Comparing electromyographic and mechanomyographic frequency-based fatigue thresholds to critical torque during isometric forearm flexion

Hendrix, C. Russell; Housh, Terry J.; Camic, Clayton L.; Zúñiga, Jorge M.; Johnson, Glen O.; Schmidt, Richard J.

doi:10.1016/j.jneumeth.2010.07.006

Cited by 22 publications

(23 citation statements)

References 53 publications

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“…Eleven studies over twenty used an ACC to detect MMG signal [2,[16][17][18][89][90][91][92][93][94], seven used a PIZ [82,[95][96][97][98][99][100], and two utilized an MIC [101,102].…”

Section: Mmg and Fatiguementioning

confidence: 99%

“…Lastly, Hendrix et al [18], aiming to compare the mean torque levels derived from the critical torque and MMG MPF fatigue threshold (MPF FT ) during isometric forearm flexion muscle actions, found no correlations between the two parameters.…”

Section: Mmg and Fatiguementioning

confidence: 99%

“…The application fields of MMG are numerous and increasing: they span from the assessment of muscle function during isometric or dynamic contractions under different physiological conditions, such as fatigue [16][17][18], muscle temperature manipulation [19,20], stretching [21][22][23], ageing [24], training [25,26], to the analysis of the effects of rehabilitation programs [27,28], the development of prosthesis [29], and/or the use of the MMG as a triggering signal [30].…”

Section: Introductionmentioning

confidence: 99%

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Novel insights into skeletal muscle function by mechanomyography: from the laboratory to the field

2015

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Purpose The review aimed to provide a wider overview on the new application fields of MMG signal. A particular emphasis on measurements reliability and sensitivity was also given. Methods Five electronic databases were searched for eligible studies published between 2000 and 2014. Two authors assessed selected articles. Several domains (sensor types, participants' characteristics, experimental protocols, investigated muscle/s, measured parameters, and main results) were extracted for analysis. From a total of 1326 citations, 170 were selected for evaluation and 111 studies were identified. Results From the analysis of the literature it resulted that MMG signal (a) has a high level of reliability, especially for the parameters calculated during isometric contractions; (b) can be used to examine muscle mechanical activation and motor unit recruitment strategies under several types of exercise paradigms; (c) is influenced by the mechanical characteristics of cross-bridges and series elastic components, and may provide deeper insights into their behaviour under several physiological models; (d) could be a useful biomarker for triggering orthosis or multifunction access devices, and for the evaluation of patients presenting alterations in muscle function. Conclusions The MMG approach has been proficiently applied in several fields ascribable to both exercise physiology and clinical settings. This approach can provide deeper insights into muscle mechanical behaviour under several physiological models and for the evaluation of patients with altered muscle function.

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“…Eleven studies over twenty used an ACC to detect MMG signal [2,[16][17][18][89][90][91][92][93][94], seven used a PIZ [82,[95][96][97][98][99][100], and two utilized an MIC [101,102].…”

Section: Mmg and Fatiguementioning

confidence: 99%

Section: Mmg and Fatiguementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Novel insights into skeletal muscle function by mechanomyography: from the laboratory to the field

2015

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“…Currently, FFT of raw sEMG data and PSD summary statistics are utilized to assess localized muscle fatigue (Cifrek, Medved, Tonković, & Ostojić, 2009;Hendrix et al, 2010;Linnamo, Bottas, & Komi, 2000). In general, MPF or MdPF of raw sEMG data shifts to lower frequencies following the onset of muscle fatigue.…”

Section: Signal Processing Of Electromyography Datamentioning

confidence: 99%

Spectral Analysis of Root-Mean-Square Processed Surface Electromyography Data as a Measure of Repetitive Muscular Exertion

