European Journal of Cardiovascular Medicine

Muscle fatigue is a well-documented physiological phenomenon characterized by a decline in the muscle's ability to generate force or power during sustained or repetitive activity. It plays a significant role in limiting physical performance and can be influenced by several factors, including training status, type of muscle contraction, and metabolic demands (1). In sports science and rehabilitation, understanding muscle fatigue is crucial for optimizing performance, preventing injuries, and designing effective training or therapeutic programs.

Surface electromyography (sEMG) is a widely used, non-invasive technique to assess neuromuscular function by recording electrical activity generated during muscle contraction. It provides valuable insight into muscle recruitment patterns and fatigue by analyzing changes in signal parameters such as median frequency (MF) and root mean square (RMS) amplitude (2). During sustained isometric contractions, muscle fatigue is typically accompanied by a decrease in MF and an increase in RMS amplitude, indicating changes in motor unit firing and muscle fiber conduction velocity (3,4).

Athletes generally exhibit enhanced muscle endurance and fatigue resistance due to physiological adaptations from training, such as increased oxidative capacity, improved neuromuscular coordination, and altered motor unit recruitment strategies (5). In contrast, non-athletes, who lack systematic conditioning, may demonstrate faster onset of fatigue and altered sEMG patterns during exertion (6). Comparing the fatigue responses in these populations can provide a better understanding of how training influences neuromuscular efficiency.

This study aims to evaluate and compare muscle fatigue patterns during isometric contractions in athletes and non-athletes using sEMG analysis. By observing differences in MF and RMS values, the research seeks to highlight the effectiveness of sEMG as a diagnostic and performance-assessment tool in both clinical and sports settings.

Study Design and Participants
This was a cross-sectional observational study conducted to evaluate muscle fatigue patterns using surface electromyography (sEMG) in two distinct groups: athletes and non-athletes. A total of 40 healthy male participants, aged between 18 and 30 years, were recruited. The athlete group (n=20) consisted of individuals engaged in regular competitive sports training for a minimum of three years, at least five days a week. The non-athlete group (n=20) included individuals with sedentary lifestyles and no formal physical training history.

Inclusion and Exclusion Criteria
Participants were included if they were free from any neuromuscular or orthopedic conditions and had no history of upper limb injuries in the past six months. Individuals on medications affecting muscle function or with contraindications for sustained physical exertion were excluded.

Electromyography Procedure
Surface electromyography signals were recorded from the biceps brachii of the dominant arm. Prior to electrode placement, the skin was cleaned with alcohol swabs to reduce impedance. Disposable Ag/AgCl surface electrodes were positioned in a bipolar configuration with an inter-electrode distance of 20 mm, aligned along the muscle fibers.

Isometric Contraction Protocol
Each participant underwent a maximum voluntary contraction (MVC) test using a standardized arm curl setup with a digital force gauge. Following a 5-minute rest period, participants performed an isometric contraction at 60% of their MVC for 60 seconds while sEMG signals were continuously recorded. Standardized verbal encouragement was provided to ensure maximal effort throughout the task.

Data Acquisition and Analysis
sEMG signals were captured using a multichannel EMG system with a sampling frequency of 1000 Hz and band-pass filtered between 20–450 Hz. The acquired signals were processed using custom MATLAB scripts. Median frequency (MF) and root mean square (RMS) values were computed in 5-second intervals. The slope of MF decline and the percentage increase in RMS amplitude were calculated to quantify muscle fatigue.

Statistical Analysis
Data were analyzed using SPSS version 25. Descriptive statistics were presented as mean ± standard deviation. Independent sample t-tests were used to compare MF and RMS parameters between athletes and non-athletes. A p-value of <0.05 was considered statistically significant.

A total of 40 participants (20 athletes and 20 non-athletes) successfully completed the study protocol. Surface EMG data were analyzed to compare the rate of muscle fatigue during isometric contraction between both groups using two primary indicators: median frequency (MF) decline and root mean square (RMS) amplitude increase.

