The electrocardiogram (ECG) is an emerging biometric modality that has seen about 13 years of development in peer-reviewed literature, and as such deserves a systematic review and discussion of the associated methods and findings. In this paper, we review most of the techniques that have been applied to the use of the electrocardiogram for biometric recognition. In particular, we categorize the methodologies based on the features and the classification schemes. Finally, a comparative analysis of the authentication performance of a few of the ECG biometric systems is presented, using our inhouse database. The comparative study includes the cases where training and testing data come from the same and different sessions (days). The authentication results show that most of the algorithms that have been proposed for ECG-based biometrics perform well when the training and testing data come from the same session. However, when training and testing data come from different sessions, a performance degradation occurs. Multiple training sessions were incorporated to diminish the loss in performance. That notwithstanding, only a few of the proposed ECG recognition algorithms appear to be able to support performance improvement due to multiple training sessions. Only three of these algorithms produced equal error rates (EERs) in the single digits, including an EER of 5.5% using a method proposed by us.

ECG Biometric Recognition: A Comparative Analysis

The long-term ST database is the result of a multinational research effort. The goal was to develop a challenging and realistic research resource for development and evaluation of automated systems to detect transient ST segment changes in electrocardiograms and for supporting basic research into the mechanisms and dynamics of transient myocardial ischaemia. Twenty-four hour ambulatory ECG records were selected from routine clinical practice settings in the USA and Europe, between 1994 and 2000, on the basis of occurrence of ischaemic and non-ischaemic ST segment changes. Human expert annotators used newly developed annotation protocols and a specially developed interactive graphic editor tool (SEMIA) that supported paperless editing of annotations and facilitated international co-operation via the Internet. The database contains 86 two- and three-channel 24 h annotated ambulatory records from 80 patients and is stored on DVD-ROMs. The database annotation files contain ST segment annotations of transient ischaemic (1155) and heart-rate related ST episodes and annotations of non-ischaemic ST segment events related to postural changes and conduction abnormalities. The database is intended to complement the European Society of Cardiology ST-T database and the MIT-BIH and AHA arrhythmia databases. It provides a comprehensive representation of 'real-world' data, with numerous examples of transient ischaemic and non-ischaemic ST segment changes, arrhythmias, conduction abnormalities, axis shifts, noise and artifacts.

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Long-term ST database: a reference for the development and evaluation of automated ischaemia detectors and for the study of the dynamics of myocardial ischaemia.

http://ecg.mit.edu/george/publications/jager-cbr-1998.pdf

Detection of transient ST segment episodes during ambulatory ECG monitoring

A new approach to early diagnosis of congestive heart failure disease by using HilbertHuang transform

http://ecg.mit.edu/george/publications/costa-isce-2003.pdf

PhysioNet: An NIH Research Resource for Complex signals

Presents the Long Term ST Database, a collection of eighty 24-hour two and three lead ECG records from ambulatory subjects with transient ST segment abnormalities. The database provides a comprehensive standard research resource for quantitatively assessing the performance of automated detectors of transient ischemia, and for supporting basic research into the mechanisms and dynamics of transient ischemia. Records of the database contain annotated significant transient ischemic ST episodes, non-ischemic ST episodes caused by heart rate related changes, non-ischemic ST events due to axis shifts or QRS conduction changes, and individual QRS and rhythm annotations, all made by human experts.

/pdf/the-long-term-st-database-a-research-resource-for-algorithm-2cmwz17vi7.pdf

The Long-Term ST database: a research resource for algorithm development and physiologic studies of transient myocardial ischemia

The authors have begun to develop a new annotated long term ambulatory ST-T database. The aim of the database is to be a reference set containing a number of well documented ischemic ST episodes, axis-related non-ischemic ST episodes, episodes of slow ST level drift and mixed episodes to support development and evaluation of detectors capable of accurate differentiation of ischemic and non-ischemic ST events, as well as basic research into mechanisms and dynamics of ischemia. The authors discuss selection criteria, define the events of interest, and describe the annotation procedure.

/pdf/development-of-a-long-term-database-for-assessing-the-2sbr6nlntb.pdf

M. Zabukovec

Papers

The Long-Term ST database: a research resource for algorithm development and physiologic studies of transient myocardial ischemia

Development of a long term database for assessing the performance of transient ischemia detectors