Feature selection based on mutual information for human activity recognition
Benjamin Fish, Ammar Hussain Khan, Nabil Hajj Chehade, Chieh Chien, Greg J. Pottie · 2012
In this work, we consider a classification problem of 14 physical activities using a body sensor network (BSN) consisting of 14 tri-axial accelerometers. We use a tree-based classifier, and develop a feature selection algorithm based on mutual information to find the relevant features at every internal node of the tree. We evaluate our algorithm on 31 features per accelerometer (total of 434), and we present the results on 8 subjects with a 96% average accuracy.