Abstract
Myofascial pain is a prevalent condition characterized by chronic musculoskeletal discomfort, often requiring precise diagnostic tools for effective assessment. This project focuses on developing an advanced robotic arm control system to facilitate fiber-optic evaluation of myofascial pain. By leveraging Python-based programming, the robotic arm’s functionality was significantly enhanced, transitioning from single-joint control via a proprietary app to parallel joint control through keyboard commands. This advancement streamlines operation, reducing assessment time and improving workflow efficiency.
Key contributions include establishing a robust communication protocol between the robotic arm and external hardware, optimizing system performance through collaboration with Dobot Factory technical support, and integrating user-friendly controls tailored for biomedical applications. The resulting system demonstrates potential for enhancing diagnostic precision in clinical settings, providing a scalable framework for similar robotic interventions in medical diagnostics.
Document Type
Article
Class Name
Electrical and Systems Engineering Undergraduate Research
Language
English (en)
Date of Submission
12-12-2023
Recommended Citation
Li, Yuyao, "Robotic Arm Controlling Strategy for Fiber-optic Assessment of Myofascial Pain" (2023). Electrical and Systems Engineering Undergraduate and Graduate Research. 32.
https://openscholarship.wustl.edu/eseundergraduate_research/32