Galvanic Vestibular Stimulation Advancements for Spatial Disorientation Training.

INTRODUCTION: Spatial disorientation (SD) remains the leading contributor to Class A mishaps in the U.S. Navy, consistent with historical trends. Despite this, SD training for military aircrew is largely confined to the classroom and experiential training replicating SD illusions is limited and infrequent. Static flight simulators are most commonly used for training but offer no vestibular stimulation to the flight crew, omitting the source of vestibular-mediated SD.BACKGROUND: We first cover vestibular-mediated SD illusions which may be replicated through galvanic vestibular stimulation (GVS) in a static environment. GVS is a safe, reliable, low-cost avenue for providing vestibular sensory stimulation. We review the underlying mechanisms of GVS such as the excitement and inhibition of the afferent neurons innervating the vestibular system, particularly in the binaural bipolar electrode montage.APPLICATIONS: Two approaches for how GVS may be used to enhance SD training are examined. The first is a means for providing unreliable vestibular sensory perceptions to pilots, and the second details how GVS can be leveraged for replicating vestibular-mediated SD illusions.DISCUSSION: We recommend GVS be pursued as an enhancement to existing SD training. The ability to disorient aircrew in the safe training environment of a static flight simulator would allow for aircrew familiarization to SD, serving as an opportunity to practice life-saving checklist items to recover from SD. A repeatable training profile that could be worn by military aircrew in a static flight simulator may afford a low-cost training solution to the number one cause of fatalities in military aviation.Allred AR, Lippert AF, Wood SJ. Galvanic vestibular stimulation advancements for spatial disorientation training. Aerosp Med Hum Perform. 2024; 95(7):390-398.

A computational model of motion sickness dynamics during passive self-motion in the dark.

Predicting the time course of motion sickness symptoms enables the evaluation of provocative stimuli and the development of countermeasures for reducing symptom severity. In pursuit of this goal, we present an Observer-driven model of motion sickness for passive motions in the dark. Constructed in two stages, this model predicts motion sickness symptoms by bridging sensory conflict (i.e., differences between actual and expected sensory signals) arising from the Observer model of spatial orientation perception (stage 1) to Oman's model of motion sickness symptom dynamics (stage 2; presented in 1982 and 1990) through a proposed "Normalized Innovation Squared" statistic. The model outputs the expected temporal development of human motion sickness symptom magnitudes (mapped to the Misery Scale) at a population level, due to arbitrary, 6-degree-of-freedom, self-motion stimuli. We trained model parameters using individual subject responses collected during fore-aft translations and off-vertical axis of rotation motions. Improving on prior efforts, we only used datasets with experimental conditions congruent with the perceptual stage (i.e., adequately provided passive motions without visual cues) to inform the model. We assessed model performance by predicting an unseen validation dataset, producing a Q2 value of 0.91. Demonstrating this model's broad applicability, we formulate predictions for a host of stimuli, including translations, earth-vertical rotations, and altered gravity, and we provide our implementation for other users. Finally, to guide future research efforts, we suggest how to rigorously advance this model (e.g., incorporating visual cues, active motion, responses to motion of different frequency, etc.).

An Augmented Reality Hand-Eye Sensorimotor Impairment Assessment for Spaceflight Operations.

INTRODUCTION: Following a transition from microgravity to a gravity-rich environment (e.g., Earth, Moon, or Mars), astronauts experience sensorimotor impairment, primarily from a reinterpretation of vestibular cues, which can impact their ability to perform mission-critical tasks. To enable future exploration-class missions, the development of lightweight, space-conscious assessments for astronauts transitioning between gravity environments without expert assistance is needed.METHODS: We examined differences in performance during a two-dimensional (2D) hand-eye multidirectional tapping task, implemented in augmented reality in subjects (N = 20) with and without the presence of a vestibular-dominated sensorimotor impairment paradigm: the binaural bipolar application of a pseudorandom galvanic vestibular stimulation (GVS) signal. Metrics associated with both the impairment paradigm and task performance were assessed.RESULTS: Medial-lateral sway during balance on an anterior-posterior sway-referenced platform with eyes closed was most affected by GVS (effect size: 1.2), in addition to anterior-posterior sway (effect size: 0.63) and the vestibular index (effect size: 0.65). During the augmented reality task, an increase in time to completion (effect size: 0.63), number of misses (effect size: 0.52), and head linear accelerations (effect size: 0.30) were found in the presence of the selected GVS waveform.DISCUSSION: Findings indicate that this multidirectional tapping task may detect emergent vestibular-dominated impairment (near landing day performance) in astronauts. Decrements in speed and accuracy indicate this impairment may hinder crews' ability to acquire known target locations while in a static standing posture. The ability to track these decrements can support mission operations decisions.Allred AR, Weiss H, Clark TK, Stirling L. An augmented reality hand-eye sensorimotor impairment assessment for spaceflight operations. Aerosp Med Hum Perform. 2024; 95(2):69-78.

