Nine Degree-of-Freedom Kinematic Modeling of the Upper-Limb Complex for Constrained Workspace Evaluation
Bibliographic record
Abstract
The design of rehabilitation devices for patients experiencing musculoskeletal disorders (MSDs) requires a great deal of attention. This article aims to develop a comprehensive model of the upper-limb complex to guide the design of robotic rehabilitation devices that prioritize patient safety, while targeting effective rehabilitative treatment. A 9 degree-of-freedom kinematic model of the upper-limb complex is derived to assess the workspace of a constrained arm as an evaluation method of such devices. Through a novel differential inverse kinematic method accounting for constraints on all joints1820, the model determines the workspaces in which a patient is able to perform rehabilitative tasks and those regions where the patient needs assistance due to joint range limitations resulting from an MSD. Constraints are imposed on each joint by mapping the joint angles to saturation functions, whose joint-space derivative near the physical limitation angles approaches zero. The model Jacobian is reevaluated based on the nonlinearly mapped joint angles, providing a means of compensating for redundancy while guaranteeing feasible inverse kinematic solutions. The method is validated in three scenarios with different constraints on the elbow and palm orientations. By measuring the lengths of arm segments and the range of motion for each joint, the total workspace of a patient experiencing an upper-limb MSD can be compared to a preinjured state. This method determines the locations in which a rehabilitation device must provide assistance to facilitate movement within reachable space that is limited by any joint restrictions resulting from MSDs.
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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 | 0.002 |
| 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 | 0.000 | 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".