ECG contamination of paraspinal EMG measurements is a known issue (1,2), with several proposed methods of correction(3,4). In addition to this some question remains to how much of an effect this contamination actually has on the EMG recordings. From a population of 455 previously recorded EMG datasets, 33 severely contaminated sets of data were selected. These 33 datasets were analysed to produce the Half-Width, RMS, RMS Slope, RMS Intercept, MF Slope, and MF Intercept variables. The Independent Component Analysis method was used to separate the EMG data into a series of additive subcomponents which allowed the removal of ECG contamination whilst preserving underlying EMG. The subcomponents were then reintegrated to produce the original EMG signal, minus the contamination. The resultant signal data were analysed to produce the same outcome variables so a comparison could be made.Introduction
Methods
It has previously been reported ( EMG data was recorded from 192 subjects across two years (initial contact, 12 months and 24 months). The data were analysed and the spectral half-widths calculated. The ICA method was then applied to the original raw data. As the power spectrum of ECG runs from 0-20Hz the resultant spectra were analysed to calculate which of them had the most signal energy below 20Hz. A high band pass filter was used to remove all signal data below 20Hz from this independent component. This method was chosen as there was signal data present in the chosen spectrum above 20Hz which would be EMG data. Removing data only below 20Hz preserved this EMG data. The components were then re-integrated and re-analysed to calculate the new half-widths. These new half-widths were compared with the originals to generate the results.Introduction
Methods
Previous work( EMG data was recorded from 192 subjects across two years (initial contact, 12 months and 24 months). The data were analysed and SCMs produced. The 30 second test data was split into 30 one second epochs. Colour values were scaled to the individual data set maximum and divided into 12 bands according to frequency strength at a particular point. Median Frequency values were calculated for each epoch and a line of best fit added to the colour map to further aid the diagnosis process. Maps with faulty recordings were excluded and 20 data sets from each group (BP and no BP) selected at random. Four observers were given only 5 minutes instruction and then asked to indicate whether they thought each map belonged to the LBP or no LBP group.Introduction
Methods
As multiple source signals were recorded per test, the Independent Component Analysis technique was able to be used to split the EMG raw signal into statistically independent components. This technique is designed to take the multiple signal inputs, and convert them into multiple outputs, where the inputs are distinguishable by electrode location; the outputs are distinguishable by signal biological origin.
