Improved Benchmarking Method Using Kinematics Analysis in Design of an Upper Limb Exoskeleton Rehabilitation Device
Bibliographic record
Abstract
Conceptual design plays an important role in product development to meet requirements of the product function, cost and other factors. Existing methods of the product conceptual design rely on experience of designers or benchmarking methods to estimate design parameters, which limits the design automation and optimization. This paper improves the benchmarking methods by integrating the kinematics analysis with quality function deployment in design of an upper limb exoskeleton rehabilitation device. Parameters such as velocity, acceleration and displacement of the product are included for rating benchmarking products to evaluate the rehabilitation device based on customer needs. By integrating the benchmarking method and kinematics analysis, products with the best performance can be determined accurately to help designers to improve the existing product or develop a new product. The proposed method is verified in the design of an upper limb rehabilitation device.
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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".