ECG-Based Biometric Recognition: A Survey of Methods and Databases

This work presents a comprehensive and chronologically ordered survey of existing studies and data sources on Electrocardiogram (ECG) based biometric recognition systems. This survey is organized in terms of the two main goals pursued in it: first, a description of the main ECG features and recognition techniques used in the existing literature, including a comprehensive compilation of references; second, a survey of the ECG databases available and used by the referenced studies. The most relevant characteristics of the databases are identified, and a comprehensive compilation of databases is given. To date, no other work has presented such a complete overview of both studies and data sources for ECG-based biometric recognition. Readers interested in the subject can obtain an understanding of the state of the art, easily identifying specific key papers by using different criteria, and become aware of the databases where they can test their novel algorithms.

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Publication Details

Journal
Archivo Digital UPM (Universidad Politécnica de Madrid)
Published
2025-03-17
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
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article

ECG-Based Biometric Recognition: A Survey of Methods and Databases

David Luengo García, David Meltzer Camino
Archivo Digital UPM (Universidad Politécnica de Madrid)
ECG Monitoring and Analysis
article

ECG-Based Biometric Recognition: A Survey of Methods and Databases

David Luengo García, David Meltzer Camino
article en

Abstract

This work presents a comprehensive and chronologically ordered survey of existing studies and data sources on Electrocardiogram (ECG) based biometric recognition systems. This survey is organized in terms of the two main goals pursued in it: first, a description of the main ECG features and recognition techniques used in the existing literature, including a comprehensive compilation of references; second, a survey of the ECG databases available and used by the referenced studies. The most relevant characteristics of the databases are identified, and a comprehensive compilation of databases is given. To date, no other work has presented such a complete overview of both studies and data sources for ECG-based biometric recognition. Readers interested in the subject can obtain an understanding of the state of the art, easily identifying specific key papers by using different criteria, and become aware of the databases where they can test their novel algorithms.

Archivo Digital UPM (Universidad Politécnica de Madrid)
Quality Education
Openalex Percentile: Top 24%
ECG Monitoring and Analysis
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