Premature Ventricular Contraction Recognition using a Fuzzy Maximum Approaching Degree

This work presents a new methodology for ventricular premature contraction arrhythmias recognition using a set of geometrical attributes recently proposed and a fuzzy maximum approaching degree.  Pattern models based on triangular and trapezoidal membership functions are proposed and a committee comprising these functions is composed using some statistical data, beyond a mechanism for manual selection of attributes and automatic weighting for each attribute. The obtained results show the efficiency and validity of the proposed approach, with 99.07%, 98.36% and 99.79% of accuracy, sensibility and specificity, respectively, as good as the ones obtained by the state-of-art methods.