Precalving behavior in dairy cattle with different calving times.

Predicting the calving time in dairy cattle can help in avoiding calving accidents and reducing burdens on animal caretakers. In this study, we analyzed the behavior of pregnant dairy cattle for 7 days prior to calving, to assess the feasibility of predicting the calving time. Eleven Holstein cows were divided into two groups based on their calving times, that is, in the morning (the Morning Parturition Group) or the evening (the Evening Parturition Group).

Analysis of characteristics required for gait evaluation of patients with knee osteoarthritis using a wireless accelerometer.

Background: Knee osteoarthritis (KOA) is associated with reduced quality of life due to knee pain and gait disturbance. However, the evaluation of KOA is mainly based on images and patient-reported outcome measures (PROMs), which are said to be insufficient for functional evaluation. Recently, gait analysis using an accelerometer has been used for functional evaluation of KOA patients.

Dairy cattle behavior classifications based on decision tree learning using 3-axis neck-mounted accelerometers.

Demand has been increasing recently for an automated monitoring system of animal behavior as a tool for the management of livestock animals. This study investigated the association between the behavior of dairy cattle and the acceleration data collected using three-axis neck-mounted accelerometers, as well as the feasibility of improving the precision of behavior classifications through machine learning. In total 38 Holstein dairy cows were used, and kept in four different farms.