Biosignals and Compression Standards

Electric, mechanical or chemical signals of biological origin delivered by living things can always be of interest for diagnosis, patient monitoring, and biomedical research. Such biological signals, namely biosignals, as electrocardiogram (ECG), electroencephalogram (EEG), surface electromyogram (SEMG), bioacoustic signals (lung, heart, and bowel sounds), are usually presented by large amounts of data when digitized for storage and analysis within a signal processing framework. On the contrary, other medical information, i.e., drug description, demographic and anamnestic data, result in substantially smaller data archives. To this end, it is noteworthy the 80 kbytes data equivalence of 10 sec digitized resting ECG of 8/12 leads to 40 pages of text of an encyclopedic dictionary! (Zywietz, 1998). As a result, data reduction and compression processes are of great interest to biosignal analysis, especially when data transmission (e.g. in telemedicine applications) or long-term recordings (e.g. in sleep laboratories, intensive care) are involved. With appropriate processing of biosignals, the redundant data stream could be reduced to the most significant parameters that could efficiently contribute to medical decision making. In this way, high density storage could be achieved. In the same vein, reduction of the number of bits required to describe a biosignal could facilitate the data transmission, but it must be done with great care if it results in a loss of information. Although new emerging data compression techniques with very promising results are seen in the recent years, some problems have not been entirely addressed. In particular, the following items are still under consideration