Improved evaluation of back muscle SEMG characteristics by modelling

Surface EMG (SEMG) as non-invasive method is a valuable tool in functional studies of movement co-ordination. The interpolation of the SEMG power (EMG mapping) gives information about intra- and inter-muscular co-ordination. It has been shown that SEMG maps of low back pain patients and healthy subjects differ. The only major drawback to SEMG is that volume conduction of muscle tissue, fat, and skin decreases the spatial and temporal resolution of signals. To improve the interpretation of SEMG signals, we have applied high pass filtering of cross covariance functions, which has proved to be useful in increasing the spatial resolution, to SEMG data of the back region. Experimental data demonstrate that SEMG signals from the back extensors show only rarely signs of action potential propagation. This behaviour, also described in the literature, can be explained by a model assuming short, deep muscle fibres, having bipolar end effects, with overlapping positions parallel to the fibre direction. This condition is fulfilled by the mm. multifidii et rotatores which are part of the m. erector spinae. Although the model is simplistic, the agreement between simulations and experiments is good.