A Nonfiducial PPG-Based Subject Authentication Approach Using the Statistical Features of DWT-Based Filtered Signals
Joint Authors
Alotaiby, Turky N.
Aljabarti, Fatima
Alotibi, Gaseb
Alshebeili, Saleh A.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-17
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Nowadays, there is a global change in lifestyle that is moving more toward the use of e-services and smart devices which necessitate the verification of user identity.
Different organizations have put into place a range of technologies, hardware, and/or software to authenticate users using fingerprints, iris recognition, and so forth.
However, cost and reliability are significant limitations to the use of such technologies.
This study presents a nonfiducial PPG-based subject authentication system.
In particular, the photoplethysmogram (PPG) signal is first filtered into four signals using the discrete wavelet transform (DWT) and then segmented into frames.
Ten simple statistical features are extracted from the frame of each signal band to compose the feature vector.
Augmenting the feature vector with the same features extracted from the 1st derivative of the corresponding signal is investigated, along with different fusion approaches.
A support vector machine (SVM) classifier is then employed for the purpose of identity authentication.
The proposed authentication system achieved an average authentication accuracy of 99.3% using a 15 sec frame length with the augmented multiband approach.
American Psychological Association (APA)
Alotaiby, Turky N.& Aljabarti, Fatima& Alotibi, Gaseb& Alshebeili, Saleh A.. 2020. A Nonfiducial PPG-Based Subject Authentication Approach Using the Statistical Features of DWT-Based Filtered Signals. Journal of Sensors،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1190644
Modern Language Association (MLA)
Alotaiby, Turky N.…[et al.]. A Nonfiducial PPG-Based Subject Authentication Approach Using the Statistical Features of DWT-Based Filtered Signals. Journal of Sensors No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1190644
American Medical Association (AMA)
Alotaiby, Turky N.& Aljabarti, Fatima& Alotibi, Gaseb& Alshebeili, Saleh A.. A Nonfiducial PPG-Based Subject Authentication Approach Using the Statistical Features of DWT-Based Filtered Signals. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1190644
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1190644