A two-dimensional approach for lossless EEG compression
In this paper, we study various lossless compression techniques for electroencephalograph (EEG) signals. We discuss a computationally simple pre-processing technique, where EEG signal is arranged in the form of a matrix (2-D) before compression. We discuss a two-stage coder to compress the EEG matri...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/101141 http://hdl.handle.net/10220/18353 |
| _version_ | 1826109556071071744 |
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| author | Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba |
| author_sort | Srinivasan, K. |
| collection | NTU |
| description | In this paper, we study various lossless compression techniques for electroencephalograph (EEG) signals. We discuss a computationally simple pre-processing technique, where EEG signal is arranged in the form of a matrix (2-D) before compression. We discuss a two-stage coder to compress the EEG matrix, with a lossy coding layer (SPIHT) and residual coding layer (arithmetic coding). This coder is optimally tuned to utilize the source memory and the i.i.d. nature of the residual. We also investigate and compare EEG compression with other schemes such as JPEG2000 image compression standard, predictive coding based shorten, and simple entropy coding. The compression algorithms are tested with University of Bonn database and Physiobank Motor/Mental Imagery database. 2-D based compression schemes yielded higher lossless compression compared to the standard vector-based compression, predictive and entropy coding schemes. The use of pre-processing technique resulted in 6% improvement, and the two-stage coder yielded a further improvement of 3% in compression performance. |
| first_indexed | 2024-10-01T02:20:10Z |
| format | Journal Article |
| id | ntu-10356/101141 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T02:20:10Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1011412020-03-07T14:00:34Z A two-dimensional approach for lossless EEG compression Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics In this paper, we study various lossless compression techniques for electroencephalograph (EEG) signals. We discuss a computationally simple pre-processing technique, where EEG signal is arranged in the form of a matrix (2-D) before compression. We discuss a two-stage coder to compress the EEG matrix, with a lossy coding layer (SPIHT) and residual coding layer (arithmetic coding). This coder is optimally tuned to utilize the source memory and the i.i.d. nature of the residual. We also investigate and compare EEG compression with other schemes such as JPEG2000 image compression standard, predictive coding based shorten, and simple entropy coding. The compression algorithms are tested with University of Bonn database and Physiobank Motor/Mental Imagery database. 2-D based compression schemes yielded higher lossless compression compared to the standard vector-based compression, predictive and entropy coding schemes. The use of pre-processing technique resulted in 6% improvement, and the two-stage coder yielded a further improvement of 3% in compression performance. Accepted version 2013-12-20T03:08:32Z 2019-12-06T20:33:55Z 2013-12-20T03:08:32Z 2019-12-06T20:33:55Z 2011 2011 Journal Article Srinivasan, K., Dauwels, J., & Reddy, M. R. (2011). A two-dimensional approach for lossless EEG compression. Biomedical signal processing and control, 6(4), 387–394. 1746-8094 https://hdl.handle.net/10356/101141 http://hdl.handle.net/10220/18353 10.1016/j.bspc.2011.01.004 163243 en Biomedical signal processing and control © 2011 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Biomedical signal processing and control, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.bspc.2011.01.004]. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Srinivasan, K. Dauwels, Justin Reddy, M. Ramasubba A two-dimensional approach for lossless EEG compression |
| title | A two-dimensional approach for lossless EEG compression |
| title_full | A two-dimensional approach for lossless EEG compression |
| title_fullStr | A two-dimensional approach for lossless EEG compression |
| title_full_unstemmed | A two-dimensional approach for lossless EEG compression |
| title_short | A two-dimensional approach for lossless EEG compression |
| title_sort | two dimensional approach for lossless eeg compression |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics |
| url | https://hdl.handle.net/10356/101141 http://hdl.handle.net/10220/18353 |
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