Chronic symptoms after vestibular neuritis and the high velocity vestibulo-ocular reflex

Hypothesis: As the anterior and posterior semicircular canals are vital to the regulation of gaze stability, particularly during locomotion or vehicular travel, we tested whether the high velocity vestibulo‐ocular reflex (VOR) of the three ipsilesional semicircular canals elicited by the modified Head Impulse Test would correlate with subjective dizziness or vertigo scores after vestibular neuritis (VN). Background: Recovery following acute VN varies with around half reporting persistent symptoms long after the acute episode. However, an unanswered question is whether chronic symptoms are associated with impairment of the high velocity VOR of the anterior or posterior canals. Methods: Twenty patients who had experienced an acute episode of VN at least three months earlier were included in this study. Participants were assessed with the video head impulse test (vHIT) of all six canals, bithermal caloric irrigation, the Dizziness Handicap Inventory (DHI) and the Vertigo Symptoms Scale short‐form (VSS). Results: Of these 20 patients, 12 felt that they had recovered from the initial episode whereas 8 did not and reported elevated DHI and VSS scores. However, we found no correlation between DHI or VSS scores and the ipsilesional single or combined vHIT gain, vHIT gain asymmetry or caloric paresis. The high velocity VOR was not different between patients who felt they had recovered and patients who felt they had not. Conclusions: Our findings suggest that chronic symptoms of dizziness following VN are not associated with the high velocity VOR of the single or combined ipsilesional horizontal, anterior or posterior semicircular canals.

MUSA: A Scalable Multi-Touch and Multi-Perspective Variability Management Tool

Variability management is one of the main activities in the Software Product Line Engineering process. Common and varied features of related products are modelled along with the dependencies and relationships among them. With the increase in size and complexity of product lines and the more holistic systems approach to the design process, managing the ever- growing variability models has become a challenge. In this paper, we present MUSA, a tool for managing variability and features in large-scale models. MUSA adopts the Separation of Concerns design principle by providing multiple perspectives to the model, each conveying different set of information. The demonstration is conducted using a real-life model (comprising of 1000+ features) particularly showing the Structural View, which is displayed using a mind-mapping visualisation technique (hyperbolic trees), and the Dependency View, which is displayed graphically using logic gates.