A single tri-axial accelerometer-based real-time personal life log system capable of activity classification and exercise information generation.

Recording a personal life log (PLL) of daily activities is an emerging technology for u-lifecare and e-health services. In this paper, we present an accelerometer-based personal life log system capable of human activity classification and exercise information generation. In our system, we use a tri-axial accelerometer and a real-time activity recognition scheme in which a set of augmented features of accelerometer signals, processed with Linear Discriminant Analysis (LDA), is classified by our hierarchical artificial neural network classifier: in the lower level of the classifier, a state of an activity is recognized based on the statistical and spectral features; in the upper level, an activity is recognized with a set of augmented features including autoregressive (AR) coefficients, signal magnitude area (SMA), and tilt angles (TA).