Artikel
Open Access
Classification of Bundle Branch Blocks with QRS Templates Extracted from 12-lead ECGs
-
Hannes Welle
Veröffentlicht/Copyright:
9. Oktober 2021
Abstract
Being non-invasive, cheap and widely available, the 12-lead electrocardiogram (ECG) is a standard method to assess cardiac function. Still, its reliable interpretation requires specialized knowledge and experience, rendering a second opinion valuable. We evaluated the performance of machine learning based classification of 11,705 healthy and bundle branch block 12-lead ECGs from 3 open databases. For each lead of the ECG signal, a representative QRS-complex template was extracted automatically. Principal component analysis (PCA) was applied to the concatenated, normalized and rescaled QRS signals to reduce their dimensionality. Multilayer perceptron and support-vector machine classifiers were trained using the principal components of weighted and non-weighted QRS template signals as input data. Classifiers achieved F1 scores between 0.92 and 0.96 on the test set for different input configurations. Anomaly based weighting slightly improved the performance of the classifiers. Neither class-wise PCA for feature extraction nor adding information on sex, gender and electrical heart axis to the input data yielded considerable improvement of the F1 scores. The achieved classification accuracy is similar to deep learning classifier performances and should generalize robustly to other ECG datasets. Our results suggest that this simple and well interpretable approach based on morphological signal characteristics is suitable for automatically and non-invasively identifying bundle branch block pathologies in clinical or smart electronics contexts.
Published Online: 2021-10-09
Published in Print: 2021-10-01
© 2021 The Author(s), published by Walter de Gruyter GmbH, Berlin/Boston
This work is licensed under the Creative Commons Attribution 4.0 International License.
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Schlagwörter für diesen Artikel
12 lead ECG;
QRS;
classification;
bundle branch block;
preprocessing;
machine learning
Creative Commons
BY 4.0
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- Differentiation of Mild Cognitive Impairment Conditions in MR Images using Fractional order Jacobi Fourier Moment Features
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- Protein Adsorbate Biohybrids and Sequential Hystallosteric Protein Adsorption
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- Development and validation of a test facility for pivotal characterization of glaucoma drainage devices
- 10.1515/cdbme-2021-2191
- Influence of pedicle screw thread width and recovery time after surgery on fixation strength
- Cross Data Set Generalization of Ultrasound Image Augmentation using Representation Learning: A Case Study
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- Classification of Alzheimer Condition using MR Brain Images and Inception-Residual Network Model
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- Investigation of biocompatible Parylene as triboelectric layer for wearable energy harvesting
- 10.1515/cdbme-2021-2198
- Needle insertion planning for obstacle avoidance in robotic biopsy
- 10.1515/cdbme-2021-2200
- 10.1515/cdbme-2021-2201
- 10.1515/cdbme-2021-2202
- Clinical case study in acoustic-kinetic joint analysis: Synchronization and Evaluation of kinetic measurement data in AEA (Acoustic Emission Analysis) based diagnosis of arthritic knee joint defects
- Insights of posture dependent pressure characteristics in five rats
- Selective electrical stimulation with current-field modulation
- 10.1515/cdbme-2021-2206
- Automatic Hypercube Acquisition with high spatial and spectral resolution using a HSI Linescan Camera
- 10.1515/cdbme-2021-2208
- 10.1515/cdbme-2021-2209
- 10.1515/cdbme-2021-2210
- 10.1515/cdbme-2021-2211
- 10.1515/cdbme-2021-2212
- Angiogenesis by BMP-2-PDLLA-Biohybrids in Co-Culture with Osteoblasts and Endothelia
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- Utilizing direct-initiation of thiols for photoinitiator-free stereolithographic 3D printing of mechanically stable scaffolds
- Vitrectome with Integrated LED Illumination: Development and Testing
- A Step towards Neuro-Steered Hearing Aids: Integrated Portable Setup for Time- Synchronized Acoustic Stimuli Presentation and EEG Recording
- In vitro validation of a non-invasive continuous blood pressure measurement method for the perioperative application
- 10.1515/cdbme-2021-2220
- Analysis of uterine electromyography signals using time-frequency based topological features for detection of preterm birth
- Separating ventricular activity in thoracic EIT using 4D image-based FEM simulations
- Evaluation of Streptococcus oralis adhesion and biofilm formation on laser-processed titanium
- Comparison of Deep Learning Algorithms for Semantic Segmentation of Ultrasound Thyroid Nodules
- Investigation of an Active Measurement Method to Detect Inertial Cavitation and the Presence of Potential Drug Carriers
- 10.1515/cdbme-2021-2226
- 10.1515/cdbme-2021-2227
- Correlation of Black Blood MRI with Image- Based Blood Flow Simulations in Intracranial Aneurysms
- 10.1515/cdbme-2021-2229
- ForeSight Approach to improve Privacy and Security in the Smart Living Domain
