Performance analysis of triaxial accelerometer for activity recognition

Human Activity Recognition (HAR) based on accelerometer has become an important mobile application. Activity recognition however depends on X, Y, Z the Cartesian coordinate parameters. There are several approaches for activity recognition. Popular methods of activity recognition using accelerometer reading includes machine learning approach, rule based data mining approach, fuzzy inference approach etc. This paper compares activity recognition based on temporal pattern mining and ANFIS method for wearable sensor accelerometer and mobile accelerometer readings. Though the existing activity recognition using body worn accelerometer gives better accuracy it is found to be costly and consume more power. Hence this paper proposes an ANFIS based activity recognition with the available accelerometer in mobile phone.