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 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.
Ergo pairs custom EMG/EEG acquisition hardware with dynamical-systems analysis of human-in-the-loop control.
Ergo builds biosignal-acquisition tooling — with an emphasis on EMG and EEG — and uses it to study how a control system's stability shifts when it is driven by human biosignals. The working hypothesis is that cooperation and competition between subjects, and fatigue-linked changes in EMG, produce measurably different stability trajectories.
The intended hardware path is deliberately standard and repeatable rather than exotic:
Like the other SPS team projects, Ergo runs on issue-per-task ownership, a branch and linked pull request per issue, and CI plus review before anything merges — with hardware specs and a bill of materials tracked alongside the code.
Hardware integration and the simulation side are both underway; this is an active build rather than a finished system, so the page describes the plan and the acquisition stack rather than claiming results.