A New Statistical-based Algorithm for ECG Identification

Abstract

In this paper, a new statistical-based ECG algorithm, which applies the idea of matching Reduced Binary Pattern, is proposed to seek a timely and accurate human identity recognition. A comparison with previous researches, the proposed design requires neither waveform complex information nor de-noising pre-processing in advance. Our algorithm is tested on the public MIT-BIH arrhythmia and normal sinus rhythm databases. The experimental result confirms that the proposed scheme is feasible for high accuracy, low complexity, and fast processing for ECG identification.