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Impact of lossy data compression techniques on EEG-based pattern recognition systems | IEEE Conference Publication | IEEE Xplore

Impact of lossy data compression techniques on EEG-based pattern recognition systems


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...Show More

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.
Date of Conference: 20-24 August 2018
Date Added to IEEE Xplore: 29 November 2018
ISBN Information:
Print on Demand(PoD) ISSN: 1051-4651
Conference Location: Beijing, China

References

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