Train smarter. Prevent injuries.
AthleteEMG measures muscle activity and jump mechanics with EMG, ultrasonic and inertial sensors, then visualises the results so coaches and medical staff can spot risk early.
The problem
Injuries end seasons, and careers, too often.
Fatigue and poor movement patterns build up before an injury happens, but they are hard to see with the naked eye. Objective, data-driven monitoring helps coaches act before damage is done.
muscle activity signals captured during jumps.
sensing systems combined: ultrasonic and inertial measurement unit (IMU).
minimum foot clearance and orientation measured for every jump.
Source: system design from the founding research paper (Fusion Practice and Applications, 2024).
How it works
How it works
A clear path from data to decision.
Wear
Athletes wear EMG and motion sensors during training.
Capture
Ultrasonic and IMU systems measure foot clearance and orientation.
Analyse
LabVIEW virtual instruments process and display jump patterns.
Act
Coaches and physios adjust training based on the data.
Product
What makes it different.
Every feature is grounded in the founding research.
EMG analysis
Reads muscle activation to reveal fatigue and imbalance.
Jump analysis
Measures minimum foot clearance and orientation.
Error correction
Combining ultrasonic and IMU data gives a more complete, corrected picture.
IoMT ready
Wireless communication as a step toward connected sports medicine.
Who it's for
Who it's for.
Sports clubs & academies
Objective monitoring of training load.
Physiotherapists
Track recovery and return-to-play readiness.
Sports medicine centres
Data-driven athlete health assessments.
The research
Built on peer-reviewed research.
- Monitors and analyses athletes' jumps using EMG signals and virtual instruments (LabVIEW).
- Hardware includes sensory boards, ultrasonics and wireless communication.
- Two systems, ultrasonic and inertial measurement unit, measure minimum foot clearance and orientation.
- Combining both provides a complete solution with error correction.
Azmi, A., Al-Kubaisi, M., Mohammed, A. H., & Abdulbaqi, A. S. (2024). Medical Assistant System for Athletes' Health Analysis Based on EMG-Signals Activity and Virtual Instruments as a Step towards the Internet of Medical Things. Fusion Practice and Applications, 18(1), 56–65.
Team
The team behind it.
Founded in 2025 by a student team from two faculties.
Faculty of Physical Education & Sport Sciences
Sports performance, athlete testing and injury prevention.
Faculty of Engineering Technologies (Medical Devices)
Sensors, signal processing and system design.
FAQ
Questions we hear often.
Which sports is it for?
Any sport involving jumping and explosive movement, such as basketball, volleyball, football and athletics.
Does it diagnose injuries?
No. It monitors movement and muscle activity to support coaches and medical staff.
Is this a finished commercial product?
It is a research-based student startup moving from validated prototype toward pilots with real users.
Can we partner or run a pilot?
Yes. We are looking for organisations willing to test the solution in real conditions and share feedback.
Bring AthleteEMG to your organisation.
We are onboarding pilot partners now. Read the research and get in touch.