ABSTRACT
The complexity of the biological system often introduces difficulties in the measurement and processing procedures. Unlike the physical systems, the biological system cannot be uncoupled like a subsystem that can be monitored and investigated individually. The signals produced by the system are influenced directly by the activity of the surrounding systems. The source of biological signals is the neural or muscular cell. These, however, do not function alone but in large groups. The accumulated effects of all active cells in the vicinity produce an electrical field which propagates in the volume conductor consisting of the various tissues of the body. The activity of a muscle can thus be indirectly measured by means of electrodes placed on the skin. The acquisition of this type of information is easy; electrodes can be conveniently placed on the skin. The information, however, is difficult to analyse. It is the result of all neural or muscular activity in unknown locations transmitted through an inhomogeneous medium. In spite of these difficulties, electrical signals monitored on the skin surface are of enormous clinical, physiological and kinesiological importance (Cohen, 1986). The electrical signal associated with the contraction of a muscle is called an electromyogram and the study of electromyograms is called electromyography (Winter, 1990). Electromyography (EMG) is a tool that can be very valuable in measuring skeletal muscle electrical output during physical activities. It is important that the EMG is detected correctly and interpreted in light of basic biomedical signal processing, and physiological and biomechanical principles (Soderberg, 1992). The usefulness of the EMG signal is greatly dependent on the ability to extract the information contained in it. EMG is an attractive tool because it gives easy access to physiological processes that cause the muscle to generate force and produce movement (De Luca, 1993a). Since the EMG tool is easy to use, it might be easily misused and the outcomes wrongly interpreted. Therefore, it is important to understand the principles of EMG signal detection and processing to optimize the quality of signal information.
