See notebook.ipynb for statistical analysis
The aim of the current study was to investigate the relation between reticulorumen contractions and monitored cow behaviors. A purpose-built pressure measuring device was used and shown to be capable of detecting the known contraction patterns in the reticulorumen of four rumen-fistulated cows. RF algorithms based on reticulum pressure data were developed to detect rumination and other cow behaviors. In addition, we developed a peak-detection algorithm for rumination based on visual observation of patterns in reticular pressure. Cow behaviors, differentiated in ruminating, eating, drinking, sleeping and ‘other’, as scored from video observation, were used to develop and test the algorithms. The results demonstrate that rumination of a cow can be detected by measuring pressure differences in the reticulum using either an RF algorithm or the developed peak-detection algorithm. A proof of principle is presented indicating that an RF can in addition detect eating, drinking and sleeping from the same data. The measurement device used in this study needed rumen-fistulated cows, but the results indicate that behavior detection based on only measurements in the reticulum is feasible and would thus be promising for wireless sensor techniques that may continuously monitor a range of important behaviors of cows.
