The aim of this study was to test intra-session repeatability of automatic neuromuscular responses of three muscles which are involved in lumbo-pelvic stability (LPSM). Sixteen young healthy volunteers participated in the study. Three different tests of trunk stability functions were carried out in each of them: (1) a test of self initiated quick shoulder flexion to test the anticipatory pre-activation patterns of the LPSM, (2) a test of neuromuscular reaction of LPSM on unexpected loading, and (3) a test of neuromuscular reaction of LPSM on unexpected unloading of upper extremities. Forty consecutive trials of each task were carried out. The latency of the neuromuscular responses (LAT) and the rate of LPSM increase in activation (RMS50) were analysed in all of the responses. The dependence of parameters` repeatability on the number of trials averaged was analysed using intra-class correlation coefficient, typical error of measurement and coefficient of variation. For all the three observed muscles and all the motor tasks ICCa values of the RMS50 was generally higher than that of LAT. Eighteen or more trials of the same task are needed to achieve acceptable ICCa values. Results of TE and CV showed progressive decrease with the increasing number of the trials being averaged. The most reduction in TE and CV took place with averaging the first 10 consecutive trials. Based on our results we can conclude that averaging of 20 or more trials of the same lumbo-pelvic stability test will bring us a repeatable measure. However, in order to work with less trials also other methodological approaches such as signal averaging should be considered.
COBISS.SI-ID: 2072019
The paper describes Pade, a new method for qualitative learning which estimates partial derivatives of the target function from training data and uses them to induce qualitative models of the target function. We formulated three methods for computation of derivatives, all based on using linear regression on local neighbourhoods. The methods were empirically tested on artificial and real-world data. We also provide a case study which shows how the developed methods can be used in practice. Described methods are useful for providing abstractions of measured data, especially in presence of noise, therefore we expect them to be very applicable to this project as one of the preprocessing steps before actual analysis of the data.
COBISS.SI-ID: 8324436
Skeletal muscle composition is valuable information for physicians, athletes/coaches, physiotherapists, scientists, etc. From this information a timing of treatment and final results are depending. Since now only invasive techniques were known, which limits us in everyday use. We have proposed a noninvasive technique, that enables valid and reliable measurement of muscle composition with use of linear displacement sensor and nonpainful electrical stimulation
COBISS.SI-ID: 1992147