An Interdisciplinary Myoelectric Prosthetic Hand Capstone Project
Bibliographic record
Abstract
Interdisciplinary capstone projects have been used in engineering education to provide students an opportunity to collaborate on a project with students from other disciplines that are different from their own.A few of the perceived benefits of such an experience are students developing a creative problem-solving approach, learning to communicate and collaborate with individuals outside of their major, increased understanding of the connections between different technical topics, and a deeper appreciation of other disciplines.For the last three years, York College of Pennsylvania has conducted an interdisciplinary capstone project focused on designing and constructing a prosthetic hand that will interpret muscle contractions from a young amputee and output the desired movement in the hand and fingers.The overarching goal of the design was to create an affordable option compared to commercially available prosthetics as young amputees can quickly grow out of their prosthetic limb and are more likely to use a prosthetic that is visually appealing.Two features of the prosthetic design are myoelectric technology to detect muscle contractions and 3D printing technology in the construction of the hand.Each academic year, a new student team spends two semesters focused on improving the prosthetic hand design from the previous year's team.The student team was small consisting of no more than five students from the Mechanical Engineering, Electrical Engineering, and Computer Engineering majors.This paper will detail the evolution of the interdisciplinary project from its first group of students who focused their efforts on researching and developing an initial prototype, due to working remotely because of the COVID-19 pandemic, to the current year's team concentrating on implementing sensors in the hand and refining the ergonomics of the existing design.The paper will also include student & faculty reflection and discussion of the faculty facilitation needed for such a service-based project and how engineering educators can consider implementing such projects into their programs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".