EFFECT OF TRANSTIBIAL PROSTHESIS MASS ON GAIT ASYMMETRIES
Bibliographic record
Abstract
BACKGROUND: Individuals with transtibial amputation (TTA) typically walk with an asymmetrical gait pattern, which may predispose them to secondary complications and increase risk of fall. Gait asymmetry may be influenced by prosthesis mass. OBJECTIVE: To explore the effects of prosthesis mass on temporal and limb loading asymmetry in people with TTA following seven days of acclimation and community use. METHODS: Eight individuals with transtibial amputation participated. A counterbalanced repeated measures study, involving three sessions (each one week apart) was conducted, during which three load conditions were examined: no load, light load and heavy load. The light load and heavy load conditions were achieved by adding 30% and 50% of the mass difference between legs, at a proximal location on the prosthesis. Kinematic and ground reaction force data was captured while walking one week after the added mass. Symmetry indices between the prosthetic and intact side were computed for temporal (Stance and Swing time) and limb loading measures (vertical ground reaction force Peak and Impulse). FINDINGS: Following seven days of acclimation, no significant differences were observed between the three mass conditions (no load, light load and heavy load) for temporal (Stance time: p=0.61; Swing time: p=0.13) and limb loading asymmetry (vertical ground reaction force Peak: p=0.95; vertical ground reaction force Impulse: p=0.55). CONCLUSION: Prosthesis mass increase at a proximal location did not increase temporal and limb loading asymmetry during walking in individuals with TTA. Hence, mass increase subsequent to replacing proximally located prosthesis components may not increase gait asymmetry, thereby allowing more flexibility to the clinician for component selection. Layman's Abstract People with a below the knee amputation typically have an asymmetrical walking style, i.e., they spend more time and put more body weight on their non-amputated leg. This may result in development of knee or hip osteoarthritis of the non-amputated leg, over time. Further, an asymmetrical walking style may also predispose people to a greater number of falls. It is believed that the weight of a prosthesis may influence the walking asymmetry. It is, however, unclear if changing the weight of a prothesis during routine clinical visits (for example, switching or replacing prosthesis parts) would increase walking asymmetry. To explore this, eight individuals with a below the knee amputation had two different weights added to the top half of their prosthesis. After the addition of the weight, participants went home to use the device in their communities for seven days. Subsequently, they returned to the lab to record their walking. We observed that walking with the heavier prosthesis, using either load, did not increase the amount of time spent and body weight applied by our participants on their non-amputated side. Hence, adding mass to the top half of a prosthesis may not increase walking asymmetry. Article PDF Link: https://jps.library.utoronto.ca/index.php/cpoj/article/view/34609/26769 How To Cite: Seth M, Hou W, Goyarts L.R, Galassi J.P, Lamberg E.M. Effect of transtibial prosthesis mass on gait asymmetries. Canadian Prosthetics & Orthotics Journal. 2020;Volume 3, Issue 2, No.5. https://doi.org/10.33137/cpoj.v3i2.34609 Corresponding Author: Mayank Seth, PhDDelaware Limb Loss Studies Lab, University of Delaware, Newark, USA.E-mail: mseth@udel.eduORCID: https://orcid.org/0000-0003-3526-7058
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".