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Compression of Bio-Signals Using Block-Based Haar Wavelet Transform and COVIDOA
Faculty
Computer Science
Year:
2023
Type of Publication:
ZU Hosted
Pages:
1-15
Authors:
Khalied Mohamed Hosny
Staff Zu Site
Abstract In Staff Site
Journal:
Bioengineering MDPI
Volume:
10
Keywords :
Compression , Bio-Signals Using Block-Based Haar Wavelet
Abstract:
Background: Bio-signals are the essential data that smart healthcare systems require for diagnosing and treating common diseases. However, the amount of these signals that need to be processed and analyzed by healthcare systems is huge. Dealing with such a vast amount of data presents difficulties, such as the need for high storage and transmission capabilities. In addition, retaining the most useful clinical information in the input signal is essential while applying compression. Methods: This paper proposes an algorithm for the efficient compression of bio-signals for IoMT applications. This algorithm extracts the features of the input signal using block-based HWT and then selects the most important features for reconstruction using the novel COVIDOA. Results: We utilized two different public datasets for evaluation: MIT-BIH arrhythmia and EEG Motor Movement/Imagery, for ECG and EEG signals, respectively. The proposed algorithm’s average values for CR, PRD, NCC, and QS are 18.06, 0.2470, 0.9467, and 85.366 for ECG signals and 12.6668, 0.4014, 0.9187, and 32.4809 for EEG signals. Further, the proposed algorithm shows its efficiency over other existing techniques regarding processing time. Conclusions: Experiments show that the proposed method successfully achieved a high CR while maintaining an excellent level of signal reconstruction in addition to its reduced processing time compared with the existing techniques.
Author Related Publications
Khalied Mohamed Hosny, "SEMANTIC REPRESENTATION OF MUSIC DATABASE USING NEW ONTOLOGY-BASED SYSTEM", Journal of Theoretical and Applied Information Technology, 2020
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Khalied Mohamed Hosny, "Building a New Semantic Social Network Using Semantic Web-Based Techniques", ِASPG, 2021
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Khalied Mohamed Hosny, "New Graphical Ultimate Processor for Mapping Relational Database to Resource Description Framework", IEEE, 2022
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Khalied Mohamed Hosny, "Fast computation of accurate Zernike moments", Springer, 2008
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Khalied Mohamed Hosny, "Accurate Computation of QPCET for Color Images in Different Coordinate Systems", SPIE, 2017
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Department Related Publications
Ehab Roshdy Mohamed, "FOUR-PHASE PROTOCOL FOR DETECTION, DELETION, PROTECTION AND RECOVERY FROM AUTORUN VIRUS", ScienceDirect, 2018
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Khalied Mohamed Hosny, "Resilient Color Image Watermarking Using Accurate Quaternion Radial Substituted Chebyshev Moments", ACM, 2019
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Nabil Ali Mohamed Lashen, "Copy-move forgery detection of duplicated objects using accurate PCET moments and morphological operators", THE IMAGING SCIENCE JOURNAL, 2018
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Khalied Mohamed Hosny, "Novel fractional-order polar harmonic transforms for gray-scale and color image analysis", ُElsevier, 2020
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Khalied Mohamed Hosny, "Fusion of Orthogonal Moment Features for Mammographic Mass Detection and Diagnosis", Ieee, 2020
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