Gant¹,

Fethke²,

Gerr³

2012

PsycEXTRA Dataset

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Highly repetitive motion is associated with upper extremity musculoskeletal disorders (UEMSDs) among industrial workers, especially when encountered concurrently with forceful exertions. Current methods of estimating occupational exposure to "repetitiveness" provide information about the repetitiveness of joint motion, but fail to provide complete information about the repetitiveness of muscular exertion, a more biomechanically meaningful measure of repetition. This thesis introduces an innovative digital signal processing method, from which muscular exertion frequency was estimated. Specifically, time series recordings of muscle activity obtained with surface electromyography (sEMG) were processed with standard root-mean-square (RMS) amplitude calculations and then transformed from the time domain into the frequency domain. The mean power frequencies of the RMS-processed sEMG signals (MPF EMG ) were then calculated to estimate muscular exertion frequency.In a laboratory-based validation study involving repetitive isometric hand gripping exertions, MPF EMG was compared to established measures of muscular exertion frequency and joint motion frequency across a range of known exertion frequencies, exertion intensities (i.e. forces), and exertion durations (i.e., duty cycles). Strong linear relationships were observed between MPF EMG and external measures of muscular exertion frequency. However, performance of MPF EMG as a measure of muscular exertion frequency may be improved with an increase of the signal to noise ratio in the sEMG data. Signal processing parameters were therefore investigated and alternative techniques were explored. Alternative processing parameters were suggested to minimize difference between MPF EMG and established methods of muscular exertion frequency.A second laboratory-based validation study compared MPF EMG to an established measure of muscular exertion frequency and a widely-used measure of joint movement frequency during a simulated industrial task. Although a stronger linear relationship was observed between metrics of joint motion frequency and established measures of 2 muscular exertion, the differences between measures were not meaningful and the relationship between MPF EMG and established measures was moderate-to-strong.The final phase of this thesis explores the application of the newly proposed techniques to field-based data collected during a study of ironworkers involved in construction stud-welding tasks. Limitations in data collection limited the analysis of MPF EMG in this study.The research presented in this thesis introduces a novel metric based on the frequency analysis of RMS processed sEMG data, and presents evidence that MPF EMG has potential to be a valuable assessment technique of exposure to repetitive muscular exertion.Abstract Approved: _____________________________________ Thesis Supervisor

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“…Additionally, near-infrared spectroscopy (NIRS), in which the oxygen consumption by muscular activity is measured using photosensors, has been researched [3,5,15]. Moreover, multimodal systems using two types of sensors, such as EMG and MMG sensors or EMG and NIRS sensors, have been researched for more detailed analysis of muscular function [1,7,[9][10][11]24]. In the case of multimodal systems, it needs to be determined whether muscle activity is restricted by the several sensors in contact with the skin.…”

mentioning

confidence: 99%

A new layered sensor for simultaneous measurement of EMG, MMG and oxygen consumption at the same position

Kimoto

Yamada

2014

Med Biol Eng Comput

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A new layered sensor for simultaneous measurement of electromyography (EMG), mechanomyography (MMG) and oxygen consumption based on near-infrared spectroscopy (NIRS) at the same position of the muscle is presented. The proposed sensor is a layered structure of a thin stainless-steel electrode, a PVDF film with transparent electrodes and optical sensors. EMG, MMG and oxygen consumption based on NIRS are measured by the stainless-steel electrodes, PVDF film and optical sensors, respectively. Using the three types of data, muscular activity can be analyzed in more detail. Additionally, the proposed sensor system reduces the constraint of the sensors arranged on the skin in measurements at multiple points because three types of information, previously obtained with three types of general sensors, are detected by a pair of proposed sensors. In an experiment, simultaneous measurement of EMG, MMG and oxygen consumption via NIRS at the forearm was demonstrated using the proposed sensor under fluorescent light. The performance of the layered sensor was evaluated.

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Comparing electromyographic and mechanomyographic frequency-based fatigue thresholds to critical torque during isometric forearm flexion

Cited by 22 publications

References 53 publications

Novel insights into skeletal muscle function by mechanomyography: from the laboratory to the field

Novel insights into skeletal muscle function by mechanomyography: from the laboratory to the field

Spectral Analysis of Root-Mean-Square Processed Surface Electromyography Data as a Measure of Repetitive Muscular Exertion

A new layered sensor for simultaneous measurement of EMG, MMG and oxygen consumption at the same position

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