Background: Vestibular flight illusions remain a significant source of concern for aviation training. Most fixed-based simulation training environments, including new virtual reality (VR) technology, lack the ability to recreate vestibular flight illusions as vestibular cues cannot be provided without stimulating the vestibular end organs. Galvanic vestibular stimulation (GVS) has long been used to create vestibular perception. The purpose of this study is to evaluate the ability of GVS to simulate common flight illusions by intentionally providing mismatched GVS during flight simulation scenarios in VR.Methods: Nineteen participants performed two flight simulation tasks—take off and sustained turn—during two separate VR flight simulation sessions, with and without GVS (control). In the GVS session, specific multi-axis GVS stimulation (i.e., electric currents) was provided to induce approximate somatogravic and Coriolis illusions during the take-off and sustained turn tasks, respectively. The participants used the joystick to self-report their subjective motion perception. The angular joystick movement along the roll, yaw, and pitch axes was used to measure cumulative angular distance and peak angular velocity as continuous variables of motion perception across corresponding axes. Presence and Simulator Sickness Questionnaires were administered at the end of each session.Results: The magnitude and variability of perceived somatogravic illusion during take-off task in the form of cumulative angular distance (p < 0.001) and peak velocity (p < 0.001) along the pitch-up axis among participants were significantly larger in the GVS session than in the NO GVS session. Similarly, during the sustained turn task, perceived Coriolis illusion in the form of cumulative angular distances (roll: p = 0.005, yaw: p = 0.015, pitch: p = 0.007) and peak velocities (roll: p = 0.003, yaw: p = 0.01, pitch: p = 0.007) across all three axes were significantly larger in the GVS session than in the NO GVS session. Subjective nausea was low overall, but significantly higher in the GVS session than in the NO GVS session (p = 0.026).Discussion: Our findings demonstrated that intentionally mismatched GVS can significantly affect motion perception and create flight illusion perceptions during fixed-based VR flight simulation. This has the potential to enhance future training paradigms, providing pilots the ability to safely experience, identify, and learn to appropriately respond to flight illusions during ground training.

Background/Objectives: Galvanic vestibular stimulation (GVS) integrated into virtual reality (VR) environments enhances immersion and mitigates cybersickness. It is well known that GVS can affect standing balance. Most studies have investigated the effects of GVS in VR in seated conditions. The purpose of this study was to evaluate the impact of joint GVS and VR with moving visual stimulus on standing balance. Methods: Using a repeated measures counter-balanced design, motion sickness, postural sway, and velocity utilizing the center of pressure (COP) along the mediolateral (ML) and anteroposterior (AP) axes were obtained in 18 subjects during optokinetic (OPK) stimulus (black and white vertical bars moving from left to the right) in VR across three interventions: GVS in the same direction of visual stimulus—left to right ear (Positive GVS), GVS in the opposite direction of visual stimulus—right to left ear (Negative GVS), and without GVS (Null GVS). Motion sickness symptom scoring was obtained using the Pensacola Diagnostic Index. Results: The PDI score was increased significantly in the Negative GVS. The root mean square and sway range of COP along ML was greater during the Positive GVS and Negative GVS than the Null GVS, while, along AP, it was only greater during Negative GVS. During Positive GVS, mean positive and negative peak velocities, only in ML, were increased and decreased, respectively. During Negative GVS, only negative peak velocities in both ML and AP directions were decreased. Conclusions: This research highlights the importance of testing combined VR and GVS to assess standing balance while mitigating cybersickness.

Processing of accelerometer data for recognizing short duration hand movements is a challenging problem. This paper focuses on characterization of acceleration data corresponding to hand movements (lift to mouth, scoop, stir, pour, unscrew cap) using aggregate statistical features and histograms computed from raw acceleration and derivative of the acceleration data. Data collected from an accelerometer placed on the wrist of subjects was used to perform the analysis. Supplementing the statistical features with raw acceleration histograms had a very marginal effect on the classification performance. However, the addition of derivative histograms resulted in a considerable improvement in the classification accuracy by nearly 8%. The effect of bin size of the derivative histograms was also conducted. It was observed that having a small number of bins decreased the classification accuracy by 3%. We thus show that adding features that capture the distribution of the changes in the acceleration data improve the classification performance.