The effects of repetitive bouts of a fatiguing exertion (with breaks) on the slope of EMG measures of localized muscle fatigue

Sarker, Pramiti; Mirka, Gary A.

doi:10.1016/j.jelekin.2019.102382

Cited by 15 publications

(10 citation statements)

References 19 publications

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“…Localized muscle fatigue was evaluated by calculating the change in median frequency (MF) of the EMG spectrum to lower frequency (Lindstrom et al, 1970). Previously studies have confirmed that median frequency measures could be used as indicators of local muscle fatigue and showed a trend of decrease when muscles were fatigue (Li et al, 2014; Sarker & Mirka, 2020; Tetteh et al, 2020).…”

Section: Methodsmentioning

confidence: 82%

The effect of arm support and control modes on muscle fatigue, eye fatigue, and posture changes in mobile game use among young adults

Guo

Liu

et al. 2021

Hum Ftrs & Erg Mfg Svc

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Background The popularity of mobile gaming among adults has raised concerns about the adverse health effects of localized muscle and eye fatigue. This study aimed to investigate how arm support and mobile game control characteristics affect muscle and eye fatigue, and postural changes. Methods Twelve subjects, ages 21–24 years old, were recruited to play a mobile game for 60 min. Participants used two postures (sitting with and without arm support) and two game control modes (touch and rocker). Electromyography measured the abductor pollicis brevis, the upper trapezius, and the extensor carpi radialis muscles. A motion capture system was employed to assess postural changes. Self‐reported fatigue was measured using Borg's scale and Heuer's questionnaire. Results Arm support had a significant effect on muscle fatigue and posture, including a lower rating of perceived exertion in the shoulder (p < .05) and arm (p < .01), an increase in neck and trunk forward flexion between 22% and 34%, an increase in forearm bearing angle of 97.63%, and a decrease in upper arm bearing angle of 25.94% in the group without arm support. Blink for touch mode was 10.57% higher than for rocker mode. Conclusion Arm support was effective in reducing fatigue in the arm and shoulder, but not in the hand. Compared to rocker mode, touch mode increased the visual burden and accelerated visual fatigue. This study provides an understanding of the association between playing mobile games and fatigue, which can help prevent muscle and visual fatigue in mobile gaming.

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Section: Methodsmentioning

confidence: 82%

The effect of arm support and control modes on muscle fatigue, eye fatigue, and posture changes in mobile game use among young adults

Guo

Liu

et al. 2021

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

show abstract

“…That being said, there are moments where the subject managed to control the fatigue during the experiment, as shown in Figure 9 where the RMS value on both muscles decreased at certain ends. On the other hand, most researchers agreed that a decreased value of MDF on a muscles contraction shows that the muscles are experiencing fatigue [16][17][18]. In Table 1, there are several moments where the subject begins to experience fatigue on Supraspinatus such as during the 5 th end where the MDF value drop significantly to 6.45E-02 compared to 1.00E-01 on the 4 th end at Supraspinatus.…”

Section: Resultsmentioning

confidence: 99%

“…Statistical analyses such as Root Mean Square (RMS) and Median Frequency (MDF) were used in measuring muscle fatigue conditions, as recommended by Zhou et al [13]. Nur et al [14], and Ayaz et al [15], preferred RMS to analyze and interpret the data as RMS calculation gives the best insight on the amplitude of the EMG signal with a waveform that easily be interpreted while Sarker and Mirka [16], Mas'As et al [17], and Phinyomark et al [18] preferred MDF as it is frequently considered as the gold standard for muscle fatigue assessment with sEMG signal due to its versatility to analyze both static and dynamic muscle contraction. Alhaag et al [19], in their recent research, used both RMS and MDF to identify the fatigue associated with different task complexity during maintenance operations while Borges et al [20] also used these two statistical methods to find the fatigue level of novice and elite archers on flexor digitorum superficialis (FDS).…”