A computational model of motion sickness dynamics during passive self-motion in the dark.

Predicting the time course of motion sickness symptoms enables the evaluation of provocative stimuli and the development of countermeasures for reducing symptom severity. In pursuit of this goal, we present an observer-driven model of motion sickness for passive motions in the dark. Constructed in two stages, this model predicts motion sickness symptoms by bridging sensory conflict (i.e., differences between actual and expected sensory signals) arising from the observer model of spatial orientation perception (stage 1) to Oman's model of motion sickness symptom dynamics (stage 2; presented in 1982 and 1990) through a proposed "Normalized innovation squared" statistic. The model outputs the expected temporal development of human motion sickness symptom magnitudes (mapped to the Misery Scale) at a population level, due to arbitrary, 6-degree-of-freedom, self-motion stimuli. We trained model parameters using individual subject responses collected during fore-aft translations and off-vertical axis of rotation motions. Improving on prior efforts, we only used datasets with experimental conditions congruent with the perceptual stage (i.e., adequately provided passive motions without visual cues) to inform the model. We assessed model performance by predicting an unseen validation dataset, producing a Q2 value of 0.86. Demonstrating this model's broad applicability, we formulate predictions for a host of stimuli, including translations, earth-vertical rotations, and altered gravity, and we provide our implementation for other users. Finally, to guide future research efforts, we suggest how to rigorously advance this model (e.g., incorporating visual cues, active motion, responses to motion of different frequency, etc.).

Modeling orientation perception adaptation to altered gravity environments with memory of past sensorimotor states.

Transitioning between gravitational environments results in a central reinterpretation of sensory information, producing an adapted sensorimotor state suitable for motor actions and perceptions in the new environment. Critically, this central adaptation is not instantaneous, and complete adaptation may require weeks of prolonged exposure to novel environments. To mitigate risks associated with the lagging time course of adaptation (e.g., spatial orientation misperceptions, alterations in locomotor and postural control, and motion sickness), it is critical that we better understand sensorimotor states during adaptation. Recently, efforts have emerged to model human perception of orientation and self-motion during sensorimotor adaptation to new gravity stimuli. While these nascent computational frameworks are well suited for modeling exposure to novel gravitational stimuli, they have yet to distinguish how the central nervous system (CNS) reinterprets sensory information from familiar environmental stimuli (i.e., readaptation). Here, we present a theoretical framework and resulting computational model of vestibular adaptation to gravity transitions which captures the role of implicit memory. This advancement enables faster readaptation to familiar gravitational stimuli, which has been observed in repeat flyers, by considering vestibular signals dependent on the new gravity environment, through Bayesian inference. The evolution and weighting of hypotheses considered by the CNS is modeled via a Rao-Blackwellized particle filter algorithm. Sensorimotor adaptation learning is facilitated by retaining a memory of past harmonious states, represented by a conditional state transition probability density function, which allows the model to consider previously experienced gravity levels (while also dynamically learning new states) when formulating new alternative hypotheses of gravity. In order to demonstrate our theoretical framework and motivate future experiments, we perform a variety of simulations. These simulations demonstrate the effectiveness of this model and its potential to advance our understanding of transitory states during which central reinterpretation occurs, ultimately mitigating the risks associated with the lagging time course of adaptation to gravitational environments.

Vestibular perceptual thresholds for rotation about the yaw, roll, and pitch axes.

This effort seeks to further assess human perception of self-motion by quantifying and comparing earth-vertical rotational vestibular perceptual thresholds about the yaw, roll, and pitch axes. Early seminal works (Benson Aviat Space Environ Med 60:205-213, 1989) quantified thresholds for yaw, roll, and pitch rotations, using single-cycle sinusoids in angular acceleration with a frequency of 0.3 Hz (3.33 s motion duration) and found yaw thresholds to be significantly lower than roll and pitch thresholds (1.58-1.20 deg/s vs. 2.07 deg/s and 2.04 deg/s, respectively). Our current effort uses modern methods and definitions to reassess if rotational thresholds differ between these three axes of rotation in ten human subjects at 0.3 Hz and additionally across a range of frequencies: 0.1 Hz, 0.3 Hz, and 0.5 Hz. In contrast to the established findings of Benson et al., no statistically significant differences were found between the three rotational axes at 0.3 Hz. Further, no statistically significant differences were found at any of these frequencies. Instead, a consistent pattern was found for yaw, pitch, and roll of increasing thresholds with decreasing rotational frequency, consistent with the brain employing high-pass filter mechanisms for decision-making. We also fill a gap in the literature by extending the quantification of pitch rotation thresholds to 0.1 Hz. Finally, we assessed inter-individual trends between these three frequencies and across all three axes of rotation. In thoroughly considering methodological and other differences between the current and previous studies, we conclude yaw rotation thresholds do not differ from those in roll or pitch.