Evaluation of a statistical lossless compression algorithm for the Electroencephalogram

Abstract
The undergoing explosion of performance/price ratio of the so called personal computers, brings to the scene the availability of high performance processors with large amounts of memory, at prices that are generally acceptable for most of laboratory budgets. High density storage devices, such as optical disks, add up the capability to store, at low prices, huge amounts of data in small, reliable media. Those two facts combined together result, for the first time, in the possibility of using true digital machines for the acquisition and storage of biological information such as the Electroencephalogram (EEG), with costs that can become truly competitive with current recording on paper. Practical paper-less EEG machines still have to deal with large amounts of data storage (24 hour monitoring session using 16 channels, will produce more than 400 MByte of data). It is therefore advisable to perform compression on data, prior to storage, in order to shorten the resulting cost/sample.

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