EMG interference pattern power spectrum analysis in neuro-muscular disorders

One hundred sixty six subjects, who had clinically proven Neuromuscular (NM) diagnoses and 37 normal controls, had their biceps muscle EMGs, recorded in sustained isometric maximum voluntary contraction (MVC). The EMG signals were repeatedly transformed into power spectra (PS). The PS were then analysed by various statistical methods. The statistical analyses showed an overall significant difference in power between the sexes but only in the Dysschwannian Neuropathy group and no differences due to age; a very highly significant fatigue trend that manifests, to a different extent, in all frequency bands; the groups were significantly different from one another in both total power and in band-specific power, and to differ in their responses to fatigue. These analyses showed that based on PS alone discriminant analysis can separate the cases into only two significantly different groups: normal controls could not be separated from neuropathies, but both were significantly different from Myasthenia Gravis and myopathies. The statistical analysis highlighted as important the use of separate PS frequency bands and the use of a fatigue paradigm for separating the various NM disorders--showing Group-by-Fatigue; Group-by-Band and Group-by-Band-by-Fatigue interactions to be highly significant. All the above mentioned significant features, though, resulted in a low predictive (diagnostic) value by discriminant analysis and even worse by clustering techniques.