Extreme value statistics for novelty detection in biomedical signal processing

The issue of determining whether some datum is indicative of abnormal or novel system behaviour is paramount in areas such as medical data analysis where the acquisition of large quantities of abnormal data is difficult. Several approaches to screening data for such novel segments have been proposed previously. However, extreme-value theory (EVT) and its associated statistics provide a complete and principled approach to the problem which avoids the need for heuristic methods. EVT forms an elegant methodology for any problem in which the chance of finding extremes of some quantity is required.