The prevalence of dry eye syndrome (DES) has rapidly increased in recent years, negatively affecting the eye health of many office workers worldwide. Although low eye blink rate (EBR) has been pointed out as one of the main risk factors for DES, it is difficult for office workers to continuously monitor and increase their own involuntary blinking, especially when they are focused on the primary work task. Thus, as an effort to help office workers correct their low EBR, the current study developed a real-time EBR level classification system utilizing sitting postural behavior data. A total of twenty participants performed typical computer tasks on a sensor-embedded chair. The participants’ eye blinking and postural behavior data were collected to develop the EBR level classification system with a random forest algorithm. After evaluating the system performance, the relationships between EBR and postural behaviors were empirically examined to help understand how the system worked for EBR level classification. As a result, the developed system showed high classification performance overall; and compared with high EBR condition, low EBR condition was related to less overall postural variability and greater extent of forward bending posture. The real-time EBR level classification system is expected to contribute to preventing/relieving DES and thereby enhancing the eye health of office workers.

The accident rate due to human errors in industrial fields has been consistently high over the past few decades, and noise has been emerging as one of the main causes of human errors. In recent years, auditory pre-stimulation has been considered as a means of preventing human errors by improving workers’ cognitive task performance. However, most previous studies demonstrated the effectiveness of the auditory pre-stimulation in a quiet environment. Accordingly, studies on the effects of pre-stimulation in a noisy environment are still lacking. Therefore, this study aimed to empirically investigate: (1) the effects of noisy environments on the performances of cognitive tasks related to different functions of working memory and (2) the effects of auditory pre-stimulation on the performances of cognitive tasks in a field-noise environment. To accomplish these research objectives, two major experiments were conducted. In the first experiment, a total of 24 participants performed each of three basic short-term/working memory (STM/WM) tasks under two different experimental conditions (quiet-noise environment and field-noise environment) depending on the presence or absence of field noise. In the second experiment, the participants performed each of the three basic STM/WM tasks in a field-noise environment after they were provided with one of four different auditory pre-stimulations (quiet noise, white noise, field noise, and mixed (white and field) noise). The three STM/WM tasks were the Corsi block-tapping, Digit span, and 3-back tasks, corresponding to the visuospatial sketchpad, the phonological loop, and the central executive of WM, respectively. The major findings were that: (1) the field-noise environment did not affect the scores of the Corsi block-tapping and 3-back tasks, significantly affecting only the Digit span task score (decreased by 15.2%, p < 0.01); and (2) the Digit span task performance in the field-noise environment was improved by 17.9% (p < 0.05) when mixed noise was provided as a type of auditory pre-stimulation. These findings may be useful for the work-space designs that prevent/minimize human errors and industrial accidents by improving the cognitive task performance of workers in field-noise environments.

Objective: This study aimed to investigate the effects of different monitoring systems on human performance and user experience in safety-critical diagnostic and operational tasks, and examine how these effects are moderated by task-related and human-related factors. Background: Monitoring systems are increasingly adopted in safety-critical domains to enhance performance and safety. However, these systems may present both benefits and potential drawbacks, and comprehensive understanding of their multifaceted effects remains limited. Method: 32 participants performed diagnostic and operational tasks using a nuclear power plant simulator. A mixed experimental design examined three independent variables: monitoring system (human monitoring, camera monitoring, no monitoring as a baseline), task type (accident, non-accident), and participant group (nuclear-based, engineering/science-based). Dependent variables included human performance metrics (accuracy, task completion time) and user experience (stress, workload, privacy concerns, trust, and technology acceptance). Results: Human monitoring was associated with significantly higher accuracy compared to no monitoring, but also increased stress and workload. Camera monitoring generally exhibited intermediate values between no monitoring and human monitoring, while eliciting the highest privacy concerns among all conditions. Significant interaction effects emerged between monitoring systems, participant groups, and task types on stress, trust, and technology acceptance. Conclusion: Monitoring conditions exhibited double-edged effects: enhancing human performance while simultaneously increasing the perceived burden. These effects were moderated by task characteristics and users’ background. Application: These findings can inform the human-centered design of monitoring systems and development of regulatory guidelines in safety-critical domains, emphasizing the need to balance the performance benefits with stress-related human factors issues.