Modular and Scalable Biosignal Learning Platform
Level of Education of Students Involved
Undergraduate
Faculty Sponsor
Reva Johnson; Georges El-Howayek
College
College of Engineering (COE)
Discipline(s)
Biomechanical Engineering
Presentation Type
Poster Presentation
Symposium Date
Spring 4-24-2025
Abstract
Biosignal acquisition and processing are fundamental skills for students in bioengineering fields. However, existing tools fall into two main categories. Low-cost biosignal sensors are accessible and affordable, but suffer from a large amount of noise which inhibits effective learning. On the other hand, high-end laboratory-grade systems provide clean and reliable signals but are prohibitively expensive, impractical for widespread use, and are designed as “black box” systems, with fully encapsulated signal processing and noise rejection circuits. This disconnect limits students’ abilities to learn and engage with EMG and other biosignal processing techniques, especially students with limited background knowledge of electronics and complicated circuit diagrams. To address this issue we propose a modular and scalable biosignal learning platform designed to bridge the gap between low-cost and high-end systems. The prototype uses an advanced lab kit that records EMG signals to control a prosthetic gripper. The learning platform integrates a printed circuit board (PCB) for each signal processing stage (e.g., amplification, notch filtering, low-pass filtering), with clearly marked inputs and outputs that allow students to visualize the effect of each stage on the biosignal. This setup allows students to individually test stages or build other systems using preexisting PCBs. This modular architecture allows students of all skill levels to gain hands-on experience with signal processing while tracking the different stages that the signal goes through without the need to be an expert in electronics and circuit design.
Recommended Citation
Salamon, Hugo; El-Howayek, Georges; and Johnson, Reva, "Modular and Scalable Biosignal Learning Platform" (2025). Symposium on Undergraduate Research and Creative Expression (SOURCE). 1471.
https://scholar.valpo.edu/cus/1471
Biographical Information about Author(s)
A soon-to-be BS Bio-mechanical engineer and scientist with a background in bioengineering prosthetic research; seeking to support R&D to accelerate better health outcomes for everyone by supporting complex and leading-edge projects designed to solve society's most challenging health problems; more builder than operator with a strong mindset toward unconventional approaches and fast iteration of transforming prototype systems into closed, production-ready platforms.