Classifying sows' activity types from acceleration patterns: an application of the Multi-Process Kalman Filter

An automated method of classifying sow activity using acceleration measurements would allow the individual sow's behavior to be monitored throughout the reproductive cycle; applications for detecting behaviors characteristic of estrus and farrowing or to monitor illness and welfare can be foreseen. This article suggests a method of classifying five types of activity exhibited by group-housed sows. The method involves the measurement of acceleration in three dimensions. The five activities are: feeding, walking, rooting, lying laterally and lying sternally. Four time series of acceleration (the three-dimensional axes, plus the length of the acceleration vector) are selected for each activity. Each time series is modeled using a Dynamic Linear Model with cyclic components. The classification method, based on a Multi-Process Kalman Filter (MPKF), is applied to a total of 15 times series of 120 observations, which involves 30 min for each activity. The results show that feeding and lateral/sternal lying activities are best recognized; walking and rooting activities are mostly recognized by a specific axis corresponding to the direction of the sow's movement while performing the activity (horizontal sidewise and vertical). Various possible improvements of the suggested approach are discussed.