Biomedical Signal Compression

Digitization of biomedical signals has been used in several areas. Some of these include ambulatory monitoring, phone line transmission, database storage, and several other applications in health and biomedical engineering. These applications have helped in diagnostics, patient care, and remote treatment. One example is the digital transmission of ECG signals, from the patient’s house or ambulance to the hospital. This has been proven useful in cardiac diagnoses. Biomedical signals need to be digitally stored or transmitted with a large number of samples per second, and with a great number of bits per sample, in order to assure the required fidelity of the waveform for visual inspection. Therefore, the use of signal compression techniques is fundamental for cost reduction and technical feasibility of storage and transmission of biomedical signals. The purpose of any signal compression technique is the reduction of the amount of bits used to represent a signal. This must be accomplished while preserving the morphological characteristics of the waveform. In theory, signal compression is the process where the redundant information contained in the signal is detected and eliminated. Shannon (1948) defined redundancy as “the fraction of unnecessary information, and therefore repetitive in the sense that if it was missing, then the information would still be essentially complete, or it could at least be recovered.” Signal compression has been widely studied during the past decades, and several references discuss this subject (Gersho & Gray, 1992; Jayant & Noll, 1982; Sayood, 1996). Signal compression techniques are commonly classified in two categories: lossless and lossy compression. Lossless compression means that the decoded signal is identical to the original one. In lossy compression, a controlled amount of distortion is allowed. Lossy signal compression techniques show higher compression gains than lossless ones.