Literature DB >> 30415860

Technical note: Development of a noninvasive respiration rate sensor for cattle.

S Strutzke1, D Fiske1, G Hoffmann2, C Ammon1, W Heuwieser3, T Amon4.   

Abstract

The measurement of the respiration rate (RR) in cattle is a valuable tool for monitoring health status. Thus, an RR sensor can be essential for stress detection, especially heat stress. Heat stress leads to a deviation of the normal RR and results in a decrease of milk production and fertility. Therefore, continuous monitoring of the RR can help early detection of heat stress and, thus, initiate timely counteractive actions to minimize physical stress. The most common method to measure the RR in cattle is to count the flank movement visually; however, this method is time-consuming and labor-intensive. In addition, the continuous measurement of the RR is difficult to implement and can be physically strenuous. Therefore, a device based on a differential pressure sensor that can record RR automatically has been developed to make continuous long-term studies possible. The aim of this study was to validate the data measured by the device with the help of a reference method. The reference method used was counting the flank movements of a total of 6 cows (Holstein-Friesian). The rear flank movements of each cow were recorded by a camera and counted independently of the device by an observer. Eight videos of 1 min each were recorded per cow. The data analysis was done with cows in 3 different body positions: dozing, lying, and standing. A total of 48 RR measurements of the device were compared with the counted RR frequencies of the video recording. The results were highly correlated during dozing [correlation coefficient (r) = 0.92, n = 13], lying (r = 0.98, n = 15), and standing (r = 0.99, n = 20). The evaluation showed that the device is suitable for automated RR counting. Further development of a marketable device is planned.
Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  respiration rate; sensor; stress monitoring; validation

Mesh:

Year:  2018        PMID: 30415860     DOI: 10.3168/jds.2018-14999

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  6 in total

1.  Technical note: a nose ring sensor system to monitor dairy cow cardiovascular and respiratory metrics.

Authors:  Yael Salzer; Guy Lidor; Lavie Rosenfeld; Liad Reshef; Ben Shaked; Joseph Grinshpun; Hen H Honig; Hadar Kamer; Moria Balaklav; Maya Ross
Journal:  J Anim Sci       Date:  2022-09-01       Impact factor: 3.338

2.  How should the respiration rate be counted in cattle?

Authors:  L Dißmann; J Heinicke; K C Jensen; T Amon; G Hoffmann
Journal:  Vet Res Commun       Date:  2022-08-17       Impact factor: 2.816

3.  Infrared Thermography-A Non-Invasive Method of Measuring Respiration Rate in Calves.

Authors:  Gemma Lowe; Mhairi Sutherland; Joe Waas; Allan Schaefer; Neil Cox; Mairi Stewart
Journal:  Animals (Basel)       Date:  2019-08-07       Impact factor: 2.752

4.  Modelling and Validation of Computer Vision Techniques to Assess Heart Rate, Eye Temperature, Ear-Base Temperature and Respiration Rate in Cattle.

Authors:  Maria Jorquera-Chavez; Sigfredo Fuentes; Frank R Dunshea; Robyn D Warner; Tomas Poblete; Ellen C Jongman
Journal:  Animals (Basel)       Date:  2019-12-06       Impact factor: 2.752

5.  Assessment of feeding, ruminating and locomotion behaviors in dairy cows around calving - a retrospective clinical study to early detect spontaneous disease appearance.

Authors:  Mahmoud Fadul; Luigi D'Andrea; Maher Alsaaod; Giuliano Borriello; Antonio Di Lori; Dimitri Stucki; Paolo Ciaramella; Adrian Steiner; Jacopo Guccione
Journal:  PLoS One       Date:  2022-03-04       Impact factor: 3.240

Review 6.  Affective State Recognition in Livestock-Artificial Intelligence Approaches.

Authors:  Suresh Neethirajan
Journal:  Animals (Basel)       Date:  2022-03-17       Impact factor: 3.231

  6 in total

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