Decision making using electromyographic signals

点击翻译按钮获取中文摘要

Decision Making using Electromyographic SignalsClinical examination of diseased muscle is performed, in part, through qualitative analysis of electromyographic data obtained from a needle electrode placed within a contracting muscle.While some efforts have been made to provide a quantitative framework for this analysis, clinical adoption of these quantitative techniques has been slow to occur.  This is largely due to the unfamiliarity of clinical staff with these new techniques, and a lack of quality tools to assist in the interpretation and exploration of this data.I therefore propose to establish a tool designed to assist a clinical professional in the exploration of the electromyographic data of a particular patient, providing a context of the similarity of the patient's data with the various types of muscular disease.  To achieve this goal, a database of normative and disease data must be created and validated, allowing the construction of a knowledge base describing this data.  This knowledge base will be constructed through the applied statistical analysis techniques found in the "pattern discovery" rule based system.Using the knowledge base so constructed, an interpretive decision support tool will allow the clinical professional to visually explore the relations within the knowledge base, providing a clear means of establishing the relationship between the patient under examination with the data describing prior examinations exhibiting various states and stages of muscular disease.The described system will initially focus on myopathic and neuropathic disease states, and the ability to discern the difference between these disease states and normal data.  Upon establishment of this database, it will be possible to extend the system to further disease types, including stress injury and stroke.