Median Frequency (MF) Analysis

The athletes demonstrated a slower decline in MF over the 60-second contraction period compared to the non-athletes. The mean slope of MF reduction was −0.42 ± 0.08 Hz/sec in the athlete group and −0.87 ± 0.11 Hz/sec in the non-athlete group. This difference was statistically significant (p = 0.001), indicating higher fatigue resistance in athletes (Table 1).

Root Mean Square (RMS) Amplitude

The RMS amplitude showed a progressive increase during the isometric task, reflecting muscle fatigue development. The percentage increase in RMS from the start to the end of the contraction was significantly lower in athletes (16.3% ± 2.4%) compared to non-athletes (28.9% ± 3.1%), with a p-value of 0.002 (Table 2).

Summary of sEMG Parameters

Table 3 provides a combined summary of MF and RMS changes during the isometric contraction task in both groups. Athletes consistently exhibited lower fatigue indicators than non-athletes.

Table 1: Comparison of Median Frequency Decline Between Groups

Table 2: RMS Amplitude Changes during Isometric Contraction

Table 3: Summary of sEMG Parameters

As shown in Tables 1 and 2, both MF and RMS parameters reveal a statistically significant difference between athletes and non-athletes, with athletes displaying greater muscular endurance and neuromuscular efficiency during sustained isometric 

The present study investigated muscle fatigue characteristics during isometric contraction using surface electromyography (sEMG) in athletes and non-athletes. Findings from this research demonstrated that athletes exhibit a significantly slower decline in median frequency (MF) and a lower increase in root mean square (RMS) amplitude compared to non-athletes, indicating superior fatigue resistance and neuromuscular efficiency.

Muscle fatigue, especially during sustained isometric activity, is influenced by both central and peripheral mechanisms involving changes in motor unit recruitment, muscle fiber conduction velocity, and metabolic byproducts (1,2). The decline in MF observed in sEMG is a reliable indicator of reduced muscle fiber conduction velocity, which is a hallmark of peripheral fatigue (3). Athletes in this study showed a less steep MF decline, which aligns with previous findings suggesting that trained individuals have enhanced oxidative capacity and delayed onset of fatigue due to efficient neuromuscular adaptations (4,5).

The observed increase in RMS amplitude among non-athletes reflects an increased recruitment of additional motor units to maintain force output during fatigue, a typical response in untrained individuals (6). This compensatory mechanism results in greater muscle activation, often interpreted as inefficiency in force maintenance (7). In contrast, athletes maintain performance with lower RMS increases, likely due to optimized motor unit synchronization and firing rates (8).

These findings are supported by earlier studies demonstrating that resistance and endurance training lead to physiological adaptations such as increased capillary density, mitochondrial content, and fatigue resistance (9,10). Furthermore, sports training is associated with improved neuromuscular control, which may explain the more stable sEMG patterns observed in athletes during fatiguing tasks (11).

Comparative studies using sEMG have consistently shown that trained individuals have a slower decrease in MF during sustained contractions across various muscle groups, including the biceps brachii and quadriceps (12,13). The difference in RMS behavior between groups in our study echoes similar patterns seen in literature, where lower RMS increments in athletes have been attributed to better motor unit economy (14).

From a practical standpoint, sEMG serves as a valuable tool in performance assessment and rehabilitation. It allows non-invasive monitoring of fatigue progression, which is crucial for designing personalized training regimens and preventing overuse injuries (15). For non-athletes or sedentary individuals, monitoring RMS and MF changes could aid in identifying early fatigue onset and in customizing gradual resistance training programs.

Limitations:

This study include its cross-sectional nature and the limited sample size, which may affect the generalizability of the results. Additionally, only the biceps brachii was assessed; future studies should explore multiple muscle groups and dynamic contractions for broader applicability.

In conclusion, the current study confirms that athletes possess greater resistance to muscle fatigue during isometric tasks compared to non-athletes, as evidenced by distinct sEMG patterns. These results underscore the impact of regular training on neuromuscular performance and support the use of sEMG as an effective tool for evaluating fatigue.

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