A New Statistical-based Algorithm for ECG Identification

  • Authors:

  • Fufu Zeng;Kuo-Kun Tseng;Huang-Nan Huang;Shu-Yi Tu;Jeng-Shyang Pan

  • Affiliations:

  • -;-;-;-;-

  • Venue:
  • IIH-MSP '12 Proceedings of the 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
  • Year:
  • 2012

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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.