Analysis of Head Micromovements and Body Posture for Vigilance Decrement Assessment

Rossi, Dario; Aricò, Pietro; Di Flumeri, Gianluca; Ronca, Vincenzo; Giorgi, Andrea; Vozzi, Alessia; Capotorto, Rossella; Inguscio, Bianca M. S.; Cartocci, Giulia; Babiloni, Fabio; Borghini, Gianluca · 2024 · DOAJ

DOI: 10.3390/app14051810

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Summary

This study addresses the challenge of reliably assessing vigilance decrements in real-time, particularly in operational environments where attention lapses can have severe consequences. While traditional methods rely on performance metrics (e.g., reaction times) and self-reports, these approaches are often insufficient for continuous, objective monitoring. The authors propose that head micromovements and body posture changes, measured via inertial measurement units (IMUs), serve as viable proxies for tracking vigilance degradation. This approach leverages the widespread availability of IMUs in consumer electronics, offering a low-cost, non-invasive alternative to complex neurophysiological tools like EEG. The experimental design involved 12 healthy participants (balanced gender, mean age 27) who performed two 10-minute Psychomotor Vigilance Tasks (PVT). The PVT required participants to respond as quickly as possible to visual stimuli appearing at random intervals, a protocol known to induce vigilance decrement over time. During the tasks, head and chest movements were recorded using two Shimmer GSR3+ IMU devices sampling at 100 Hz. Data processing involved fusing accelerometer and gyroscope signals to calculate linear acceleration modulus. The authors derived two key metrics for each minute of the task: the median value of acceleration, representing the intensity of movement, and the median absolute deviation (MAD), representing the variability of movement. These metrics were analyzed to determine their correlation with vigilance states, using a baseline resting period for comparison. The results demonstrated that head micromovements and body posture variations are significantly associated with vigilance levels. Specifically, the analysis revealed that these kinematic markers could effectively discriminate between conditions of high and low vigilance. The study confirmed that as vigilance decreased during the prolonged PVT, measurable changes occurred in the intensity and variability of head and body movements. This indicates that subtle motor behaviors, often overlooked, reflect the underlying cognitive state of the operator. The significance of this work lies in its validation of IMU-based kinematic analysis as a practical tool for vigilance monitoring. By establishing a link between vestibular/motor outputs and cognitive alertness, the study provides a foundation for developing real-time vigilance indices that do not require specialized personnel or intrusive sensors. This has broad implications for safety-critical fields such as aviation, driving, and industrial automation, where detecting early signs of attention deficit is crucial for preventing accidents. The findings support the integration of wearable sensors into human-machine interaction systems to enhance situational awareness and operator safety.

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Topics

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• vigilance
• sustained attention vigilance
• drowsiness
• microsleep