ArticleBioengineering (Basel, Switzerland)2020
An Analysis of the Effects of Noisy Electrocardiogram Signal on Heartbeat Detection Performance.
Article in Bioengineering (Basel, Switzerland), 2020. 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, 43 citations in OpenAlex.
- How the Level of Noise Affects Temporal Accuracy of a QRS Detector-Case Study.Sensors (Basel, Switzerland) · 2025Article
- Monitoring long-term cardiac activity with contactless radio frequency signals.Nature communications · 2024Article
- QRS Detector Performance Evaluation Aware of Temporal Accuracy and Presence of Noise.Sensors (Basel, Switzerland) · 2024Article
- Validity and Efficacy of the Elite HRV Smartphone Application during Slow-Paced Breathing.Sensors (Basel, Switzerland) · 2023Article
- Variational Autoencoders for Biomedical Signal Morphology Clustering and Noise Detection.IEEE journal of biomedical and health informatics · 2023Article
- A two-step pre-processing tool to remove Gaussian and ectopic noise for heart rate variability analysis.Scientific reports · 2022Article
- Validity of the Polar H10 Sensor for Heart Rate Variability Analysis during Resting State and Incremental Exercise in Recreational Men and Women.Sensors (Basel, Switzerland) · 2022Article
- Noise-Reducing Fabric Electrode for ECG Measurement.Sensors (Basel, Switzerland) · 2021Article
- Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Heartbeat detection for ambulatory cardiac monitoring is more challenging as the level of noise and artefacts induced by daily-life activities are considerably higher than monitoring in a hospital setting. It is valuable to understand the relationship between the characteristics of electrocardiogram (ECG) noises and the beat detection performance in the cardiac monitoring system. For this purpose, three well-known algorithms for the beat detection process were re-implemented. The beat detection algorithms were validated using two types of ambulatory datasets, which were the ECG signal from the MIT-BIH Arrhythmia Database and the simulated noise-contaminated ECG signal with different intensities of baseline wander (BW), muscle artefact (MA) and electrode motion (EM) artefact from the MIT-BIH Noise Stress Test Database. The findings showed that signals contaminated with noise and artefacts decreased the potential of beat detection in ambulatory signal with the poorest performance noted for ECG signal affected by the EM artefacts. In conclusion, none of the algorithms was able to detect all QRS complexes without any false detection at the highest level of noise. The EM noise influenced the beat detection performance the most in comparison to the MA and BW noises that resulted in the highest number of misdetections and false detections.
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