Section: Figure 1 Flow Chart Of Experiments Conductedmentioning

confidence: 99%

Investigation of muscle fatigue of the archer’s during endurance shooting

Hamdan

Ahmad@Manap²,

Johari³

2022

JMES

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Endurance of Drawing-Aim-Release (DAR) during the shooting process in archery will be causing the muscles to fatigue. Besides, the archer's inability to use the right muscles for DAR will lead to a muscle injury as well as dropping the performance. This study aims to monitor the localized muscle fatigue of an archer during the repetitive DAR and its effect to the archer’s performance. Wet electrode sensors were placed on the specific muscles that are heavily involved in DAR such as Muscle Extensor Digitorum (MED) on the archer's bow arm and the Supraspinatus muscle at the shoulder. In order to induce fatigue, the archer has shot 72 arrows continously in 2 rounds of set. The surface electromyography (sEMG) signals of the muscle contraction are recorded during the shooting for the post-processing analysis. Each score of the shooting was also recorded to correlate with the effect of muscle fatigue to the archer’s performance. The finding of this study is that the MED and Supraspinatus begin to fatigue toward the end of each shooting round. The Root Mean Square (RMS) and Median Frequency (MDF) values for both targeted muscles increased significantly during the 6th end compare to the 1st end. It is also found that there is no correlation between muscle fatigue on MED and Supraspinatus to the score obtained by the archer where the F value is lower than F-critical while Draw (1.9339), Aim (1.3754) and Release (0.6515) phases. In conclusion, this experiment benefits archers and coaches to identify which muscles are vigorously used during the DAR process and allows for precaution and prevention procedures.

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“…As such, we argue that it is a compelling relative metric to measure or identify properties in the muscle in response to fatigue, or anti-fatiguing, due to repetitive exercise. Thus, the change in the ratio with respect to time (i.e., the slope of EMG vs. time) can show changes to motor unit recruitment in the muscle over time ( 6 ).…”

Section: Methodsmentioning

confidence: 99%

“…Neuromuscular activity during muscle training has shown to be correlated to contraction response, specifically in the identification of motor recruitment changes and fatigue. Commonly used biopotential measurement systems such as surface electromyograms (EMG) have demonstrated use in these findings, specifically in identifying the patterns of contractile amplitudes and frequencies during a fatiguing exercise (1)(2)(3)(4)(5)(6). For example, fatiguing muscles show an increase in EMG contractile amplitude that correlates to the number of recruited motor neurons, as well as a low-frequency shift in the raw EMG signal (7)(8)(9)(10).…”

Section: Introductionmentioning

confidence: 99%

Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training

Stefanovic

Ramanarayanan²,

Karkera³

et al. 2022

Front. Rehabilit. Sci.

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An individual's long-term neuromuscular adaptation can be measured through time-domain analyses of surface electromyograms (EMG) in regular resistance-based training. The perceived changes in recruitment, such as those measured during muscle fatigue, can subsequently prolong the recovery time in rehabilitation applications. Thus, by developing quantifiable methods for measuring neuromuscular adaptation, adjuvant treatments applied during neurorehabilitation can be improved to reduce recovery times and to increase patient quality of care. This study demonstrates a novel time-domain analysis of long-term changes in EMG captured neuromuscular activity that we aim to use to develop a quantified performance metric for muscle-based intervention training and optimization of an individual. We measure EMG of endurance and hypertrophy-based resistance exercises of healthy participants over 100 days to identify trends in long-term neuromuscular adaptation. Particularly, we show that the rate of EMG amplitude increase (motor recruitment) is dependent on the training modality of an individual. Particularly, EMG decreases over time with repetitive training – but the rate of decrease is different in hypertrophy, endurance, and control exercises. We found that the EMG peak contraction decreases across all subjects, on average, by 8.23 dB during hypertrophy exercise and 10.09 dB for endurance exercises over 100 days of training, while control participants showed negligible change. This represents approximately 2 dB difference EMG activity when comparing endurance and hypertrophy exercises, and >8 dB change when comparing to our control cases. As such, we show that the slope of the long-term EMG activity is related to the resistance-based exercise. We believe this can be used to identify person-specific performance metrics, and to create optimized interventions using a measured performance baseline of an individual.

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The effects of repetitive bouts of a fatiguing exertion (with breaks) on the slope of EMG measures of localized muscle fatigue

Cited by 15 publications

References 19 publications

The effect of arm support and control modes on muscle fatigue, eye fatigue, and posture changes in mobile game use among young adults

The effect of arm support and control modes on muscle fatigue, eye fatigue, and posture changes in mobile game use among young adults

Investigation of muscle fatigue of the archer’s during endurance shooting

Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training

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