arXiv Machine Learning October 16, 2026 By Max Rosenblattl, Milana Gurbanova, Karl Aurel Deck, Narayan Schuetz, Thomas Kaar, Manuel Milling, Nicolas Zumarraga, Ning Wang, Kelly W. Zhang, Anders Johnson, Robert Jakob, Bj\"orn W. Schuller, Elgar Fleisch, Daniel Seung Kim, Allan Lawrie, Patrick Langer, Maxwell A. Xu, Euan Ashley, Paul Schmiedmayer

TimeCap: A Scalable Open-Source Pipeline for Captioning Wearable Health Time-Series Data

Read the original on arXiv Machine Learning →

TimeCap is an open, deterministic pipeline that generates text captions for wearable health time‑series data without using a language model in the loop. It consists of three reusable extractor tiers and a cross‑channel synthesis layer, allowing new schemas to be added by defining channel mappings. Applying TimeCap to the MyHeart Counts dataset produced MHCap, the largest open caption layer for multimodal wearable data, containing 7,005,763 captions over 908,944 person‑days across 19 Apple HealthKit channels.

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