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Surface electromyography (SEMG) is a commonly used tool in the study of muscle activity due its non-invasive and representative nature. In particular, the presence of fatigue can be detected in SEMG signals when the power spectrum becomes compressed, resulting in a reduction in both the mean and median frequencies. Despite these benefits, several problems arise when SEMG is used in an ergonomic setting to detect postural muscle activity. In order to detect fatigue in postural muscles, recordings must be of long duration due to the low levels of SEMG activity present. Furthermore, low activation levels are often compounded by low signal to noise ratios (SNR), while postural SEMG activity is often masked by other electrical activity and noise (Lamotte et al, 1996). The aim of this investigation was to develop an automatic segmentation method, in order to detect postural SEMG segments. The secondary aim of …