Correlação entre o sinal mecanomiográfico e a escala modificada de Ashworth durante avaliação clínica da espasticidade

Spasticity is a common disorder in people who have upper motor neuron injury. The involvement may occur at different levels. The Modified Ashworth Scale (MAS) is the most used method to measure involvement levels. But it corresponds to a subjective evaluation. Mechanomyography (MMG) is an objective technique that quantifies the muscle vibration during the contraction and stretching events. So, it may assess the level of spasticity accurately. This study aimed to investigate the correlation between spasticity levels determined by MAS with MMG signal in spastic and not spastic muscles. In the experimental protocol, we evaluated 34 members of 22 volunteers, of both genders, with a mean age of 39.91 ± 13.77 years. We evaluated the levels of spasticity by MAS in flexor and extensor muscle groups of the knee and/or elbow, where one muscle group was the agonist and one antagonist. Simultaneously the assessment by the MAS, caught up the MMG signals. We used a custom MMG equipment to register and record the signals, configured in LabView platform. Using the MatLab computer program, it was processed the MMG signals in the time domain (median energy) and spectral domain (median frequency) for the three motion axes: X (transversal), Y (longitudinal) and Z (perpendicular). For bandwidth delimitation, we used a 3rd order Butterworth filter, acting in the range of 5-50 Hz. Statistical tests as Spearman's correlation coefficient, Kruskal-Wallis test and linear correlation test were applied. As results in the time domain, the Kruskal-Wallis test showed differences in median energy (MMGME) between MAS groups. The linear correlation test showed high linear correlation between MAS and MMGME for the agonist muscle as well as for the antagonist group. The largest linear correlation occurred between the MAS and MMG ME for the Z axis of the agonist muscle group (R2 = 0.9557) and the lowest correlation occurred in the X axis, for the antagonist muscle group (R2 = 0.8862). The Spearman correlation test also confirmed high correlation for all axes in the time domain analysis. In the spectral domain, the analysis showed an increase in the median frequency (MMGMF) in MAS’ greater levels. The highest correlation coefficient between MAS and MMGMF signal occurred in the Z axis for the agonist muscle group (R2 = 0.4883), and the lowest value occurred on the Y axis for the antagonist group (R2 = 0.1657). By means of the Spearman correlation test, the highest correlation occurred between the Y axis of the agonist group (0.6951; p <0.001) and the lowest value on the X axis of the antagonist group (0.3592; p <0.001). We conclude that there was a significantly high correlation between the MMGME and MAS in both muscle groups. Also between MMG and MAS occurred a significant correlation, however moderate for the agonist group, and low for the antagonist group. So, the MMGME proved to be more an appropriate descriptor to correlate with the degree of spasticity defined by the MAS.

Ambiente para aquisição e processamento de sinal eletromiográfico de superfície

In this work, a platform to the conditioning, digitizing, visualization and recording of the EMG signals was developed. After the acquisition, the analysis can be done by signal processing techniques. The platform consists of two modules witch acquire electromyography (EMG) signals by surface electrodes, limit the interest frequency band, filter the power grid interference and digitalize the signals by the analogue-to- digital converter of the modules microcontroller. Thereby, the data are sent to the computer by the USB interface by the HID specification, displayed in real-time in graphical form and stored in files. As processing resources was implemented the operations of signal absolute value, the determination of effective value (RMS), Fourier analysis, digital filter (IIR) and the adaptive filter. Platform initial tests were performed with signal of lower and upper limbs with the aim to compare the EMG signal laterality. The open platform is intended to educational activities and academic research, allowing the addition of other processing methods that the researcher want to evaluate or other required analysis.