Integrating Analytic and Appearance Attributes for Human Identification from ECG Signals

2006 ◽  
Author(s):  
Yongjin Wang ◽  
Konstantinos N. Plataniotis ◽  
Dimitrios Hatzinakos
Keyword(s):  
Human Identification ◽  
Ecg Signals

scholarly journals Electrocardiograph Identification Using Hybrid Quantization Sparse Matrix and Multi-Dimensional Approaches

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4138
Author(s):  
Kuo-Kun Tseng ◽  
Jiao Lo ◽  
Chih-Cheng Chen ◽  
Shu-Yi Tu ◽  
Cheng-Fu Yang
Keyword(s):  
Matrix Method ◽  
Sparse Matrix ◽  
Human Identification ◽  
Recognition Algorithm ◽  
Blood Oxygen ◽  
Dimensional Approach ◽  
Identification Rate ◽  
Ecg Signals ◽  
Biometric Security ◽  
Biometric Information

Electrocardiograph (ECG) technology is vital for biometric security, and blood oxygen is essential for human survival. In this study, ECG signals and blood oxygen levels are combined to increase the accuracy and efficiency of human identification and verification. The proposed scheme maps the combined biometric information to a matrix and quantifies it as a sparse matrix for reorganizational purposes. Experimental results confirm a much better identification rate than in other ECG-related identification studies. The literature shows no research in human identification using the quantization sparse matrix method with ECG and blood oxygen data combined. We propose a multi-dimensional approach that can improve the accuracy and reduce the complexity of the recognition algorithm.

An approach for human identification based on time and frequency domain features extracted from ECG signals

2011 ◽  
Author(s):  
Shaikh Anowarul Fattah ◽  
Abu Shafin Mohammad Mahdee Jameel ◽  
Rajib Goswami ◽  
Sudip Kumar Saha ◽  
Nitu Syed ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Human Identification ◽  
Ecg Signals

Human Identification From ECG Signals Via Sparse Representation of Local Segments

2013 ◽  
Vol 20 (10) ◽  
pp. 937-940 ◽  
Author(s):  
Jin Wang ◽  
Mary She ◽  
Saeid Nahavandi ◽  
Abbas Kouzani
Keyword(s):  
Sparse Representation ◽  
Human Identification ◽  
Ecg Signals

scholarly journals Sparse Matrix for ECG Identification with Two-Lead Features

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Kuo-Kun Tseng ◽  
Jiao Luo ◽  
Robert Hegarty ◽  
Wenmin Wang ◽  
Dong Haiting
Keyword(s):  
Feature Extraction ◽  
Matrix Method ◽  
Sparse Matrix ◽  
Human Identification ◽  
Two Dimensional ◽  
Ecg Signals ◽  
Biometric Security ◽  
Dimensional Matrix ◽  
The Matrix ◽  
Sparse Matrix Techniques

Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

scholarly journals Human Identification Using Compressed ECG Signals

2015 ◽  
Vol 39 (11) ◽  
Author(s):  
Carmen Camara ◽  
Pedro Peris-Lopez ◽  
Juan E. Tapiador
Keyword(s):  
Human Identification ◽  
Ecg Signals

Human identification using finger vein and ECG signals

2019 ◽  
Vol 332 ◽  
pp. 111-118 ◽  
Author(s):  
Kun Su ◽  
Gongping Yang ◽  
Bo Wu ◽  
Lu Yang ◽  
Dunfeng Li ◽  
...  
Keyword(s):  
Human Identification ◽  
Ecg Signals ◽  
Finger Vein

scholarly journals ECG signals for human identification based on fiducial and non-fiducial approaches

2020 ◽  
Vol 10 (47) ◽  
pp. 89-95
Author(s):  
Anwar E. Ibrahim ◽  
Salah Abdel-Mageid ◽  
Nadra Nada ◽  
Marwa A. Elshahed
Keyword(s):  
Human Identification ◽  
Ecg Signals
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