A study based on Fiducial and Non-Fiducial methods via applying the Short Time Fourier Transform and Histograms of QRS Features for ECG based human identification
2 McMaster School of Biomedical Engineering, McMaster University, Canada
Received: 30-Jan-2023, Manuscript No. 84320; Editor assigned: 02-Jan-2023, Pre QC No. 84320; Accepted Date: Dec 30, 2022 ; Reviewed: 16-Jan-2023 QC No. 84320; Revised: 23-Jan-2023, Manuscript No. 84320; Published: 30-Jan-2023, DOI: 10.24105/ejbfi.2023.19.1.149-166
This open-access article is distributed under the terms of the Creative Commons Attribution Non-Commercial License (CC BY-NC) (http://creativecommons.org/licenses/by-nc/4.0/), which permits reuse, distribution and reproduction of the article, provided that the original work is properly cited and the reuse is restricted to noncommercial purposes. For commercial reuse, contact submissions@ejbi.org
Abstract
Biometric systems have been a subject of considerable research interest for human identification. In this paper, we present both fiducial and non-fiducial methods for individual identification. In both methods, we randomize the process of data selection, and we use different referencing and testing windows to examine the stability of our methods. Our identification system randomly selects both the referencing and testing data by utilizing multiple data windows from the full ECG record. The first identification method is based on extracting multiple bivariate histograms of fiducial QRS features. Namely, these features are the amplitude and slope differences between the Q, R and S peaks. Then, we find the Euclidean distance between these multiple histograms for classification purposes. Additionally, we propose an algorithm which automatically locates and segments QRS waves using Short Time Fourier Transform (STFT) and single feature-based classification process. The second non-fiducial identification method is based on finding the magnitudes of the frequency components from the ECG data
Retraction Note
The article entitled “A Study Based on Fiducial and Non-Fiducial Methods via Applying the Short Time Fourier Transform and Histograms of QRS Features for ECG Based Human Identification” has been accepted for publication in the European Journal for Biomedical Informatics considering the statements provided in the article as personal opinion of the author which was found not having any conflict or biasness towards anything. As the article was a perspective one, information provided by the author was considered as an opinion to be expressed through publication. Publisher took decision to make the article online solely based on the reviewers suggestion which considered the article not but a personal opinion of the author. However, it is found that the author have some personal concerns and issues, therefore, being retracted from the journal.