Since Electroencephalogram (EEG) signals are treated as datasets, the volume of such datasets are particularly large, EEG compression focuses on diminishing the amount of data entailed to represent EEG signal for the purposes of both transmission and storage. EEG compression is used for eliminating the redundant data in EEG signal. In this paper, a low complexity efficient compression system based on data modulation and enhanced adaptive shift coding is proposed for fast, lossless, and efficient compression. The proposed system starts with delta modulation, which is performed on the raw data, followed by mapping to positive to get rid of any negative values if present, and then two types of enhanced adaptive shift coders are applied. The code-words are passed simultaneously to both optimizers; and the number of bits equivalent to the same code-word from each optimizer is compared, the optimizer with smaller number of bits is chosen for this code-word to be stored in the binary file as the compression outcome. The system performance is tested using EEG data files of Motor\Movement Dataset; the test samples have different size, and the compression system performance is evaluated using Compression Ratio (CR). The experiment outcomes showed that the compression recital of the system is encouraging and outperformed the standard encoder of WinRAR application when it was applied on the same data samples.

New Trends in Information and Communications Technology Applications : 5th International Conference, NTICT 2021, Baghdad, Iraq, November 17–18, 2021, Proceedings

Abbas M. Al-Bakry, Safaa O. Al-mamory, Mouayad A. Sahib, Loay E. George, Jaafar A. Aldhaibani, Safaa O. Al-Mamory, Haitham S. Hasan, George S. Oreku

International Conference on New Trends in Information and Communications Technology Applications (5th : 2021 : Baghdad, Iraq)

Ivan V. Sergienko; Valeriy K. Zadiraka; Oleg M. Lytvyn

Springer International Publishing AG

Springer Nature Switzerland AG

publisher not identified

Communications in computer and information science, Cham, Switzerland :, 2021

Communications in Computer and Information Science Ser, Cham, 2022

Springer Nature, Cham, 2022

Switzerland, Switzerland

4, 20220111

S.l, uuuu

S.l, 2022

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Referenced by: doi:10.1109/atc.2015.7388309 doi:10.1109/4233.788586 doi:10.1016/j.bspc.2011.06.007 doi:10.1016/j.bspc.2016.08.024 doi:10.1109/titb.2012.2194298 doi:10.1109/titb.2012.2230012 doi:10.24996/ijs.2020.61.4.25 doi:10.24996/ijs.2020.61.11.32 doi:10.1109/crcsit.2017.7965556 doi:10.1109/tbme.2004.827072 doi:10.19026/rjaset.14.3992 doi:10.25195/ijci.v43i1.74 doi:10.1109/tkde.2012.237

This book constitutes refereed proceedings of the 5th International Conference on New Trends in Information and Communications Technology Applications, NTICT 2021, held in Baghdad, Iraq, in November 2021. The 13 full papers presented were thoroughly reviewed and selected from 52 qualified submissions. The volume presents the latest research results in such areas as network protocols, overlay and other logical network structures, wireless access networks, computer vision, machine learning, artificial Intelligence, data mining, control methods.