Slepa ločitev večkanalnih površinskih elektromiogramov dinamičnih mišičnih skrčitev : doktorska disertacija

slovenian

doktorska dela

2016

Univerza v Mariboru, Fakulteta za elektrotehniko računalništvo in informatiko

Analysis of electromyograms (EMG) is of great importance in medicine as it often represents a key part of medical diagnostics. In the last decade, the method called Convolution Kernel Compensation (CKC) was developed in System Software Laboratory at Faculty of Electrical Engineering and Computer Science, University of Maribor. This method successfully decomposes EMG signals into contributions of individual motor units. It was extensively tested in different experimental conditions and has proven to be very efficient in the case of isometric muscle contractions. However, this is no longer the case in dynamic muscle contractions. The latter introduce geometrical deformations of muscle tissues which drastically affect the CKC method. In this thesis, we study changes of surface EMG in the case of dynamic muscle contractions and introduce two new surface EMG decomposition approaches. Both approaches are based on the CKC method. The first algorithm builds on the notion that measured motor unit action potentials (MUAPs) combine travelling and non-travelling components. We demonstrate that non-travelling component is significantly less prone to geometric deformations of a muscle than its traveling counterpart. For this reason we focus our decomposition on non-travelling component of a MUAP only. The second algorithm is based on dynamical weighting of contributions from individual motor units in CKC and adapts very well to the dynamic changes of MUAPs. Both approaches have been tested on synthetic and experimental surface EMG signals. Synthetic signals have been generated with adapted surface EMG simulator that discretises the muscle contractions and supports systematic testing of noise impact, effect of spatial filters and different speeds and ranges of dynamic contractions. Experimental surface EMG signals have been obtained from vastus lateralis and rectus femoris muscles of five young healthy subjects during knee bending at speeds of 5°/s and 10°/s, respectively. The best results were obtained with dynamical weighting of motor unit contributions. This method detected with high reliability 6.5 % 1.8 and 4.5 % 1.6 motor units in vastus lateralis and rectus femoris muscle, respectively. The method using non-travelling MUAP component was significantly less efficient, especially in the case of experimental EMG signals.

07.08.2023