title: Systems engineering principles for the design of biomedical signal processing systems.
abstract: Systems engineering aims to produce reliable systems which function according to specification. In this paper we follow a systems engineering approach to design a biomedical signal processing system. We discuss requirements capturing, specification definition, implementation and testing of a classification system. These steps are executed as formal as possible. The requirements, which motivate the system design, are based on diabetes research. The main requirement for the classification system is to be a reliable component of a machine which controls diabetes. Reliability is very important, because uncontrolled diabetes may lead to hyperglycaemia (raised blood sugar) and over a period of time may cause serious damage to many of the body systems, especially the nerves and blood vessels. In a second step, these requirements are refined into a formal CSP‖ B model. The formal model expresses the system functionality in a clear and semantically strong way. Subsequently, the proven system model was translated into an implementation. This implementation was tested with use cases and failure cases. Formal modeling and automated model checking gave us deep insight in the system functionality. This insight enabled us to create a reliable and trustworthy implementation. With extensive tests we established trust in the reliability of the implementation.
authors.affiliation: Department of Engineering, University of Aberdeen, Scotland, UK. faust_o@web.de
authors.forename: Oliver
authors.initials: O
authors.lastname: Faust
authors.forename: Rajendra
authors.initials: R
authors.lastname: Acharya U
authors.forename: Bernhard H C
authors.initials: BH
authors.lastname: Sputh
authors.forename: Lim Choo
authors.initials: LC
authors.lastname: Min
mesh_terms: D001698:Biomedical Engineering / Q000379:methods; D003929:Diabetic Neuropathies / Q000378:metabolism; D006801:Humans; D006943:Hyperglycemia / Q000378:metabolism; D016571:Neural Networks, Computer; D015398:Signal Transduction; D013597:Systems Analysis; D049490:Systems Biology