storage, retrieval, and communication of body sensor network data
Recently, Body Sensor Networks (BSNs) are being deployed for monitoring and managing medical conditions as well as human performance in sports. These BSNs include various sensors such as accelerometers, gyroscopes, EMG (Electromyogram), EKG (Electro-cardiograms), and other sensors depending on the needs of the medical conditions. Data from these sensors are typically Time Series data and the data from multiple sensors form multiple, multidimensional time series data. Analyzing data from such multiple medical sensors pose several challenges: different sensors have different characteristics, different people generate different patterns through these sensors, and even for the same person the data can vary widely depending on time and environment. This tutorial describes the technologies that go behind BSNs - both in terms of the hardware infrastructure as well as the basic software. First, we outline the BSN hardware features and the related requirements. We then discuss the energy and communication choices for BSNs. Next, we discuss approaches for classification, data mining, visualization, and securing these data. We also show several demonstrations of body sensor networks as well as the software that aid in analyzing the data.
body sensor networks multidimensional fuzzy clustering factor analysis association rules principal component analysis