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Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_I | Pages 36 - 36
1 Jan 2012
Coxon A Farmer S Greenough C
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Introduction

It has previously been reported (1,2,3) that EMG signals from the lumbar spine are highly prone to contamination by ECG artefacts. It has also been reported that Independent Component Analysis is a suitable method for extracting this contamination (4).

Methods

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.


Orthopaedic Proceedings
Vol. 94-B, Issue SUPP_I | Pages 40 - 40
1 Jan 2012
Coxon A Farmer S Watson P Murray M Roper H Kaid L Greenough C
Full Access

Introduction

Previous work(1) has suggested that Spectral Colour Mapping (SCM) may have potential as an objective measurement tool for analysing Electromyography (EMG) data from spinal muscles, but the production and analysis of these maps is a complex undertaking. It would be beneficial for a system to create these maps and be useable with a minimum of training.

Methods

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.