Kinesthetic teaching of a therapist's behavior to a rehabilitation robot
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Bibliographic record
Abstract
The use of robots for rehabilitation has become increasingly attractive in recent years. Robots are capable of providing highly repetitive hands-on therapy for patients. In this paper, we present a robotic system for learning a therapist's behavior when interacting with a patient to complete a therapy task. Learning from Demonstration (LfD) techniques are utilized to statistically encode the therapist's behaviors during interaction with a patient. Demonstrations are provided by having the therapist move the patient (and the robot) during the therapy task, which is known as kinesthetic teaching. Later, reproduction of the therapist's interaction is performed by a robot in the absence of the therapist, allowing a patient to continue practicing the therapy task. The results show the system is able to provide interactions similar to the therapist's demonstrated behavior for a given task.
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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