A lower limb exoskeleton based on recognition of lower limb walking intention
Bibliographic record
Abstract
Recognition of walking intention and assistance in the load-carrying driver’s walking capability are key challenging areas in lower limb exoskeletons. We present a lower limb exoskeleton called the unmanned technology research centre exoskeleton (UTRCEXO). It recognizes walking intention, including step initiation, step velocity (acceleration and deceleration), and step termination of drivers using only insole-type FSRs and three axis F/T sensors. UTRCEXO recognizes the driver’s intention of step initiation using insole-type FSRs and recognizes the intention of step velocity and step termination using three axis F/T sensors. UTRCEXO makes use of four DC motors, two at each knee and hip joint, to assist the driver. The the driver can carry a 20 kg payload comfortably with muscle activity reduction. In this paper, we evaluate muscle activity reduction in walking drivers equipped with UTRCEXO carrying a 20 kg payload.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 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".