• Corpus ID: 35674408

ECG Authentication for Mobile Devices by Juan

  title={ECG Authentication for Mobile Devices by Juan},
  author={Sebastian Arteaga Falconi},

Dense Deep Neural Network Architecture for Keystroke Dynamics Authentication in Mobile Phone

It is found that the propose deep learning – dense neural network authentication scheme is more robust than the classical algorithms and has the potential to be fully implemented on smartphone to improve the security system of the mobile smartphone touch screen devices.



Wireless, ultrasonic personal health monitoring system

  • USA Patent US 8301232
  • 2012

Multimodal Biometric Person Authentication : A Review

An overview of some performance parameters and error rates for biometric person authentication systems is presented, and the importance of information fusion in multi-biometric approach is considered.

Accuracy performance analysis of multimodal biometrics

  • S. DahelQ. X. Dominquez
  • Computer Science
    IEEE Systems, Man and Cybernetics SocietyInformation Assurance Workshop, 2003.
  • 2003
The purpose of the study is to provide a theoretical evaluation for the false acceptance and the false rejection rates to improve the accuracy as well as the convenience of biometric applications.

ECG analysis: a new approach in human identification

A new approach in human identification is investigated, using a standard 12-lead electrocardiogram, recorded during rest, to identify a person in a predetermined group by features extracted from one lead only.

ECG to identify individuals

Evaluation of Electrocardiogram for Biometric Authentication

The EER results of the combined systems prove that the ECG has an excellent source of supplementary information to a multibiometric system, despite it shows moderate performance in a unimodal framework.

An introduction to biometric recognition

A brief overview of the field of biometrics is given and some of its advantages, disadvantages, strengths, limitations, and related privacy concerns are summarized.

Identifying Individuals Using Eigenbeat Features of Electrocardiogram

The result demonstrates that the derived eigenbeat features from proposed ECG characterization perform better and achieve the recognition accuracy of 91.42% and 95.55% on the subjects of MIT-BIH Arrhythmia database and IIT(BHU) database, respectively.

Removal of Base-Line Wander and Power-Line Interference from the ECG by an Efficient FIR Filter with a Reduced Number of Taps

Linear phase filtering is proposed for the removal of baseline wander and power-line frequency components in electrocardiograms with a considerably reduced number of impulse response coefficients.

BioID: A Multimodal Biometric Identification System

This article goes into detail about the BioID system functions, explaining the data acquisition and preprocessing techniques for voice, facial, and lip imagery data and the classification principles used for optical features and the sensor fusion options.