Effects of saccade delay, side of deficit, and training on detection of catch-up saccades during head-impulse test in virtual-reality-enhanced mannequin - Imagerie et Vision Artificielle Accéder directement au contenu
Article Dans Une Revue Scientific Reports Année : 2023

Effects of saccade delay, side of deficit, and training on detection of catch-up saccades during head-impulse test in virtual-reality-enhanced mannequin

Résumé

In this study, a training simulator for the examination of dizzy patients based on a virtual-reality-enhanced mannequin (VREM) was developed to evaluate the detection of catch-up saccades during head impulse test (HIT) and the effect of training in VREM. For novices (n = 35), 2 trials were conducted before and after a training session. Experts (n = 7) were submitted to an evaluation session. In each trial, a left or a right horizontal canal deficit with an overt catch-up saccade (delay between 110 and 320 ms) was randomly presented. Participants scored the difficulty in performing the maneuver, in recognizing the saccades, and the self-confidence in the diagnosis using a visual analogue scale (VAS). Saccade delay significantly influenced the performance. Training significantly improved the sensitivity in the residents (69.1% before to 97.9% after the training, p < 0.001, Fisher's exact test, n = 560 tests), surpassing experts’ performances (p < 0.001, versus 87% in experts, Fisher's exact test). The specificity also increased to the expert level (78% before to 95% after the training, and 95% in experts, p < 0.001, Fisher’s exact test). The VAS showed a decrease difficulty to execute the HIT, with an increase in the confidence after training. VREM improved the HIT execution performance and the confidence in novice practitioners.
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Dates et versions

hal-04004051 , version 1 (24-02-2023)

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Ambre Charlery-Adèle, Caroline Guigou, Julien Ryard, Mathis Chartier, Michel Toupet, et al.. Effects of saccade delay, side of deficit, and training on detection of catch-up saccades during head-impulse test in virtual-reality-enhanced mannequin. Scientific Reports, 2023, 13 (1), pp.2718. ⟨10.1038/s41598-023-29801-8⟩. ⟨hal-04004051⟩
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