Inertia-1 pretraining buys robustness to downsampling for activity recognition but not disease prediction

Answers part of question-inertia-1-which-design-choices-win. Varying sampling rate across {20Hz, 5Hz, 1Hz, 0.2Hz} under a fixed ART/PatchTST pretraining setup, the Inertia-1 paper (arXiv:2607.06617) finds overall AUROC (across human activity recognition (HAR), freezing-of-gait (FoG) detection, and disease prediction) rising from 71.7 at 1Hz to 76.4 at 5Hz to 81.5 at 20Hz. But the effect is task-dependent rather than uniform: "pretrained representations remain competitive even at 1Hz" for HAR specifically, which the authors contrast with prior work — "unlike prior studies that report sharp drops below 10Hz." That robustness does not transfer to the clinical task: "this robustness is weaker for disease prediction, where higher sampling rates provide clearer gains, indicating that clinical outcomes may depend on subtle biomechanical signatures that are attenuated by aggressive downsampling."

Scope caveat, per the paper's own limitations section: this sampling-rate sweep was run only on its two "top-performing representative methods," ART and PatchTST — see claim-inertia-1-data-scale-beats-model-size for that caveat in full.