Electromyographic (EMG) signal analysis allows studying and analysing muscle fatigue. By analysing an electromyographic signal, various factors can be examined, thereby better defining the muscle activity of the muscle of interest. Specifically, this study focused on the analysis of two muscles belonging to the lower body regions: the vastus lateralis and the medial gastrocnemius. The purpose of this analysis is to identify muscle fatigue in dynamic conditions for the two muscles of interest. Two groups of subjects were considered: typically developed (control) subjects and subjects with cerebral palsy. The testing protocol differs between the two groups: for the typically developed subjects, it involved running on a treadmill at incremental speeds, while for the cerebral palsy subjects, a specialized structure (frame running) on a treadmill at incremental speeds was used. Both test protocols continued until the analysed subject was exhausted. In addition to EMG signals, other values such as blood parameter concentrations and respiratory values were collected. The patients also provided personal considerations on the Borg scale. Analysing these two groups of subjects allowed identifying when muscle fatigue occurs and how early it occurs in subjects with cerebral palsy. The analysis of muscle fatigue was divided into two main phases: the first based on evaluating respiratory values and blood concentration parameters such as lactate concentration, pO2, pCO2, etc. Subsequently, electromyographic signals were analyzed using different techniques to correctly identify muscle fatigue and make comparisons among different methodologies, as there is no gold standard technique for this type of analysis under such conditions. Before analysing the signals, they were filtered using a fourth-order Butterworth filter, and undesired peaks were subsequently removed. The signals were then initially analysed considering the median frequency and mean power, two gold standard techniques for muscle fatigue analysis in static conditions. The signals were further processed to analyse the Lempel Ziv complexity measure (LZ2) and Hurst Exponent. This study enabled the comparison of different techniques for identifying muscle fatigue and the actual identification of muscle fatigue, thereby defining a time interval in which the muscles of interest begin to exhibit muscle fatigue. Additionally, the study provided a more detailed understanding of which muscle typically experiences muscle fatigue first in a protocol executed under dynamic conditions.
Electromyographic (EMG) signal analysis allows studying and analysing muscle fatigue. By analysing an electromyographic signal, various factors can be examined, thereby better defining the muscle activity of the muscle of interest. Specifically, this study focused on the analysis of two muscles belonging to the lower body regions: the vastus lateralis and the medial gastrocnemius. The purpose of this analysis is to identify muscle fatigue in dynamic conditions for the two muscles of interest. Two groups of subjects were considered: typically developed (control) subjects and subjects with cerebral palsy. The testing protocol differs between the two groups: for the typically developed subjects, it involved running on a treadmill at incremental speeds, while for the cerebral palsy subjects, a specialized structure (frame running) on a treadmill at incremental speeds was used. Both test protocols continued until the analysed subject was exhausted. In addition to EMG signals, other values such as blood parameter concentrations and respiratory values were collected. The patients also provided personal considerations on the Borg scale. Analysing these two groups of subjects allowed identifying when muscle fatigue occurs and how early it occurs in subjects with cerebral palsy. The analysis of muscle fatigue was divided into two main phases: the first based on evaluating respiratory values and blood concentration parameters such as lactate concentration, pO2, pCO2, etc. Subsequently, electromyographic signals were analyzed using different techniques to correctly identify muscle fatigue and make comparisons among different methodologies, as there is no gold standard technique for this type of analysis under such conditions. Before analysing the signals, they were filtered using a fourth-order Butterworth filter, and undesired peaks were subsequently removed. The signals were then initially analysed considering the median frequency and mean power, two gold standard techniques for muscle fatigue analysis in static conditions. The signals were further processed to analyse the Lempel Ziv complexity measure (LZ2) and Hurst Exponent. This study enabled the comparison of different techniques for identifying muscle fatigue and the actual identification of muscle fatigue, thereby defining a time interval in which the muscles of interest begin to exhibit muscle fatigue. Additionally, the study provided a more detailed understanding of which muscle typically experiences muscle fatigue first in a protocol executed under dynamic conditions.
Muscle fatigue analysis during graded exercise in children with Cerebral Palsy
RIPPA, SIMONE
2023/2024
Abstract
Electromyographic (EMG) signal analysis allows studying and analysing muscle fatigue. By analysing an electromyographic signal, various factors can be examined, thereby better defining the muscle activity of the muscle of interest. Specifically, this study focused on the analysis of two muscles belonging to the lower body regions: the vastus lateralis and the medial gastrocnemius. The purpose of this analysis is to identify muscle fatigue in dynamic conditions for the two muscles of interest. Two groups of subjects were considered: typically developed (control) subjects and subjects with cerebral palsy. The testing protocol differs between the two groups: for the typically developed subjects, it involved running on a treadmill at incremental speeds, while for the cerebral palsy subjects, a specialized structure (frame running) on a treadmill at incremental speeds was used. Both test protocols continued until the analysed subject was exhausted. In addition to EMG signals, other values such as blood parameter concentrations and respiratory values were collected. The patients also provided personal considerations on the Borg scale. Analysing these two groups of subjects allowed identifying when muscle fatigue occurs and how early it occurs in subjects with cerebral palsy. The analysis of muscle fatigue was divided into two main phases: the first based on evaluating respiratory values and blood concentration parameters such as lactate concentration, pO2, pCO2, etc. Subsequently, electromyographic signals were analyzed using different techniques to correctly identify muscle fatigue and make comparisons among different methodologies, as there is no gold standard technique for this type of analysis under such conditions. Before analysing the signals, they were filtered using a fourth-order Butterworth filter, and undesired peaks were subsequently removed. The signals were then initially analysed considering the median frequency and mean power, two gold standard techniques for muscle fatigue analysis in static conditions. The signals were further processed to analyse the Lempel Ziv complexity measure (LZ2) and Hurst Exponent. This study enabled the comparison of different techniques for identifying muscle fatigue and the actual identification of muscle fatigue, thereby defining a time interval in which the muscles of interest begin to exhibit muscle fatigue. Additionally, the study provided a more detailed understanding of which muscle typically experiences muscle fatigue first in a protocol executed under dynamic conditions.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/62132