Abstract
Electroencephalogram (EEG) data compression has been used to reduce the space for storage and speed up the data circulation. Albeit lossy compression techniques achieve a much higher compression ratio than lossless ones, they introduce the loss of information in reconstructed data, which may affect to the performance of EEG-based pattern recognition systems. In this paper, we investigate the impact of lossy compression techniques on the performance of EEG-based pattern recognition systems including seizure recognition and person recognition. Our experiments are conducted on two public databases using two different EEG lossy compression techniques. Experimental results show that the recognition performance is not significantly reduced when using lossy techniques at high compression ratios.
| Original language | English |
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| Title of host publication | 2018 24th International Conference on Pattern Recognition, ICPR 2018 |
| Place of Publication | Beijing, PRC |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 2308-2313 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538637883 |
| ISBN (Print) | 9781538637890 |
| DOIs | |
| Publication status | Published - 26 Nov 2018 |
| Event | 24th International Conference on Pattern Recognition 2018 - Beijing, China Duration: 20 Aug 2018 → 24 Aug 2018 http://www.icpr2018.net/ |
Publication series
| Name | Proceedings - International Conference on Pattern Recognition |
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| Volume | 2018-August |
| ISSN (Print) | 1051-4651 |
Conference
| Conference | 24th International Conference on Pattern Recognition 2018 |
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| Abbreviated title | ICPR |
| Country/Territory | China |
| City | Beijing |
| Period | 20/08/18 → 24/08/18 |
| Internet address |