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Journal of Medical Engineering & Technology Volume 33, 2009 - Issue 1
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Articles

ECG signal compression using combined modified discrete cosine and discrete wavelet transforms

S. M. Ahmed Electrical and Electronics Engineering Department, Faculty of Engineering, Assiut University, Assiut, Egypt
,
A. F. Al-Ajlouni Communication Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, Jordan
,
M. Abo-Zahhad Electrical and Electronics Engineering Department, Faculty of Engineering, Assiut University, Assiut, EgyptCorrespondence[email protected]
&
B. Harb Communication Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid, Jordan
Pages 1-8 | Published online: 09 Jul 2009

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Balambigai Subramanian & Asokan Ramasamy. (2017) Investigation on the Compression of Electrocardiogram Signals Using Dual Tree Complex Wavelet Transform. IETE Journal of Research 63:3, pages 392-402.
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J.I. Peláez, J.M. Doña, J.F. Fornari & G Serra. (2014) Ischemia classification via ECG using MLP neural networks. International Journal of Computational Intelligence Systems 7:2, pages 344-352.
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A. Alshamali. (2010) Wavelet based ECG compression with adaptive thresholding and efficient coding. Journal of Medical Engineering & Technology 34:5-6, pages 335-339.
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Articles from other publishers (13)

Neenu Sharma & Ramesh Kumar Sunkaria. (2024) ECG compression based on empirical mode decomposition and tunable-Q wavelet transform with validation using heartbeat classification. Signal, Image and Video Processing 18:4, pages 3079-3095.
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Supriya Rajankar, Omprakash Rajankar, Sanjay Talbar & Vrushali Raut. (2024) Signal Adaptive Threshold for ECG Signal Compression Using False Discovery Rate Approach. Circuits, Systems, and Signal Processing.
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Siham Ez-ziymy, Anas Hatim & Slama Hammia. (2023) Real-time hardware architecture of an ECG compression algorithm for IoT health care systems and its VLSI implementation. Multimedia Tools and Applications 83:10, pages 30937-30961.
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Vibha Aggarwal, Sandeep Gupta, Manjeet Singh Patterh & Shipra. (2023) Meta-Analysis approach to assess ECG compression methods: A systematic Review. Meta-Analysis approach to assess ECG compression methods: A systematic Review.
Neenu Sharma & Ramesh Kumar Sunkaria. (2023) Electrocardiography signal compression using non-decimated stationary wavelet transform-based technique. Biomedical Physics & Engineering Express 9:4, pages 045025.
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Ignacio Rojas-Valenzuela, Fernando Rojas, Juan Carlos de la Cruz, Peter Gloesekoetter & Olga Valenzuela. 2023. Bioinformatics and Biomedical Engineering. Bioinformatics and Biomedical Engineering 398 412 .
Hardev Singh Pal, Anil Kumar & Amit Vishwakarma. (2021) Electrocardiogram Compression using Optimized TQWT and Dead-Zone Quantizer. Electrocardiogram Compression using Optimized TQWT and Dead-Zone Quantizer.
Supriya O. Rajankar & Sanjay N. Talbar. (2018) An electrocardiogram signal compression techniques: a comprehensive review. Analog Integrated Circuits and Signal Processing 98:1, pages 59-74.
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Ozal Yildirim, Ru San Tan & U. Rajendra Acharya. (2018) An efficient compression of ECG signals using deep convolutional autoencoders. Cognitive Systems Research 52, pages 198-211.
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A. Swarnkar, Ranjeet Kumar, A. Kumar & P. Khanna. (2017) Performance of different threshold function for ECG compression using Slantlet transform. Performance of different threshold function for ECG compression using Slantlet transform.
Javier F. Fornari & José I. Peláez. 2014. Knowledge Engineering and Management. Knowledge Engineering and Management 429 440 .
Javier F. Fornari & José I. Peláez Sánchez. 2014. Foundations and Applications of Intelligent Systems. Foundations and Applications of Intelligent Systems 547 561 .
Jerrold Scott Petrofsky & Lee Berk. 2012. Treatment of Dry Skin Syndrome. Treatment of Dry Skin Syndrome 561 580 .

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