Foot contact forces can be used to personalize a wearable robot during human walking
Bibliographic record
Abstract
Individuals with below-knee amputation (BKA) experience increased physical effort when walking, and the use of a robotic ankle-foot prosthesis (AFP) can reduce such effort. The walking effort could be further reduced if the robot is personalized to the wearer using human-in-the-loop (HIL) optimization of wearable robot parameters. The conventional physiological measurement, however, requires a long estimation time, hampering real-time optimization due to the limited experimental time budget. This study hypothesized that a function of foot contact force, the symmetric foot force-time integral (FFTI), could be used as a cost function for HIL optimization to rapidly estimate the physical effort of walking. We found that the new cost function presents a reasonable correlation with measured metabolic cost. When we employed the new cost function in HIL ankle-foot prosthesis stiffness parameter optimization, 8 individuals with simulated amputation reduced their metabolic cost of walking, greater than 15% (p < 0.02), compared to the weight-based and control-off conditions. The symmetry cost using the FFTI percentage was lower for the optimal condition, compared to all other conditions (p < 0.05). This study suggests that foot force-time integral symmetry using foot pressure sensors can be used as a cost function when optimizing a wearable robot parameter.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".