Analysis of Time and Frequency Domain Features of Accelerometer Measurements

This paper addresses the signal processing aspect of wireless sensor networks. It analyzes several time and frequency domain features of measurements that are taken from 3D accelerometer sensors. The measurements represent various types of movements related to humans and cars. The aim is to obtain quantitative as well as qualitative comparisons concerning the expression power of these features in the presence of various sources of uncertainties (calibration, placement of sensors, and time synchronization). For the qualitative analysis, we define fuzzy sets and fuzzy membership functions for all the features. Particular attention is given to the analysis of the existence of correlation between measurements of different sensor nodes. We will demonstrate that correlation coefficients of both time and frequency domain features exhibit high degrees of uncertainties. On the other hand, short time Fourier transformations (STFT) of all types of movements prove to be agnostic of various forms of measurement and calibration errors.