Cross-Talk in Mechanomyographic Signals from the Forearm Muscles during Sub-Maximal to Maximal Isometric Grip Force

“…Nevertheless, for an improved signal integrity, the standard practice include the use of double sided adhesive tape to fix the MMG's sensor to the skin in order to ensure a constant pressure. Isolation of irrelevant muscles through an experimental setup on standard testing devices such as custom made or commercially available dynamometers has been suggested to limit the yet unavoidable effects of cross-talk [ 43 ].…”

Section: Technical Characteristics Of Mmg Sensors Selection Criteriamentioning

confidence: 99%

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

Ibitoye

Hamzaid

Zúñiga

et al. 2014

Sensors

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The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.

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“…The data stored on a personal computer were first digitally bandpass filtered (fourth order Butterworth) at 5–100 Hz to obtain the MMG signals, and the MMG signals from the 2 seconds corresponding to the middle 33% of each 6 second isometric contraction were then extracted to remove the effect of signal transition, as recommended by 38 . The dominant power in MMG frequency spectrum was found outside the tremor range (5–12 Hz) 25 . The power density spectra of MMG signal from the three muscles of a subject performing forearm flexion, pronation and supination tasks are shown in Fig.…”

Section: Methodsmentioning

confidence: 96%

“…The authors found a weak negative correlation between these parameters measured from the biceps brachii (BB) using an accelerometer during isometric contractions. The correlation between the forearm circumference and CT in MMG signals was quantified by 25 during an isometric grip force task and was found to be weakly positive. Similarly, the effect of variations in the forearm circumference on CT in sEMG signals was also discussed by 26 .…”

Section: Introductionmentioning

confidence: 99%

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Association of anthropometric parameters with amplitude and crosstalk of mechanomyographic signals during forearm flexion, pronation and supination torque tasks

Talib

Sundaraj

Lam

2019

Sci Rep

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This study aimed to quantify the association of four anthropometric parameters of the human arm, namely, the arm circumference (CA), arm length (LA), skinfold thickness (ST) and inter-sensor distance (ISD), with amplitude (RMS) and crosstalk (CT) of mechanomyography (MMG) signals. Twenty-five young, healthy, male participants were recruited to perform forearm flexion, pronation and supination torque tasks. Three accelerometers were employed to record the MMG signals from the biceps brachii (BB), brachialis (BRA) and brachioradialis (BRD) at 80% maximal voluntary contraction (MVC). Signal RMS was used to quantify the amplitude of the MMG signals from a muscle, and cross-correlation coefficients were used to quantify the magnitude of the CT among muscle pairs (BB & BRA, BRA & BRD, and BB & BRD). For all investigated muscles and pairs, RMS and CT showed negligible to low negative correlations with CA, LA and ISD (r = −0.0001-−0.4611), and negligible to moderate positive correlations with ST (r = 0.004-0.511). However, almost all of these correlations were statistically insignificant (p > 0.05). These findings suggest that RMS and CT values for the elbow flexor muscles recorded and quantified using accelerometers appear invariant to anthropometric parameters. conclusion CA, LA and ISD were found to exhibit negligible to low negative correlations with RMS and CT, whereas ST exhibited negligible to moderate positive correlations with RMS and CT. These findings suggest that the MMG signal parameters and CT acquired using accelerometers appear invariant to the four anthropometric parameters but might depend on other physiological and subject-based factors. The findings obtained in this study might aid our understanding of CT mechanisms in MMG signals, which could be useful in future research for devising techniques for the reduction or removal of CT in MMG.

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Cross-Talk in Mechanomyographic Signals from the Forearm Muscles during Sub-Maximal to Maximal Isometric Grip Force

Cited by 25 publications

References 19 publications

Analysis of crosstalk in the mechanomyographic signals generated by forearm muscles during different wrist postures

Analysis of crosstalk in the mechanomyographic signals generated by forearm muscles during different wrist postures

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

Association of anthropometric parameters with amplitude and crosstalk of mechanomyographic signals during forearm flexion, pronation and supination torque tasks

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