One Lead ECG Based Personal Identification with Feature Subspace Ensembles

Silva, Hugo; Gambôa, Hugo; Fred, Ana

doi:10.1007/978-3-540-73499-4_58

Cited by 36 publications

(27 citation statements)

References 24 publications

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“…The former describes approaches based on reference points in the signals and/or specific features derived from them (such as the P-QRS-T complexes illustrated in Fig.1(a)) [13], [14], [15], [16]. The latter generally refers to techniques that rely on intrinsic information from the ECG signals, without having any particular cues within the signal as a reference [17], [18], [19], [20].…”

Section: Ecg Biometric Systemsmentioning

confidence: 99%

ECG biometrics: A template selection approach

Lourenço

Carreiras

Silva

et al. 2014

2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

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Section: Ecg Biometric Systemsmentioning

confidence: 99%

ECG biometrics: A template selection approach

Lourenço

Carreiras

Silva

et al. 2014

2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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“…Instead, features like wavelet coefficients [12] and autocorrelation coefficients [16] are utilized. The hybrid methods combine both fiducial-based features and non fiducialbased features [25], [26].…”

mentioning

confidence: 99%

ECG Biometric Recognition: A Comparative Analysis

Odinaka

Lai

Kaplan

et al. 2012

IEEE Trans.Inform.Forensic Secur.

307

196

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The electrocardiogram (ECG) is an emerging biometric modality that has seen about thirteen 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 in-house 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 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. 2 equal error rates (EERs) in the single digits, including an EER of 5.5% using a method proposed by us.

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“…In the reference [7], the feature selection algorithm was used and it could improve the low recognition rate and reduce data dimensions, it also add FSE and k-NN. algorithm to improve the final recognition.…”

Section: Analysis Among Different Identity Authentication Based Onmentioning

confidence: 99%

Biometric Electrocardiogram Card for Access Control System

Zeng

Tseng

Zhao

et al. 2011

2011 Fifth International Conference on Genetic and Evolutionary Computing

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With the rapid development of access control system based on biometric technologies, the conventional identification exposed more and more weakness while they are easy to be counterfeited and imitated. In this paper, we bring the access control systems with electrocardiogram identification into a practical application. Moreover, a new prompt based ECG algorithm are proposed to seek a more secure and accurate identification. In our evaluation, a hardware board were designed to verified its feasibility, then the analysis and comparison among various biometric identification and previous ECG identification researches were further disused as well. The result shown our proposed design could provide a more secure, low cost and convenient identification for access control system.

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One Lead ECG Based Personal Identification with Feature Subspace Ensembles

Cited by 36 publications

References 24 publications

ECG biometrics: A template selection approach

ECG biometrics: A template selection approach

ECG Biometric Recognition: A Comparative Analysis

Biometric Electrocardiogram Card for Access Control System

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