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 far-rowing 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. (C) 2007 Elsevier B.V. All rights reserved.