Health monitoring with learning methods

Abstract

In this paper we provide a framework for the design of a practical monitoring method with learning methods. We demonstrate that three medical and industrial monitoring problems involve subproblems that can be tackled with our approach. Application of interference removal, novelty detection and learning of a signature leads to a feasible monitoring method in these cases.