Objective The aim of the EMG project was to develop a knowledge-based assistant to support physicians in all stages of an electromyographical (EMG) examination of patients with neurological diseases. The objective was to produce a system sufficiently robust to withstand clinical trials in a neurophysiological laboratory. Particular attention was given to involving users in the definition of requirements and in system acceptance testing, and to bringing medical knowledge-based systems to a fully functional state. The aim of the project was to develop a knowledge based assistant to support physicians in all stages of an electromyographical (EMG) examination of patients with neurological diseases. The objective was to produce a system sufficiently robust to withstand clinical trials in a neurophysiological laboratory. Particular attention was given to involving users in the definition of requirements and in system acceptance testing, and to bringing medical knowledge based systems to a fully functional state. The prototype EMG expert system supports the diagnostician in the analysis of EMG signals and advises on the test procedures to be performed. It includes a report generator, and contains a database of case studies. It incorporates a casual probabilistic network model to allow a unified approach to planning, diagnosis, explanation and reporting. The following major features were developed subsequently: robust inference systems; new ways of handling uncertainty by probabilistic methods; and methodologies of general applicability in knowledge representation, blackboard architecture, and user interface specification.The prototype EMG expert system constructed in Phase I supports the diagnostician in the analysis of EMG signals and advises on the test procedures to be performed. It includes a report generator, and contains a database of case studies. It incorporates acausal-probabilistic network model to allow a unified approach to planning, diagnosis, explanation and reporting. Phase II saw a substantial improvement in real-time performance and the development of the following major features: -robust inference systems -new ways of handling uncertainty by probabilistic methods -methodologies of general applicability in knowledge representation, blackboard architecture, and user-interface specification. Exploitation The integrated EMG knowledge-based assistant will broaden the scope of the use of electrophysiological techniques. An expert system shell based on causal-probabilistic reasoning, HUGIN, has been developed and is now available on the market. Fields of science natural sciencescomputer and information sciencesdatabasesnatural sciencescomputer and information sciencesknowledge engineeringnatural sciencescomputer and information sciencesartificial intelligenceexpert systems Programme(s) FP1-ESPRIT 1 - European programme (EEC) for research and development in information technologies (ESPRIT), 1984-1988 Topic(s) Data not available Call for proposal Data not available Funding Scheme Data not available Coordinator AXION A/S EU contribution No data Address BRENGNOEDVEJ 144 3460 BIRKEROED Denmark See on map Total cost No data Participants (4) Sort alphabetically Sort by EU Contribution Expand all Collapse all Institute of Neurology United Kingdom EU contribution No data Address The National Hospital, Queen Square WC1N 3BG LONDON See on map Total cost No data JUDEX DATASYSTEMER A/S Denmark EU contribution No data Address LYNGVEJ 8 9000 AALBORG See on map Total cost No data Logica Ltd United Kingdom EU contribution No data Address Betjeman House 104 Hills Road CB2 1LQ Cambridge See on map Total cost No data RESEARCH AND DEVELOPMENT INSTITUTE (NUC) Denmark EU contribution No data Address FREDRIK BAJERSVEY 7 9220 AALBORG See on map Total cost No data