System identification of the mechanomyogram from single motor units during voluntary isometric contraction

Uchiyama, Takanori; Hashimoto, Erika

doi:10.1007/s11517-011-0752-0

Cited by 17 publications

(25 citation statements)

References 10 publications

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“…The analysis we employed was similar to that in the authors' previous studies [5], [7]. Here, we briefly outline the method.…”

Section: Discussionmentioning

confidence: 99%

“…We expected the model order at low recruitment level to be fifth and that at high recruitment level to be fourth because the MMG from the single motor unit was approximated with the fifth-order model [7] and the induced MMG from parallel muscle was with the fourth-order model [6]. The decrease of the model order as the recruitment level increased can be explained based on Hill's model.…”

Section: Discussionmentioning

confidence: 99%

“…The method of recording the MMG from a single motor unit was similar to that of the authors' previous study [7], while the target muscle differed. Each participant sat on a chair, with his right hand in the horizontal plane.…”

Section: Mmg Of Single Motor Unitmentioning

confidence: 97%

“…In these studies, the transfer function was identified using the MMGs induced by supramaximal electrical stimulation. On the other hand, the transfer function identified from an acceleration MMG of a single motor unit of the anconeus muscle was approximated with a fifth-order model [7]. The differences of the model orders suggest that the recruitment level could also have an effect on the model order, but this has not been verified.…”

Section: Introductionmentioning

confidence: 99%

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System Identification of Mechanomyogram at Various Levels of Motor Unit Recruitment

Uchiyama

Tamura

2014

SICE Journal of Control, Measurement, and System Integration

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: The mechanomyogram from a single motor unit and the induced mechanomyogram at various levels of recruitment were measured with an acceleration sensor. The transfer functions between motor unit action potential (or electrical stimulation) and the mechanomyogram were identified using the singular value decomposition method. The purpose of this study is to clarify how the model order of the transfer function depends on the recruitment level. The second-to tenth-order transfer functions were calculated, and the difference between the observed and the estimated mechanomyograms using the transfer function, the fitness, was calculated. The relationship between the model order and the fitness was tested using the Holm-Bonferroni multiple comparison. At low levels (single motor unit, 20, and 40%) of recruitment, there were significant differences between the fourth-and higher-order models, but there were no significant differences between the fifth-and higher-order models. In contrast, at high levels (60, 80, and 100%) of recruitment, the fourth-order model did not show significant differences between the fifth-or higher-order models. As a result, the fifthand fourth-order models were appropriate at low and high recruitment levels, respectively. The differences in the order might be caused by interactions between active and resting motor units.

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“…The analysis we employed was similar to that in the authors' previous studies [5], [7]. Here, we briefly outline the method.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Mmg Of Single Motor Unitmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

System Identification of Mechanomyogram at Various Levels of Motor Unit Recruitment

Uchiyama

Tamura

2014

SICE Journal of Control, Measurement, and System Integration

Self Cite

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“…The spectral content may be represented by four major indicators: (i) the mean power frequency (MPF) (Merletti and Parker, 2004) that is the average value of the power spectral density (Søgaard et al, 2012;Tarata et al, 2001;Uchiyama and Hashimoto, 2011;Zuniga et al, 2010Zuniga et al, , 2011; (ii) Mc 2 , a dispersion index, which represents the variance of the power spectral density; (iii) µ3 (Madeleine et al, 2006), which uses MPF to determine the skewness (Lee et al, 2011) of the spectrum; and (iv) the kurtosis index (Lee et al, 2011) that reflects the kurtosis of the power spectral density.…”

Section: Signal Acquisition Processing and Analysismentioning

confidence: 99%

Advances and perspectives of mechanomyography

Krueger

Scheeren

Nogueira-Neto

et al. 2014

Rev. Bras. Eng. Bioméd.

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Introduction: The evaluation of muscular tissue condition can be accomplished with mechanomyography (MMG), a technique that registers intramuscular mechanical waves produced during a fi ber's contraction and stretching that are sensed or interfaced on the skin surface. Objective: Considering the scope of MMG measurements and recent advances involving the technique, the goal of this paper is to discuss mechanomyography updates and discuss its applications and potential future applications. Methods: Forty-three MMG studies were published between the years of 1987 and 2013. Results: MMG sensors are developed with different technologies such as condenser microphones, accelerometers, laser-based instruments, etc. Experimental protocols that are described in scientifi c publications typically investigated the condition of the vastus lateralis muscle and used sensors built with accelerometers, third and fourth order Butterworth fi lters, 5-100Hz frequency bandpass, signal analysis using Root Mean Square (RMS) (temporal), Median Frequency (MDF) and Mean Power Frequency (MPF) (spectral) features, with epochs of 1 s. Conclusion: Mechanomyographic responses obtained in isometric contractions differ from those observed during dynamic contractions in both passive and functional electrical stimulation evoked movements. In the near future, MMG features applied to biofeedback closed-loop systems will help people with disabilities, such as spinal cord injury or limb amputation because they may improve both neural and myoelectric prosthetic control. Muscular tissue assessment is a new application area enabled by MMG; it can be useful in evaluating the muscular tonus in anesthetic blockade or in pathologies such as myotonic dystrophy, chronic obstructive pulmonary disease, and disorders including dysphagia, myalgia and spastic hypertonia. New research becomes necessary to improve the effi ciency of MMG systems and increase their application in rehabilitation, clinical and other health areas.

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Influence of age on force and re-lengthening dynamics after tetanic stimulation withdrawal in the tibialis anterior muscle

et al. 2023

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Purpose During alternate movements across a joint, the changeover from one direction of rotation to the opposite may be influenced by the delay and rate of tension reduction and the compliance to re-lengthening of the previously active muscle group. Given the aging process may affect the above-mentioned factors, this work aimed to compare the dynamics of both the ankle torque decline and muscle re-lengthening, mirrored by mechanomyogram (MMG), in the tibialis anterior because of its important role in gait. Methods During the relaxation phase, after a supramaximal 35 Hz stimulation applied at the superficial motor point, in 20 young (Y) and 20 old (O) subjects, the torque (T) and MMG dynamics characteristics were measured. Results The T and MMG analysis provided: (I) the beginning of the decay after cessation of stimulation (T: 22.51 ± 5.92 ms [Y] and 51.35 ± 15.21 ms [O]; MMG: 27.38 ± 6.93 ms [Y] and 61.41 ± 18.42 ms [O]); (II) the maximum rate of reduction (T: − 110.4 ± 45.56 Nm/s [Y] and − 52.72 ± 32.12 Nm/s [O]; MMG: − 24.47 ± 10.95 mm/s [Y] and − 13.76 ± 6.54 mm/s [O]); (III) the muscle compliance, measuring the MMG reduction of every 10% reduction of torque (bin 20–10%: 15.69 ± 7.5[Y] and 10.8 ± 3.3 [O]; bin 10–0%: 22.12 ± 10.3 [Y] and 17.58 ± 5.6 [O]). Conclusion Muscle relaxation results are different in Y and O and can be monitored by a non-invasive method measuring physiological variables of torque and re-lengthening dynamics at the end of the electromechanical coupling previously induced by the neuromuscular stimulation.

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System identification of the mechanomyogram from single motor units during voluntary isometric contraction

Cited by 17 publications

References 10 publications

System Identification of Mechanomyogram at Various Levels of Motor Unit Recruitment

System Identification of Mechanomyogram at Various Levels of Motor Unit Recruitment

Advances and perspectives of mechanomyography

Influence of age on force and re-lengthening dynamics after tetanic stimulation withdrawal in the tibialis anterior muscle

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