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Lossless EEG Data Compression Using Delta Modulation and Two Types of Enhanced Adaptive Shift Coders

2021; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-030-93417-0_6

1865-0937

Hend A. Hadi, Loay E. George, Enas Kh. Hassan,

ECG Monitoring and Analysis

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.