MYOSENSE

Muscle injuries are prevalent among athletes, yet they are often difficult to detect early without access to medical imaging or professional evaluation. As a result, athletes often rely on subjective pain feedback or wait until the injury becomes severe enough to be noticeable, which puts them at a disadvantage during training and recovery.

Since changes in muscle conductivity can indicate muscle strain or abnormal tissue behavior, having a simple and portable way to measure these changes could help athletes monitor their muscles more reliably.

In this project, we explore Electrical Impedance Tomography (EIT) as a low-cost and non-invasive method for detecting potential muscle injuries. After reviewing existing EIT systems, we propose a wearable EIT device inspired by the EIT-kit framework.

Our device includes:

a customizable 3D-printed electrode band that fits around the target muscle,
a compact sensing board that injects small AC currents and measures the resulting voltages,
firmware that automatically calibrates the signals,
and a mobile visualization tool that reconstructs a real-time conductivity map of the muscle.

By analyzing these conductivity patterns during rest and movement, the system aims to highlight unusual changes that may indicate strain, inflammation, or other muscle issues.

Project Details

Student(s): Maroun Eid, Carmen Merheb, Serge El Skaf, Elian Rezk
Advisor(s): Dr. Noel Maalouf
Year: 2025-2026

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