Reliability of measurement of muscle fiber conduction velocity using surface EMG

Cross-correlating two surface EMG signals detected at two different locations along the path of flow of action potential enables the measurement of the muscle fiber average conduction velocity in those active motor units monitored by the electrodes. The position of the peak of the cross-correlation function is the time delay between the two signals and hence the velocity may be deduced. The estimated velocity using this technique has been observed previously to depend on the location of the electrodes on the muscle surface. Different locations produced different estimates. In this paper we present a measurement system, analyze its inherent inaccuracies and use it for the purpose of investigating the reliability of measurement of conduction velocity from surface EMG. This system utilizes EMG signals detected at a number of locations on the biceps brachii, when under light tension, to look for any pattern of variations of velocity as a function of location and time. It consists of a multi-electrode unit and a set of eight parallel on-line correlators. The electrode unit and the parallel correlators ensure that these measurements are carried out under the same physical and physiological conditions of the muscle. Further, the same detected signals are used in different measurement configurations to try to understand the reasons behind the observed variations in the estimated velocity. The results obtained seem to suggest that there will always be an unpredictable random component superimposed on the estimated velocity, giving rise to differences between estimates at different locations and differences in estimates with time at the same location. Many factors contribute to this random component, such as the non-homogeneous medium between the muscle fibers and the electrodes, the non-parallel geometry and non-uniform conduction velocity of the fibers, and the physical and physiological conditions of the muscle. While it is not possible to remove this random component completely from the measurement, the user must be aware of its presence and how to reduce its effects.