A data compression algorithm for the electroencephalogram.

This paper describes a data compression algorithm for the EEG using a local error measure. The algorithm discards input signal samples provided they can be reconstructed from the stored samples with an error smaller than a given threshold, and according to simple reconstruction functions (the hold, the ramp, and the cosine). An equivalent (in terms of storage) sampling rate of 44 Hz is achieved without noticeable degradation of the signal quality for visual analysis. The method can be easily implemented for real time multichannel data compression/reconstruction.