Ultimate Robotics

Manual labeling is the bottleneck of biosignal ML — every hour of EMG needs a human marking what the muscles were doing. We built a tool that removes the human: a first-person camera watches the hands, a pose model turns the video into timestamped gesture labels, and any instrument recording on the same clock — EMG in our lab, ECG or IMU in yours — inherits those labels for free. The camera is a teacher, not the product. During the event the loop closed: a pretrained hand model labeled 320 frames of our own footage (zero human keypoints), a small pose model fine-tuned on them and outgrew its teacher — 71% vs 46% — and now labels its own next dataset. On a consumer AMD GPU each fine-tune takes minutes, so labeling improves between recordings. Standalone, sensor-agnostic, open source: a session folder in, two CSVs out.