Head roll compensation in a visually coupled HMD: considerations for helicopter operations.
Bibliographic record
Abstract
BACKGROUND: The helmet-mounted display (HMD) research program at the Flight Research Laboratory of the National Research Council of Canada examined the effects of HMD camera platform dynamics on pilot workload. Many currently fielded visually coupled HMD systems do not reproduce head movements in the roll axis which can lead to the presentation of visual information that is not consistent with vestibular and proprioceptive information. HYPOTHESIS: Our hypothesis was that this sensory conflict can induce motion sickness and increase pilot workload. METHODS: To examine this premise, three pilots flew a series of standardized maneuvers with or without roll compensation in the camera platform of a visually coupled HMD system. RESULTS: Increases in motion sickness symptoms and pilot workload were noted during complex, high-workload maneuvers when no roll compensation was present in the camera platform. During the most demanding maneuvers, the lack of roll compensation in the camera platform made it difficult for the evaluation pilot to control the helicopter. CONCLUSIONS: Roll compensation in visually coupled HMD systems reduces pilot workload and' motion sickness during critical flight periods where pilot workload may already be considerable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".