Biomechanics of the Upper Extremity in Response to Dynamic Impact Loading Indicative of a Forward Fall: An Experimental and Numerical Investigation
Bibliographic record
Abstract
The distal radius is one of the most common fracture sites in humans, often resulting from a forward fall with more than 60 % of all fractures to the wrist requiring some form of surgical intervention. Although there is a general consensus regarding the risk factors for distal radius fractures resulting from forward falling, prevention of these injuries requires a more thorough understanding of the injury mechanisms. Therefore the overall purpose of this dissertation was to assess the response of the upper extremity to impact loading to improve the understanding of distal radius fracture mechanisms and the effectiveness of joint kinematic strategies for reducing the impact effects. Three main studies were conducted that utilized in vivo, in vitro and numerical techniques. In vitro impact testing of the distal radius revealed that fracture will occur at a mean (SD) resultant impact force and velocity of 2142.1(1228.7) N and 3.4 (0.7) m/s, respectively. Based on the failure data, multi-variate injury criteria models were produced, highlighting the dynamic and multidirectional nature of distal radius fractures The in vitro investigation was also used to develop and validate a finite element model of the distal radius. Dynamic impacts were simulated in LS-DYNA® and the resulting z-axis force validation metrics (0.23-0.54) suggest that this is a valid model. A comparison of the experimental fracture patterns to those predicted numerically (i.e. von-Mises stress criteria) shows the finite element model is capable of accurately predicting bone failure. Finally, an in vivo fall simulation apparatus was designed and built that was found to reliably (Intraclass Correlation Coefficients >0.6) apply multi-directional motion and upper extremity impacts indicative of forward falls. This study revealed that, to some extent, individuals are capable of selected an impact strategy that minimizes the significant injury variables that were outlined in the in vitro investigation, with very little instruction. The body of work presented here has the potential to be used to develop distal radius fracture prevention methods in an attempt to improve the health and well being of those individuals currently at the highest risk of sustaining these injuries.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".