Enhancing human-system synergy through neuro-physiological computing

As automated and intelligent systems are increasingly integrated into work environments, they hold immense potential to enhance productivity and decision-making. However, these systems often fail to account for the nuanced and dynamic nature of human behavior, resulting in challenges such as misaligned human-machine collaboration and human-machine conflicts. Without the ability to sense and adapt to users' intentions and cognitive and emotional states, these systems risk undermining performance, safety, and well-being. To ensure effective human-system interaction, it is crucial for these systems to become more aware of and responsive to the humans they are designed to support. This talk explores how neurophysiological computing technologies can bridge this gap by enabling real-time human state sensing. By leveraging tools such as electrocardiography (ECG), electrodermal activity (EDA), eye tracking, electroencephalography (EEG), and functional near-infrared spectroscopy (fNIRS), we can capture rich physiological and behavioral data to infer user states such as attention, workload, intention, and even team dynamics. These insights empower intelligent systems to dynamically adapt to users' needs, potentially reducing errors, resolving conflicts, and fostering better collaboration. This talk will showcase advancements in neuro-physiological computing for recognizing user intention, sensory conflicts, and teamwork states through case studies and applications. Highlights include an EEG-based system that detects visual-vestibular conflicts to assist pilots with spatial disorientation, and an fNIRS-based solution that monitors neural synchrony in teamwork for adaptive training in aviation and healthcare. These examples demonstrate how integrating human sensing technologies into intelligent systems can enhance performance, safety, and well-being in an automated world.