E-Health Human Activity Recognition Scheme Using Smartphone's Data

In this paper, we proposed a new classification model to perform automatic recognition of activities using Smartphones data from a gyroscope and accelerometer sensors. We target assisted living applications such as remote patient activity monitoring for the disabled and the elderly. The proposed method LDA-KNN-SVM combine the Linear Discriminant Analysis (LDA) for dimension reduction and K-Nearest Neighbors (KNN) with Support Vector Machines (SVM) allowing to better discrimination between the classes of activities. Several experiments performed with real datasets show a significant improvement of our proposed approach in terms of recognition performance.