Development and Control of a Robotic Exoskeleton for Shoulder, Elbow and Forearm Movement Assistance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
World health organization reports, annually more than 15 million people worldwide suffer a stroke and cardiovascular disease, among which 85% of stroke patients incur acute arm impairment, and 40% of victims are chronically impaired or permanently disabled. This results a burden on the families, communities and to the country as well. Rehabilitation programs are the main way to promote functional recovery in these individuals. Since the number of such cases is constantly growing and that the duration of treatment is long, an intelligent robot could significantly contribute to the success of these programs. We therefore developed a new 5DoFs robotic exoskeleton named MARSE -5 (motion assistive robotic-exoskeleton for superior extremity) that supposed to be worn on the lateral side of upper arm to rehabilitate and ease the shoulder, elbow and forearm movements. This paper focused on the design, modeling, development and control of the proposed MARSE -5. To control the exoskeleton, a nonlinear sliding mode control (SMC) technique was employed. In experiments, trajectory tracking that corresponds to typical passive rehabilitation exercises was carried out. Experimental results reveal that the controller is able to maneuver the MARSE -5 efficiently to track the desired trajectories.
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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 | 0.000 |
| 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 it