This thesis aims to analyze the evolution of muscle fatigue during an alternating isometric exercise between two positions, performed while suspended on a climbing wall, through the study of surface electromyographic (sEMG) signals recorded from 22 muscles. The objective is to identify robust and sensitive indicators of muscle fatigue, combining classical and advanced analysis methods. The analysis was divided into two main phases. In the first phase, EMG signals, segmented into temporal windows, were processed to extract the root mean square (RMS) and the median frequency (MDF). These indices are commonly used to evaluate the onset of muscular fatigue. In the second phase, nonlinear analysis methods were applied to the same windows, such as multifractal Detrended Fluctuation Analysis (MFDFA), Recurrence Quantification Anal ysis (RQA), and Sample Entropy, in order to explore the complexity and temporal dy namics of the EMG signals. The results show a progressive loss of complexity and an increase in regularity in muscle signals as fatigue progresses, confirmed by the reduction of entropy, and by the increase of the Hurst exponents and determinism. The work highlights how the integration of classical and nonlinear indices allows for a more in-depth and multidimensional characterization of muscle fatigue, revealing differences related to body position, the duration of the analysis intervals, and the specific muscles considered, with potential applications in athletic performance monitoring and neuromuscular assessment
Questa tesi si propone di analizzare l’evoluzione della fatica muscolare durante un esercizio isometrico alternato tra due posizioni in sospensione su parete di arrampicata, attraverso lo studio di segnali elettromiografici di superficie (sEMG) registrati da 22 muscoli. L’obiettivo è quello di identificare indicatori robusti e sensibili della fatica muscolare, combinando metodi di analisi classici e avanzati. L’analisi è stata articolata in due fasi principali. Nella prima fase, i segnali EMG, suddivisi in finestre temporali, sono stati elaborati per estrarre indici come il valore quadratico medio (RMS) e la frequenza mediana (MDF), comunemente utilizzati per valutare l’insorgenza della fatica muscolare. Nella seconda fase, sulle stesse finestre sono stati applicati metodi di analisi non lineare, come la Detrended Fluctuation Analysis multifrattale (MFDFA), la Recurrence Quantification Analysis (RQA) e l’entropia campionaria (Sample Entropy), al fine di esplorare la complessità e la dinamica temporale dei segnali EMG. I risultati mostrano una progressiva perdita di complessità e un aumento della regolarità nei segnali muscolari durante il progredire dell’affaticamento, confermata dalla riduzione dell’entropia e dall’aumento degli esponenti di Hurst e del determinismo. Il lavoro evidenzia come l’integrazione di indici classici e non lineari consenta una caratterizzazione più approfondita e multidimensionale della fatica muscolare, mettendo in luce differenze legate alla posizione, alla durata degli intervalli di analisi e ai muscoli considerati, con potenziali applicazioni nel monitoraggio delle prestazioni atletiche e nella valutazione neuromuscolare
Valutazione della fatica muscolare in arrampicata attraverso indici elettromiografici classici e non lineari
LEO, GIACOMO
2024/2025
Abstract
This thesis aims to analyze the evolution of muscle fatigue during an alternating isometric exercise between two positions, performed while suspended on a climbing wall, through the study of surface electromyographic (sEMG) signals recorded from 22 muscles. The objective is to identify robust and sensitive indicators of muscle fatigue, combining classical and advanced analysis methods. The analysis was divided into two main phases. In the first phase, EMG signals, segmented into temporal windows, were processed to extract the root mean square (RMS) and the median frequency (MDF). These indices are commonly used to evaluate the onset of muscular fatigue. In the second phase, nonlinear analysis methods were applied to the same windows, such as multifractal Detrended Fluctuation Analysis (MFDFA), Recurrence Quantification Anal ysis (RQA), and Sample Entropy, in order to explore the complexity and temporal dy namics of the EMG signals. The results show a progressive loss of complexity and an increase in regularity in muscle signals as fatigue progresses, confirmed by the reduction of entropy, and by the increase of the Hurst exponents and determinism. The work highlights how the integration of classical and nonlinear indices allows for a more in-depth and multidimensional characterization of muscle fatigue, revealing differences related to body position, the duration of the analysis intervals, and the specific muscles considered, with potential applications in athletic performance monitoring and neuromuscular assessment| File | Dimensione | Formato | |
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2025_10_Leo_Executive Summary_02.pdf
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2025_10_Leo_Tesi_01.pdf
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https://hdl.handle.net/10589/243370