IEEE SPS @ UF

Ergo — EMG/EEG biosignal acquisition + dynamical systems

A neuroengineering platform for studying stability in cooperative and competitive human-in-the-loop control using multi-subject EMG features and EEG/EMG acquisition.

Ergo project logo.

Overview

Ergo integrates biosignal hardware, feature extraction, and simulation to test how control systems move between stable and unstable regimes under cooperating vs. competing subjects and fatigue.

Ergo studies how dynamical systems behave when driven by human biosignals. The core hypothesis is that competition and cooperation produce different stability trajectories, and that fatigue-linked EMG features help explain those transitions.

What I built

  • An acquisition plan around ADS1299 + STM32 for repeatable EMG/EEG collection and reporting.
  • A modeling workflow that links extracted biosignal features to control-system stability metrics.
  • An experiment structure for comparing cooperative and competitive multi-subject scenarios.

Deliverables

  • Embedded C/MCU acquisition components and reproducible data pipelines.
  • Simulation executables and analysis outputs for publication-oriented evaluation.

Snapshot

Track
IEEE SPS @ UF · neurotech · human-machine systems
Status
Active; hardware integration and simulation phases underway.
Focus
EMG + EEGEmbedded acquisitionDynamical stability analysis

Stack

  • STM32 + ADS1299 embedded stack
  • Signal processing + feature extraction
  • Control/dynamical systems simulation

Glossary

EMG
Electromyography, a measurement of muscle electrical activity.