ArticleBiomedical engineering letters2019
Efficient QRS complex detection algorithm based on Fast Fourier Transform.
Article in Biomedical engineering letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A reproducible benchmark of QRS detection algorithms across diverse ECG datasets and noise conditions.Scientific reports · 2026Article
- Preprocessing and Denoising Techniques for Electrocardiography and Magnetocardiography: A Review.Bioengineering (Basel, Switzerland) · 2024Review
- Peak detection in intracranial pressure signal waveforms: a comparative study.Biomedical engineering online · 2024Article
- Detection of left ventricular systolic dysfunction from single-lead electrocardiography adapted for portable and wearable devices.NPJ digital medicine · 2023Article
- A Deep Learning Architecture Using 3D Vectorcardiogram to Detect R-Peaks in ECG with Enhanced Precision.Sensors (Basel, Switzerland) · 2023Article
- Improving R Peak Detection in ECG Signal Using Dynamic Mode Selected Energy and Adaptive Window Sizing Algorithm with Decision Tree Algorithm.Sensors (Basel, Switzerland) · 2021Article
- Hidden Markov model-based heartbeat detector using electrocardiogram and arterial pressure signals.Biomedical engineering letters · 2021Article
- Cloud based ensemble machine learning approach for smart detection of epileptic seizures using higher order spectral analysis.Physical and engineering sciences in medicine · 2021Article
- Area efficient folded undecimator based ECG detector.Scientific reports · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An ECG signal, generally filled with noise, when de-noised, enables a physician to effectively determine and predict the condition and health of the heart. This paper aims to address the issue of denoising a noisy ECG signal using the Fast Fourier Transform based bandpass filter. Multi-stage adaptive peak detection is then applied to identify the R-peak in the QRS complex of the ECG signal. The result of test simulations using the MIT/BIH Arrhythmia database shows high sensitivity and positive predictivity (P
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Registered trials
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