A Biomechanical Study for Developing Wearable-Sensor System to Prevent Hip Fractures among Seniors
Bibliographic record
Abstract
As the population ages, falls are becoming a major health problem, not only for those with some degree of balance or mobility impairment, but also among healthy active seniors. Previous studies suggest that the degradation of human sensorimotor function related to age contributes to falls. Hip bones are among the most frequently fractured body parts resulting from falls. Hip fractures are a frequent cause of early death, functional dependence, and high medical care costs. The current prevention method is to use hip protectors. Unfortunately, it often fails to do so because the pocket containing the pad can move away from the area during falls. Additionally, some seniors refuse to use hip protectors because they find them constraining. Hence, a new protector that is only activated during a fall is much desired. The current study explored the possibility via biomechanical analyses for building a wearable sensor system that triggers a mini-airbag system during a fall, i.e., the air-pad is only present for protection when a fall occurs. The results have revealed that two sensors placed on the left and right shoulder would be best for a detection of any-direction fall and could be applied for building a wearable sensor system for prevention of hip fractures resulting from falls.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".