A transition point: Assistance magnitude is a critical parameter when providing assistance during walking with an energy-removing exoskeleton or biomechanical energy harvester
Bibliographic record
Abstract
Researchers and engineers have developed exoskeletons capable of reducing the energetic cost of walking by decreasing the force their users' muscles are required to produce while contracting. The metabolic effect of assisting concentric and isometric muscle contractions depends, in part, on assistance magnitude. We conducted human treadmill experiments to explore the effects of assistance magnitude on the biomechanics and energetics of walking with an energy-removing exoskeleton designed to assist eccentric muscle contractions. Our results demonstrate that the assistance magnitude of an energy-removing device significantly affects the energetics, muscle activity, and biomechanics of walking. Under the moderate assistance magnitude condition, our device reduced the metabolic cost of walking below that of normal walking by 3.4% while simultaneously producing 0.29 W of electricity. This reduction in the energetic cost of walking was also associated with an 8.9% decrease in hamstring activity. Furthermore, we determined that there is an assistance magnitude threshold that, when crossed, results in the device transitioning from assisting to hindering its user. This transition is marked by significant increases in muscle activity and the metabolic cost of walking. These results could aid in the future design of exoskeletons and biomechanical energy harvesters, as well as adaptive control systems, that identify user-specific control parameters associated with minimum energy expenditure.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".