ArticleActa Cardiologica Sinica2021
The Reconstruction of a 12-Lead Electrocardiogram from a Reduced Lead Set Using a Focus Time-Delay Neural Network.
Article in Acta Cardiologica Sinica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- Anti-aliasing-enhanced WaveUNet for clinically reliable 12-lead ECG reconstruction from limited 3-lead input.Medical & biological engineering & computing · 2026Article
- Reconstructing 12-lead ECG from reduced lead sets using an encoder-decoder convolutional neural network.Biomedical signal processing and control · 2025Article
- AI-enhanced reconstruction of the 12-lead electrocardiogram via 3-leads with accurate clinical assessment.NPJ digital medicine · 2024Article
- 12-Lead ECG Reconstruction Based on Data From the First Limb Lead.Cardiovascular engineering and technology · 2024Article
- Wearable 12-Lead ECG Acquisition Using a Novel Deep Learning Approach from Frank or EASI Leads with Clinical Validation.Bioengineering (Basel, Switzerland) · 2024Article
- Design and technical validation to generate a synthetic 12-lead electrocardiogram dataset to promote artificial intelligence research.Health information science and systems · 2023Article
- Using a Smartwatch to Record Precordial Electrocardiograms: A Validation Study.Sensors (Basel, Switzerland) · 2023Article
- Exercise Test for Patients with Long QT Syndrome.Acta Cardiologica Sinica · 2022Review
- Feasibility and Reliability of Smartwatch to Obtain Precordial Lead Electrocardiogram Recordings.Sensors (Basel, Switzerland) · 2022Article
- A novel method for 12-lead ECG reconstruction.Conference record. Asilomar Conference on Signals, Systems & ComputersArticle
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 12-lead electrocardiogram (ECG) is the gold-standard ECG method used by cardiologists. However, accurate electrode placement is difficult and time consuming, and can lead to incorrect interpretation.
objectivesThe objective of this study was to accurately reconstruct a full 12-lead ECG from a reduced lead set.
methodsFive-electrode placement was used to generate leads I, II, III, aVL, aVR, aVF and V2. These seven leads served as inputs to the focus time-delay neural network (FTDNN) which derived the remaining five precordial leads (V1, V3-V6). An online archived medical database containing 549 cases of ECG recordings was used to train, validate and test the FTDNN.
resultsAfter removing outliers, the reconstructed leads exhibited correlation values of between 0.8609 and 0.9678 as well as low root mean square error values of between 123 μV and 245 μV across all cases, for both healthy controls and cardiovascular disease subgroups except the bundle branch block disease subgroup. The results of the FTDNN method compared favourably to those of prior lead reconstruction methods.
conclusionsA standard 12-lead ECG was successfully reconstructed with high quantitative correlations from a reduced lead set using only five electrodes, of which four were placed on the limbs. Less reliance on precordial leads will aid in the reduction of electrode placement errors, ultimately improving ECG lead accuracy and reduce the number of cases that are incorrectly diagnosed.
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