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Objective This study used electroencephalography to explore the behavioral and electrophysiological effects of task interruption on performance. Background Task interruption is known to harm work performance, especially on working memory-related tasks. However, most studies pay little attention to cognitive processes by exploring brain activity and ignore the cumulative effect of sequential interruptions. Method Thirty-four healthy participants performed a spatial 2-back in three conditions: (1) interruptions with simple math questions, (2) suspensions with prolonged fixation cross, and (3) a pure 2-back. The measured outcomes comprise performance data, ERP amplitudes, EEG power, and subjective workload. Results Work performance decreased in the resumption trials, and cumulative interruptions had a more destructive effect on performance. EEG results showed that the P2 and P3 amplitudes induced by the 2-back task significantly increased after interruptions; theta and alpha power increased after interruptions. The P3 amplitude and alpha power induced by interruptions were significantly higher than that induced by suspensions. Conclusion Behavioral data revealed the disruptive effect of interruptions on postinterruption performance and the cumulative effect of interruptions on accuracy. Changes in ERP amplitudes and EEG power indicate the mechanisms of attention reallocation and working memory during interruptions. Larger P3 amplitudes and alpha power after interruptions than after suspensions suggested the inhibition of irrelevant information. These results may support the memory for goals model and improve the understanding of the effects of interruption on working memory. Application Focusing upon the mechanisms at play during the interruption process can support interruption management to ensure work safety and efficiency.

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A tablet computer’s surface temperature can reach levels that can lead to user discomfort, especially in a warm environment. The ambient environments in which tablet computers are used can also vary. To understand how users perceive the heat from tablet computers, a laboratory study was conducted with controlled surface temperatures and ambient temperatures. A positive relationship between surface temperature and participants’ thermal sensation scores was found. Participants’ thermal responses to the surface heat of a simulated tablet were also moderated by the indoor temperature. Higher surface temperature (44°C) was rated less warm in cool environment than hot environment, while lower surface temperatures (34-38°C) were rated warmer in cool than hot environment. The thermal responses corresponding to the tablet surface temperatures and ambient temperatures will be helpful for setting future tablet computer heat dissipation design limits.

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.

SummaryA measure of team task complexity for emergency procedures in fully automatic metro is proposed using a Euclidean norm based on two factors: internal complexity of network nodes Nodecom − inside and external complexity of network nodes Nodecom − outside. The development of the operation complexity measure followed four steps. First, team task complexity network for emergency procedures was constructed. Second, the task complexity (TC) method used as complexity measure of individual was adopted to measure the internal complexity of network nodes. Then, the external complexity of network nodes was measured by structure entropy. Finally, the team task complexity values for emergency procedures were determined by the Euclidean norm of the two factors. To verify the validity of this team task complexity measure, a one‐factor experiment was designed to test the proposed model. Thirteen team subjects participated in the experiment and performed 5 typical emergency scenes. Both objective indexes (TeamTIME) and subjective indexes (TeamWORKLOAD and TeamSUBCOMPLEXITY) were used in the experiment. The data analysis showed that the TeamTIME, TeamWORKLOAD, and TeamSUBCOMPLEXITY could be predicted well from the team task complexity value. The proposed team task complexity measure can be used for evaluation of emergency procedures design in fully automatic metro.