Title page for ETD etd-08082005-113739

Document Type Master's Dissertation
Author Viljoen, Suretha
Email suweda@gmail.com
URN etd-08082005-113739
Document Title Analysis of crosstalk signals in a cylindrical layered volume conductor Influence of the anatomy, detection system and physical properties of the tissues
Degree MEng(Bio-Engineering)
Department Electrical, Electronic and Computer Engineering
Advisor Name Title
Dr T Hanekom Committee Chair
Prof D Farina Committee Co-Chair
  • crosstalk
  • analytical model
  • spatial filters
  • MUAP
  • ARV
  • MNF
  • muscle shortening
  • increased contraction force
  • sEMG
  • modelling
Date 2005-08-05
Availability unrestricted
A comparison of the ability of different spatial filters to reduce the amount of crosstalk in a surface electromyography (sEMG) measurement was conducted. It focused on the influence of different properties of the muscle anatomy and detection system used on the amount of crosstalk present in the measurements.

An analytical model was developed which enabled the simulation of single fibre action potentials (SFAPs). These fibres were grouped together in motor units (MUs). Each MU has characteristics which, along with the SFAPs, are used to obtain the motor unit action potential (MUAP). A summation of the MUAPs from all the MUs in a muscle leads to the electromyogram (EMG) signal generated by the muscle. This is the first model which simulates a complete muscle for crosstalk investigation. Previous studies were done for single fibres (Farina & Rainoldi 1999; Farina et al. 2002e; Farina et al. 2004a) or MUs (Dimitrova et al. 2002; Dimitrov et al. 2003; Winter et al. 1994). Lowery et al. simulated a complete muscle, but only investigated one spatial filter (Lowery et al. 2003a). This model is thus the first of its kind.

EMG signals were generated for limbs with different anatomical properties and recorded with various detection systems. The parameters used for comparison of the recorded signals are the average rectified value (ARV) and mean frequency (MNF), which describe the amplitude and frequency components of an EMG signal, respectively. These parameters were computed for each EMG signal and interpreted to make recommendations on which detection system results in the best crosstalk rejection for a specific experimental set-up.

The conclusion is that crosstalk selectivity in an sEMG measurement is decreased by increasing the thickness of the fat layer, increasing the skin conductivity, decreasing the fibre length, increasing the interelectrode distance of the detection system, placing the detection electrodes directly above the end-plate area or an increased state of muscle contraction. Varying the contraction force strength or placing the detection electrodes directly above the tendon area has no influence on the crosstalk selectivity.

For most of the conditions investigated, the normal double differential (NDD) detection system results in the best crosstalk reduction. The only exceptions are a set-up with poor skin conductivity where NDD and double differential (DD) performed comparably, and the two simulations in which the muscle length is varied, where the DD filter performed best.

Previous studies have found DD to be more selective for crosstalk rejection than NDD (Dimitrov et al. 2003; Farina et al. 2002a; Van Vlugt & Van Dijk 2000). Possible reasons for the contradictory results are the high value of skin conductivity currently used or influences of the muscle geometry.

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