Estimating Trunk and Neck Stabilization for Avoiding Head Impact during Real-World Falls in Older Adults
Bibliographic record
Abstract
In this work, we quantify the neck's involvement in stabilizing the head during falls in older adults to avoid head impacts. We tracked kinematics of 12 real-world backward falls in long-term care captured on video, where head impact was avoided. We estimated dynamic spring-dashpot parameters of the neck and hip representing active muscle activity and passive tissue structures. Neck stiffness, damping, and target posture averaged 24.00±6.17Nm/rad, 0.38±0.16Nms/rad, and 76.2±14.7° flexion respectively. The stiffness and target posture suggest that residents actively contracted their neck muscles to maintain the head upright. Our results shed light on the importance of neck strength for avoiding head impact during a fall.Clinical Relevance-Falls account for 80% of traumatic brain injuries in adults 65+ years. While upper limb bracing can reduce the risk of head impacts during a fall in young adults, this protective response is less effective in older adults living in longterm care. Understanding how the neck and torso musculature are used to avoid head impact can guide the design of therapeutic exercise programs and assistive or protective devices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".