Signal ML · 2025
Automated EMG Onset Detection for Clinical Research
Finding the moment a muscle switches on.
The project
Developed tooling for USC’s NIH-funded rotator cuff tendinopathy study that automatically detects EMG onset times across seven shoulder muscles, identifies movement repetitions, and exports per-repetition biomarkers, replacing slow manual annotation.
At a glance
7 muscles — automated EMG onset & per-rep biomarkers — NIH study.
Built with
Biosignal Processing · Clinical ML · Signal Processing