No single window length is optimal across Inertia-1's task families

Answers part of question-inertia-1-which-design-choices-win. Varying the input window length across {10s, 30s, 60s, 2h} under a fixed ART/PatchTST pretraining setup, the Inertia-1 paper (arXiv:2607.06617) reports overall AUROC (across human activity recognition (HAR), freezing-of-gait (FoG) detection, and disease prediction) of 78.9 at 10 seconds, 81.5 at 30 seconds, and 81.2 at 60 seconds — a shallow peak around 30 seconds rather than a monotonic trend. The paper's own conclusion resists collapsing this into one recommended value: "no single duration is optimal across HAR, FoG, and Disease Prediction... short-window activity labels favor localized motion structure, whereas gait and health tasks may benefit from longer behavioral context."

Paired with claim-inertia-1-downsampling-robustness-is-task-dependent, this is the second of two design axes (window length here, sampling rate there) where the paper explicitly declines to name a universal winner, instead finding that the right setting depends on which of the three task families a deployment actually targets. Scope caveat, per the paper's own limitations section: this window-length sweep was run only on ART and PatchTST — see claim-inertia-1-data-scale-beats-model-size for that caveat in full.