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1 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | BII | Atrioventricular block 2nd degree |
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1 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | R | Right bundle branch block beat |
|
2 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | B | Ventricular bigeminy |
|
3 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | BIII | Atrioventricular block 3rd degree |
|
3 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | P | Paced rhythm |
|
4 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
|
5 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
|
5 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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6 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | NOD | Nodal rhythm |
|
6 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | J | Nodal beat |
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7 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | NOD | Nodal rhythm |
|
7 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | J | Nodal beat |
|
7 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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8 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFL | Atrial flutter |
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8 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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9 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | E | Ventricular escape beat |
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9 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
|
9 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | SVTA | Supraventricular tachyarrhythmia |
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10 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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11 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | SVTA | Supraventricular tachyarrhythmia |
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12 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | PREX | Pre-excitation |
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13 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | BII | Atrioventricular block 2nd degree |
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13 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | R | Right bundle branch block beat |
|
14 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | B | Ventricular bigeminy |
|
14 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
|
15 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | NOD | Nodal rhythm |
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15 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | J | Nodal beat |
|
16 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
|
17 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
|
18 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
|
19 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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19 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | P | Paced rhythm |
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20 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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21 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | L | Left bundle branch block beat |
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21 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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22 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | L | Left bundle branch block beat |
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22 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | BI | Atrioventricular block 1st degree |
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23 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | a | Aberrated atrial premature beat |
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24 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | NA | Sinus arrhythmia |
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25 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | VP | Ventricular pair |
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25 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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26 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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26 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | R | Right bundle branch block beat |
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27 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | B | Ventricular bigeminy |
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27 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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27 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | T | Ventricular trigeminy |
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28 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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28 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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29 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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29 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | T | Ventricular trigeminy |
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30 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | IVR | Idioventricular rhythm |
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30 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | F | Fusion of ventricular and normal beat |
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30 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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31 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | F | Fusion of ventricular and normal beat |
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31 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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32 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | F | Fusion of ventricular and normal beat |
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32 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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33 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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33 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | VFL | Ventricular flutter |
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34 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | R | Right bundle branch block beat |
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35 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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35 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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36 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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36 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | L | Left bundle branch block beat |
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38 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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38 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFL | Atrial flutter |
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39 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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39 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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40 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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40 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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41 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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41 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | L | Left bundle branch block beat |
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41 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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42 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | V | Ventricular premature beat |
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43 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | SVTA | Supraventricular tachyarrhythmia |
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43 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | A | Atrial premature beat |
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44 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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45 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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46 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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47 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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48 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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49 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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50 | The Brno University of Technology ECG Signal Database with Annotations of P Wave (BUT PDB) is a specialized ECG dataset created by the cardiology team at the Department of Biomedical Engineering, Brno University of Technology. It comprises 50 two-minute, two-lead ECG recordings featuring various pathologies. These ECGs were carefully selected from three established databases: the MIT-BIH Arrhythmia Database, the MIT-BIH Supraventricular Arrhythmia Database, and the Long Term AF Database. A unique feature of this dataset is the manual annotation of P wave positions by two ECG experts across all 50 records. Additionally, each record includes annotations for QRS complex positions and types (from the original databases), as well as the dominant diagnosis or pathology present. This database was specifically designed to facilitate the development, evaluation, and objective comparison of P wave detection algorithms in ECG signal processing. | AFIB | Atrial fibrillation |
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