Back extensor muscle fatigue at submaximal workloads assessed using frequency banding of the electromyographic signal

Cardozo, Adalgiso Coscrato; Gonçalves, Mauro; Dolan, Patricia

doi:10.1016/j.clinbiomech.2011.06.001

Cited by 22 publications

(17 citation statements)

References 23 publications

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“…This finding was in good agreement with previous, in frequency domain, studies which had hypothesized that decrease in median frequency signifies onset of muscle fatigue and was associated with the negative slope of the regression line [24][25][26][27]. Unlike our frequency domain analysis, other investigators used different approaches, such as time domain analysis, found that fatigue occurred when time domain parameters such as mean amplitude and root mean square (RMS) amplitude increased [28,29].…”

Section: Rwl (Kg)supporting

confidence: 92%

Muscle Fatigue Estimation in Repetitive Lifting Task Using Surface Electromyography-Based Analysis

Spyropoulos¹,

Chroni²,

Athanassiou

2015

Ergonomics

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Section: Rwl (Kg)supporting

confidence: 92%

Muscle Fatigue Estimation in Repetitive Lifting Task Using Surface Electromyography-Based Analysis

Spyropoulos¹,

Chroni²,

Athanassiou

2015

Ergonomics

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“…This approach has been used successfully on limb muscles [18,19] and muscles in the upper back [16]. Studies of the lower back muscles have reported changes in surface muscle electromyography signals and force development as indices of fatigue/endurance [4,5]. EMG has been previously used to monitor fatigue in various muscles, but measures of muscle activation are an indirect measure of muscle performance and do not always correlate with force development or movement.…”

Section: Discussionmentioning

confidence: 99%

“…While fatigue of lower back muscles has been implicated or associated with lower back pain, the fatigability of these muscles is difficult to assess. Fatigue of the lower back muscles has been evaluated using performance tests [3], changes in muscle electromyography signals [4,5], and by other innovative approaches [6,7]. However, all of these previous approaches are considered to have methodological limitations [8].…”

Section: Introductionmentioning

confidence: 99%

Muscle-Specific Endurance of the Lower Back Erectors Using Electrical Twitch Mechanomyography

McCully

Moraes

Patel

et al. 2019

JFMK

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Lower back pain is a common symptom potentially associated with skeletal muscle dysfunction. The purpose of this study was to evaluate endurance in the lower back muscles of healthy participants using accelerometer-based mechanomyography. Methods: Young healthy subjects (N = 7) were tested. Surface electrodes and a tri-axial accelerometer were placed over the erector spinae muscle along the T11-L1 Vertebrae. Stimulation was for 3 min each at 2, 4, and 6 Hz, and changes in acceleration were used to calculate an endurance index (EI). Reproducibility of the endurance index measurements was tested on two separate days. Wrist flexor and vastus lateralis muscles were tested for comparison. Near Infrared Spectroscopy (NIRS) was used to measure muscle oxygen levels (O 2 Hb) (N = 5).

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“…Of the various measures of the power spectrum, median frequency (MF) and mean power frequency (MPF) are especially useful [1,7]. Other measures of the power spectrum that convey crucial information are, e.g., the first and third quartiles, standard deviation and skewness [8] and bands of the power spectrum [9,10].…”

Section: Introductionmentioning

confidence: 99%

Influence of type of MVC test on electromyography measures of biceps brachii and triceps brachii

Roman-Liu

Bartuzi

2017

International Journal of Occupational Safety and Ergonomics

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Objective. This study aimed to investigate the amplitude and frequency measures of the electromyography (EMG) signal in agonistic and antagonistic muscles (biceps brachii, triceps brachii). Methods. Fifteen males (22.9 ± 2.1 years old) took three isometric maximum voluntary contraction (MVC) tests. Two tests were typical MVC tests for biceps brachii and triceps brachii. The third was a test often used to obtain MVC for forearm muscles (arm and forearm hanging down). The EMG signal was recorded during three isometric MVC muscle contractions and during a relaxation test. Results. There were no differences in amplitude between relaxation and MVC antagonist in static contraction, with higher values for frequency measures in relaxation. When biceps brachii and triceps brachii act as antagonists in an MVC test, frequency measures present lower values than when the muscles act as agonists. Biceps brachii shows much lower amplitude than during an agonist MVC contraction with similar spectral measures. Triceps brachii presents much higher values of spectral measures than during an agonist MVC test. Conclusion. The type of exerted force, i.e., if a muscle acted as an agonist, antagonist or stabilizer, affects the relationship between the time and frequency domain measures.

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Back extensor muscle fatigue at submaximal workloads assessed using frequency banding of the electromyographic signal

Cited by 22 publications

References 23 publications

Muscle Fatigue Estimation in Repetitive Lifting Task Using Surface Electromyography-Based Analysis

Muscle Fatigue Estimation in Repetitive Lifting Task Using Surface Electromyography-Based Analysis

Muscle-Specific Endurance of the Lower Back Erectors Using Electrical Twitch Mechanomyography

Influence of type of MVC test on electromyography measures of biceps brachii and triceps brachii

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