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Compression of Steganographed PPG Signal With Guaranteed Reconstruction Quality Based on Optimum Truncation of Singular Values and ASCII Character Encoding.

Authors :
Mukhopadhyay, Sourav Kumar
Ahmad, M. Omair
Swamy, M.N.S.
Source :
IEEE Transactions on Biomedical Engineering. Jul2019, Vol. 66 Issue 7, p2081-2090. 10p.
Publication Year :
2019

Abstract

Objective: Extraction and analysis of various clinically significant features of photoplethysmogram (PPG) signals for monitoring several physiological parameters, as well as for biometric authentication have become important areas of research in recent years. However, PPG signal compression; particularly quality-guaranteed compression, and steganography of patient's secret information is still lagging behind. Method: This paper presents a robust, reliable and highly efficient singular value decomposition and lossless ASCII character encoding (LL-ACE)-based quality-guaranteed PPG compression algorithm. This algorithm cannot only be used to compress PPG signals, but also do so for steganographed PPG signals that include the patient information. Result and conclusion: It is worth mentioning that such an algorithm is being proposed for the first time to compress steganographed PPG signals. The algorithm is tested on PPG signals collected from four different databases, and its performance is assessed using both quantitative and qualitative measures. The proposed steganographed PPG compression algorithm provides a compression ratio that is much higher than that provided by other algorithms that are designed to compress the PPG signals only. Significance: first, the clinical quality of the reconstructed PPG signal can be controlled precisely, second, the patient's personal information is restored with no errors, third, high compression ratio, and fourth, the PPG signal reconstruction error is neither dependent on the steganographic operation nor on the size of the patient information data. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00189294
Volume :
66
Issue :
7
Database :
Academic Search Index
Journal :
IEEE Transactions on Biomedical Engineering
Publication Type :
Academic Journal
Accession number :
137215251
Full Text :
https://doi.org/10.1109/TBME.2018.2883396