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January 1, 2014IOSR Journal of Electronics and Communication EngineeringOpen Access

An Effectual Approach to Reduce the Noise in ECG

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Population

Raw noisy ECG signals

Comparison

FIR digital filters with a proposed new… vs FIR digital filters using existing windows

Design

Other

Key result

A proposed window function based on the clonal selection algorithm achieved a significantly higher Signal to Noise Ratio (28.567) for filtered ECG signals compared to Hamming, Hanning, and Kaiser windows.

Authors

GRGiritharan Ravichandran

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Overview

May enhance ECG denoising in computational research; leaves open clinical diagnostic impact and requires prospective validation.

Structured PICO

P
Population
Raw noisy ECG signals
I
Intervention
FIR digital filters with a proposed new windowing technique based on a clonal selection algorithm
C
Comparator
FIR digital filters using existing windows (Hamming, Hanning, Kaiser)
O
Outcome
Signal-to-Noise Ratio (SNR) of filtered ECGsurrogate

Main Result

Absolute Event Rate: 28.567% vs 0.9454%

A proposed windowing technique based on a clonal selection algorithm substantially improves the signal-to-noise ratio of ECG signals compared to standard windowing methods.

Cite This Study

Giritharan Ravichandran (2014) studied ECG noise. Proposed window function based on Clonal selection algorithm vs. Hamming, Hanning, and Kaiser windows was evaluated on Signal to Noise Ratio (SNR) of filtered ECG. A proposed window function based on the clonal selection algorithm achieved a significantly higher Signal to Noise Ratio (28.567) for filtered ECG signals compared to Hamming, Hanning, and Kaiser windows.

synapsesocial.com/papers/6a992c24ea739e5cccf5b133https://doi.org/10.9790/2834-09551016
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