A Research-Grade tool for animal health data

Animal health researchers typically look for high-frequency, multi-dimensional physiological data that can be tracked over time without disturbing the animal's natural behavior. The ideal datasets offer correlation across metrics like heart rate, respiration, movement, and stress levels.
PetPace collects continuous, structured, near real-time data across vital signs and behavior markers — making it especially useful for large-scale, longitudinal, or AI-driven analysis.

In most research projects, access to clean, well-organized, exportable datasets is essential. Researchers often require a secure platform that supports raw data review, customizable sampling intervals, and cloud-based storage.
PetPace offers access to its web and mobile apps, customizable dashboards, and API connectivity for institutions that need export-ready, high-volume data in real time.

Many studies aim to complement clinical data with passive, real-world measurements. Combining hands-on diagnostics with remote monitoring improves data richness and allows for a more complete understanding of health conditions.
PetPace collars are designed to monitor without interfering with routine care — helping researchers gather long-term, contextual data from natural environments without affecting standard protocols.

Academic and peer-reviewed publications demand high data quality, often validated by comparisons to gold-standard instruments. Accuracy, repeatability, and timestamp integrity are key.
PetPace data has been validated in academic and government research settings, including Tufts, LSU, and DHS studies, with accuracy benchmarks matching clinical monitoring tools.

Remote monitoring is particularly valuable in studies of chronic disease, behavioral science, stress, drug efficacy, and rehabilitation. These often require repeated, passive measurement without clinical interference.
PetPace enables precisely this type of work — giving teams real-world insights into physiology and behavior while minimizing disruption to the animal. It also improves pet owner engagement and compliance, helping teams collect more consistent and real-world data in studies that depend on owner participation.