Authors:

Hermes Heng-yu Fu

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About Paper:

Situation awareness (SA) and communication effectiveness are two essential nontechnical skills (NTS) for healthcare providers. SA plays a vital role in enabling nurses to detect early signs of patient deterioration, while effective communication supports strong team performance. However, current assessments of NTS primarily rely on subjective evaluations conducted after the surgery, which limit their accuracy and timeliness. This research proposes objective and real-time strategies to assess and predict NTS using physiological and communication data. These methods allow continuous monitoring, enabling the detection of changes in NTS and providing timely support to maintain safe and efficient clinical operations. Building on previous studies that used physiological signals to predict cognitive load in surgical settings, this study introduces two real-time assessment systems. The first system analyzes heart rate variability and eye tracking data from wearable sensors to identify patterns linked to SA. These patterns can be used to estimate SA levels and offer immediate support when low SA is detected. The second system focuses on team communication, developing a machine learning model to predict team progress from sliding windows of sentences. Together, these systems support objective and real-time evaluation of NTS, offering valuable feedback to enhance individual and team performance in healthcare environments. Keywords: Real-Time Analysis; Non-Technical Skills; Situation Awareness; Team Communication; Psychophysiological Assessment

Source:

Purdue University / 2025

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Co-authors:

Hermes Heng-yu Fu