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A Non-Invasive Continuous Respiration Rate Monitoring Device for Dairy Cattle Under Commercial Farm Conditions
Mathias Eisner1, Manuel Jedinger1, Daniel Eingang2
1smaXtec Animal Care GmbH, Sandgasse 36/2, A-8010 Graz, Austria.
A new non-invasive nose ring device accurately monitors dairy cattle respiration rate (RR) continuously. This technology enables long-term health and stress tracking in commercial farm settings.
Area of Science:
- Animal Physiology
- Agricultural Engineering
- Biomedical Engineering
Background:
- Respiration rate (RR) is crucial for assessing dairy cattle health, stress, and thermoregulation.
- Continuous RR monitoring in commercial farms presents significant challenges.
- Existing methods for RR monitoring are often invasive or impractical for long-term use.
Purpose of the Study:
- To develop and validate a non-invasive, clip-on nose ring device for continuous acoustic respiration rate monitoring in dairy cattle.
- To assess the accuracy and feasibility of the device for multi-day, within-animal RR assessment under commercial farm conditions.
Main Methods:
- A clip-on nose ring device with a MEMS microphone was designed for acoustic recording at the nostril.
- The device was deployed on five dairy cows in a commercial barn for multi-day recordings.
- Respiration rate was extracted using a signal-processing pipeline based on multiscale periodicity detection.
- Algorithm-derived RR was validated against manually annotated breath events.
Main Results:
- The algorithm achieved high accuracy with a mean absolute error of 1.47 bpm and root mean square error of 1.92 bpm.
- A strong correlation (r = 0.98, R 2 = 0.96) was observed between algorithm-derived RR and reference values.
- Stable multi-day monitoring revealed clear diurnal respiration patterns without baseline drift.
Conclusions:
- The audio-based nose ring device is feasible for continuous, long-term respiration monitoring in dairy cattle.
- This technology provides a practical foundation for longitudinal RR assessment in commercial farm settings.
- Further validation in extreme environments and larger cohorts is recommended for population-level assessment.
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