Design of a continuous passive and active motion device for hand rehabilitation
Bibliographic record
Abstract
This paper presents the design of a novel, portable device for hand rehabilitation. The device provides for CPM (continuous passive motion) and CAM (continuous active motion) hand rehabilitation for patients recovering from damage such as flexor tendon repair and strokes. The device is capable of flexing/extending the MCP (metacarpophalangeal) and PIP (proximal interphalangeal) joints through a range of motion of 0 degrees to 90 degrees for both the joints independently. In this way, typical hand rehabilitation motions such as intrinsic plus, intrinsic minus, and a fist can be achieved without the need of any splints or attachments. The CPM mode is broken into two subgroups. The first mode is the use of preset waypoints for the device to cycle through. The second mode involves motion from a starting position to a final position, but senses the torque from the user during the cycle. Therefore the user can control the ROM by resisting when they are at the end of the desired motion. During the CPM modes the device utilizes a minimum jerk trajectory model under PD control, moving smoothly and accurately between preselected positions. CAM is the final mode where the device will actively resist the movement of the user. The user moves from a start to end position while the device produces a torque to resist the motion. This active resistance motion is a unique ability designed to mimic the benefits of a human therapist. Another unique feature of the device is its ability to independently act on both the MCP and PIP joints. The feedback sensing built into the device makes it capable of offering a wide and flexible range of rehabilitation programs for the hand.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".