2026-10-15T04:05:47Z https://www.scidb.cn/oai

10.57760/sciencedb.35878 2026-05-15T14:05:35Z

2026-05-15 A Continuous Multimodal Wearable Dataset of Synchronized Cardiac, Kinematic and Heat-Production Signals from Growing Pigs in Open-Circuit Respirometry Chambers (Porcine-CaMo January-2025 Cohort, 3 Chambers / 9 Pigs / 22-Day Trial Window / 45 Pig-Days, Accelerometer-Free Configuration with Professionally-Audited ECG Annotation Training Subset) doi:10.57760/sciencedb.35878 en This dataset (Porcine-CaMo January-2025 Cohort, paper-aligned release) provides continuous multimodal wearable recordings collected from 9 small-frame growing pigs (Sus scrofa domesticus, 25–33 kg, ear-tags 1–9) in January 2025 across three open-circuit respirometry chambers, with a 22-day designed trial window (2025-01-10 → 2025-01-26) and 15 effective recording days per chamber × 3 chambers = 45 chamber pig-days actually uploaded. Two key differences from the project's September–October cohort (DOI 10.57760/sciencedb.35116) are: (i) all three chambers (A1, B1, B2) provided functional respirometry during this campaign, so 5-min HP is available for every chamber; and (ii) the back-mounted wearable device for this cohort logged 512 Hz single-lead ECG (BMD101) and 10 Hz three-axis gyroscope plus on-board temperature only, with no accelerometer channel — making this cohort the project's "accelerometer-free" (trailnoacc) anchor for evaluating IMU + HRV → HP modelling under reduced sensor configurations. Raw signals are organized by chamber and date; each recording session produces paired Raw_*.txt (ECG) and AngleTemp_*.txt (gyroscope + temperature) files. Heat production was computed by OpenCalori-Swine (https://github.com/zengzhengcheng/OpenCalori-Swine<br>Zenodo DOI: 10.5281/zenodo.20051163) via the Brouwer equation. ECG streams were processed with ECG TransUNet (https://github.com/zengzhengcheng/ECG-TransUNet<br>Zenodo DOI: 10.5281/zenodo.20051167) for automatic R-peak detection followed by adaptive statistical correction, producing one per-chamber R-peak label series. Because of long retention before publication, the Perfect quality tier of this cohort's ECG was lost and is not part of this DOI; only the Corrected tier is released. As a high-accuracy equivalent subset, this dataset additionally publishes a dedicated top-level ECGModelTrainData/ directory containing ≈ 20 ECG training segments from B1 + B2 — this subset was reviewed by professionally hired human annotators and serves as the base-training corpus of ECG TransUNet (the correction fine-tuning corpus is excellent_data.hdf in the ECG-TransUNet repository root, Git LFS-tracked, independent of and not derived from this directory). Per-chamber 1 Hz integrated signals (*heart.csv + *move_v2.csv), the 5-min ML-ready feature table (A1B1B2_features.csv, 6,812 rows × 158 columns, plus per-chamber slices), five runnable v4 reference training scripts and four work-summary documents are bundled under TrainDataAndCode/. HP prediction models are trained per cohort separately; this DOI ships training features and reference scripts but does not ship pre-trained model weights. The HRV-processing pipeline, the gyroscope-only IMU pipeline and the ECG TransUNet ONNX inference weights are publicly open-sourced at https://github.com/zengzhengcheng/SwineSync-OpenSource<br>Zenodo DOI: 10.5281/zenodo.20051135; the heart-rate annotation GUI (SwineSync Studio annotator) is retained as an internal product tool distributed only as a Windows executable. The release supports precision livestock farming, accelerometer-free metabolism–behaviour modelling, welfare phenotyping, ECG R-peak detection model training, and benchmarking of wearable animal-physiology algorithms. precision livestock farming; wearable physiological monitoring; continuous ECG; R-peak detection; heart rate variability; gyroscope; open-circuit respirometry chamber; indirect calorimetry; heat production; multimodal data fusion; deep-learning ECG analysis; ECG training corpus; expert-audited annotation; Brouwer equation; growing pigs Zeng Zhengcheng Cao Shukai Wang Shupeng Zhang Shuai PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank