Variable-stiffness prosthesis improves biomechanics of walking across speeds compared to a passive device
Bibliographic record
Abstract
Ankle push-off power plays an important role in healthy walking, contributing to center-of-mass acceleration, swing leg dynamics, and accounting for 45% of total leg power. The majority of existing passive energy storage and return prostheses for people with below-knee (transtibial) amputation are stiffer than the biological ankle, particularly at slower walking speeds. Additionally, passive devices provide insufficient levels of energy return and push-off power, negatively impacting biomechanics of gait. Here, we present a clinical study evaluating the kinematics and kinetics of walking with a microprocessor-controlled, variable-stiffness ankle-foot prosthesis (945 g) compared to a standard low-mass passive prosthesis (Ottobock Taleo, 463 g) with 7 study participants having unilateral transtibial amputation. By modulating prosthesis stiffness under computer control across walking speeds, we demonstrate that there exists a stiffness that increases prosthetic-side energy return, peak power, and center-of-mass push-off work, and decreases contralateral limb peak ground reaction force compared to the standard passive prosthesis across all evaluated walking speeds. We demonstrate a significant increase in center-of-mass push-off work of 26.1%, 26.2%, 29.6% and 29.9% at 0.75 m/s, 1.0 m/s, 1.25 m/s, and 1.5 m/s, respectively, and a significant decrease in contralateral limb ground reaction force of 3.1%, 3.9%, and 3.2% at 1.0 m/s, 1.25 m/s, and 1.5 m/s, respectively. This study demonstrates the potential for a quasi-passive microprocessor-controlled variable-stiffness prosthesis to increase push-off power and energy return during gait at a range of walking speeds compared to a passive device of a fixed stiffness.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".