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September 10, 2013Journal of Medical Engineering & Technology

The adaptive wavelet approach successfully detected R-peak variations under various ECG signal conditions including noise and baseband wandering.

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Population

ECG signals

Design

Other

Authors

TNT. R. Gopalakrishnan NairMAM. Asharani

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Overview

May aid noisy ECG monitoring; leaves open prospective clinical validation before adoption.

Structured PICO

P
Population
ECG signals
I
Intervention
Adaptive wavelet approach for R-signal identification
O
Outcome
R-peak detection under noise, baseband wandering, and temporal variationssurrogate

An adaptive wavelet technique can automate and improve the accuracy of R-peak detection in ECG signals under noisy conditions.

Cite This Study

Nair et al. (2013) studied this question.

synapsesocial.com/papers/6a83e8c7403dcf0d873c264fhttps://doi.org/10.3109/03091902.2013.828105
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1R peak detection in electrocardiogram signal based on an optimal combination of wavelet transform, Hilbert transform, and adaptive thresholding2011 · 82 citations
  2. 2R-Peak Identification in ECG Signals using Pattern-Adapted Wavelet Technique2021 · 37 citations
  3. 3Detection of R- Peaks in Electrocardiogram based onWavelet Transform andWavelet Approximation2022 · 1 citations
  4. 4A robust continuous wavelet transform (CWT) based for R-peak detection method of ECG2023 · 5 citations
  5. 5R-Peak Detection Using Wavelet Scattering Transform for Pre-Term Infant ECG Dataset2024