Multimodal biometric system combining ECG and sound signals

Bugdoł, Marcin; Mitas, Andrzej W.

doi:10.1016/j.patrec.2013.11.014

Cited by 52 publications

(26 citation statements)

References 27 publications

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“…By capturing human physiological or behavioral characteristics, wearable electronic sensors in biomonitoring and biometric systems carry significant importance in daily life such as in personalized health monitoring and assessment, disease diagnosis, entrance and mobile control, secured financial transactions, and others . Detected from human skin, the arterial pulse wave and throat sound are typical physiological and behavioral signals acquired for human characterization . To date, a majority of the wearable pressure sensors are based on force‐induced changes in capacitance, piezoelectricity, and resistivity, with various micro/nano architectures .…”

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confidence: 99%

“…To date, a majority of the wearable pressure sensors are based on force‐induced changes in capacitance, piezoelectricity, and resistivity, with various micro/nano architectures . Despite the potential and high performance, widespread usage of these techniques is possibly limited by structure complexity, fabrication of high‐quality materials, reliance on external power source, and the infeasibility of response to high‐frequency dynamic pressure, such as sound recovery from throat vibrations that lies in a frequency range of normally higher than 500 Hz …”

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confidence: 99%

“…Biometrics, the reliance on physiological or behavioral characteristics that are unique and exclusive representing features of the genuine owner, has rendered a possible solution to this problem . However, all of the current biometrics authentication systems are unimodal, relying on a single source of information to establish an identity, and have limitations like noise in sensed data, intraclass variation, interclass similarity, and nonuniversality and spoof attack . Thus, a desired identifier based on multiple physiological or behavioral characteristics would be preferred to add multilayers of strong security to current authentication systems without major modification.…”

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confidence: 99%

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Eardrum‐Inspired Active Sensors for Self‐Powered Cardiovascular System Characterization and Throat‐Attached Anti‐Interference Voice Recognition

et al. 2015

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The first bionic membrane sensor based on triboelectrification is reported for self-powered physiological and behavioral measurements such as local internal body pressures for non-invasive human health assessment. The sensor can also be for self-powered anti-interference throat voice recording and recognition, as well as high-accuracy multimodal biometric authentication, thus potentially expanding the scope of applications in self-powered wearable medical/health monitoring, interactive input/control devices as well as accurate, reliable, and less intrusive biometric authentication systems.

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Eardrum‐Inspired Active Sensors for Self‐Powered Cardiovascular System Characterization and Throat‐Attached Anti‐Interference Voice Recognition

et al. 2015

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“…The ECG signal has also been combined with popular physiological biometrics such as face [24], fingerprint [36], palmprint [37] and also with sound [11].…”

Section: Prior Workmentioning

confidence: 99%

“…Therefore, it has strong credentials to successfully address the security and privacy issues of an individual [10]. Other papers referring to ECG in identity verification consider it as an emerging biometric modality [11].…”

Section: Introductionmentioning

confidence: 99%

A novel biometric authentication approach using ECG and EMG signals

Belgacem

Fournier

Naït‐Ali

et al. 2015

Journal of Medical Engineering & Technology

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Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics' measures, it delivers proof of subject's being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals' authentication.

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