have now become supervisors of the complicated control systems that monitor the informative human–machine interface. Analyzing the visual attention allocation behaviors of supervisors is essential for the design and evaluation of the interface. Supervisors tend to pay attention to visual sections with information with more fuzziness, which makes themselves have a higher mental entropy. Supervisors tend to focus on the important information in the interface. In this paper, the fuzziness tendency is described by the probability of correct evaluation of the visual sections using hybrid entropy. The importance tendency is defined by the proposed value priority function. The function is based on the definition of the amount of information using the membership degrees of the importance. By combining these two cognitive tendencies, the informative top-down visual attention allocation mechanism was revealed, and the supervisors’ visual attention allocation model was built. The Building Automatic System (BAS) was used to monitor the environmental equipment in a subway, which is a typical informative human–machine interface. An experiment using the BAS simulator was conducted to verify the model. The results showed that the supervisor’s attention behavior was in good agreement with the proposed model. The effectiveness and comparison with the current models were also discussed. The proposed attention allocation model is effective and reasonable, which is promising for use in behavior analysis, cognitive optimization, and industrial design.

An acetaminophen icon helps reduce medication decision errors in an experimental setting

OBJECTIVES

To assess the effect of adding an acetaminophen ingredient icon to acetaminophen medication labels on consumer decision making about concomitant use of acetaminophen medications to avoid overdose, which is associated with liver injury.

DESIGN

Parallel-group randomized study.

SETTING

Consumer research facilities in Indianapolis, Baltimore, and Los Angeles.

PARTICIPANTS

A total of 517 adults (30% with limited health literacy) recruited at 3 consumer research sites.

INTERVENTION

Participants were randomized to a non-icon condition in which medications carried current labeling or an icon condition in which all acetaminophen medications were additionally marked with an icon.

MAIN OUTCOME MEASURES

Participants were presented with a medicine cabinet containing 12 diverse prescription and non-prescription medications, one-half containing acetaminophen, and made decisions about which medications were appropriate to take after an acetaminophen medication had already been taken. Outcome measures were errors in medication decisions and response time.

RESULTS

The icon reduced the odds of participants making medication-decision errors by 53% (CI 31%-68%), with effects evident across medication categories. The icon eliminated a trend for those with lower health literacy or less education to have a greater likelihood of making errors. The icon also reduced response times, indicating reduced cognitive load for decisions.

CONCLUSION

An icon can improve decision making regarding acetaminophen-containing medications, particularly among individuals with limited health literacy or education.