Motion fault detection and isolation in Body Sensor Networks
Significant amount of research and development is being directed on monitoring activities of daily living of senior citizens who live alone as well as those affected with certain disorders such as Alzheimer's and Parkinson's. A combination of sophisticated inertial sensing, wireless communication and signal processing technologies have made such a pervasive and remote monitoring possible. Due to the nature of the sensing and communication mechanisms, these monitoring sensors are susceptible to errors and failures. In this paper, we address the issue of identifying and isolating faulty sensors in a Body Sensor Network that is used for remote monitoring of daily living activities. We identify three different types of fault isolation strategies and propose both history-based and non-history based approaches.