# EEG-Based Measurement for Detecting Distraction in Coal Mine Workers
## 1 Introduction  
Coal mining has garnered widespread attention due to its high accident rates. This persistent issue remains unresolved, even amid frequent and severe incidents [1]. Research shows that over 90% of these accidents are attributable to unsafe human behaviors [2]. With advancements in safety management and technological innovations, the focus on the pivotal role of coal miners in mitigating unsafe behaviors has intensified. Miners' unsafe behaviors are influenced by the complex interplay between human factors, machinery, and the environment [3]. Critical individual factors, such as fatigue, stress, and decreased alertness, significantly contribute to these unsafe behaviors [4, 5]. These adverse physiological and psychological states impair miners' ability to filter irrelevant information, thereby affecting their attention to crucial details, leading to distractions [6]. Workplace distraction refers to the shift of attention from a primary task to irrelevant stimuli during task execution [7]. This shift can be induced by external factors, such asnoise or changes in lighting, or internal factors, including fatigue and emotional states [8,9]. While distraction is a common issue across various industries, coal miners face distinct challenges. Underground coal mines are characterized by confined spaces with low visibility and constant, high-intensity noise generated by equipment, such as ventilation fans and conveyor belts. In addition to these auditory distractions, miners are also exposed to a range of environmental stressors, including airborne dust particles and toxic gases. According to the _Coal Mine Safety Regulations_ issued by the State Administration of Work Safety [10], coal miners must meticulously follow operational instructions, monitor instrument readings and machinery conditions, and respond rapidly to anomalies. For example, miners are required to check gas concentrations during work. If the methane concentration in the mine tunnel reaches 2%, all work must stop, machinery must be shut down, and the situation must be reported to the control room. From a Gestalt psychology perspective, attention and other cognitive functions in such environments may be influenced by a \"cooperative\" effect, where the combination of environmental and task-specific demands significantly heightens the risk and consequences of distraction in coal mining, underscoring the critical need for sustained attention in this setting. Behavioral analyses of 200 coal mine incidents have identified distraction and negligence as significant contributors to unsafe behaviors, which in turn are key factors in coal mine accidents [11]. Mining tasks, typically involving low cognitive load and continuous similar work, often induce fatigue and reduced attention, increasing the risk of operational errors. This is evidenced by prolonged reaction times, higher error rates, and physiological indicators, such as elevated heart rates and increased blinking frequency [12]. Additionally, the high noise levels typical of coal mine environments can impair miners' attention and response capabilities [13]. This auditory interference may prevent miners from perceiving critical warning sounds, such as trolley car bells, equipment alarms, or water seepage signals during emergencies, thereby elevating accident risk [14]. Distraction also contributes to the neglect of safety protocols and the adoption of risky behaviors, often culminating in severe incidents [15]. These findings underscore the urgent need to study the effects of distraction on coal miners to improve safety performance and mitigate accident risks. Psychologists have traditionally relied on self-reports and task performance to understand and predict human behavior [16,17]. However, these metrics are limited predictors of behavior in specific contexts. Electroencephalography (EEG) offers a complementary approach by revealing the underlying connections between human behavior and brain activity.