***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: The purpose of this study was to determine the effect of an acute static stretching bout of the biceps brachii on torque , electromyography ( EMG ) , and mechanomyography ( MMG )  during concentric isokinetic muscle actions . Eighteen ( men , n = 10 ; women , n = 8) adult subjects ( M ± SD age = 22.7 ± 2.8 years ; weight = 78.0 ± 17.0 kg ; height = 177.9 ± 11.0 cm ) performed maximal isokinetic ( 30 and 270 ° ·s−1 ) forearm flexion strength testing on 2 occasions while EMG and MMG were recorded . Subjects were r and omly assigned to stretching ( STR ) or nonstretching ( NSTR ) protocol s before strength testing . Two-way ANOVAs with repeated measures revealed significantly ( p ≤ 0.05 ) greater torque for NSTR ( M ± SEM = 36.9 ± 3.3 N·m ) vs. STR ( 35.2 ± 3.3 N·m ) , significantly greater MMG amplitude for STR vs. NSTR for 30 ° ·s−1 ( STR = 93.5 ± 14.4 mV ; NSTR = 63.1 ± 10.6 mV ) and 270 ° ·s−1 ( STR = 207.6 ± 35.6 mV ; NSTR = 136.4 ± 31.7 mV ) , and no difference in EMG amplitude . These results indicate that a greater ability to produce torque without prior stretching is related to the musculotendinous stiffness of the muscle rather than the number of motor units activated . This suggests that performing activities that reduce muscle stiffness ( such as stretching ) , may be detrimental to performance The goal of this study was to demonstrate the feasibility of using artificial neural network ( ANN ) models to estimate the elbow flexion forces from mechanomyography ( MMG ) under isometric muscle contraction and compare the performance of the ANN models with the performance from multiple linear regression ( MLR ) models . Five participants ( mean±SD age=25.4±2.96 yrs ) performed ten predefined and ten r and omly ordered elbow flexions from 0 % to 80 % maximal voluntary contractions ( MVCs ) . The  MMG signals  were recorded from the biceps brachii ( BR ) and brachioradialis ( BRD ) , both of which contribute to elbow flexion . Inputs into the model included the root-mean-square ( RMS ) , a temporal characterization feature , which result ed in a slightly higher signal-to-noise ratio ( SNR ) than when using the mean absolute value ( MAV ) , and the zero-crossing ( ZC ) as spectral characterization features . Additionally , how the RMS and the ZC as model inputs affected the estimation accuracy was investigated . A cross-subject validation test was performed to determine if the established model of one subject could be applied to another subject . It was observed that the ANN model provided a more accurate estimation based on the values of the normalized root mean square error ( NRMSE=0.141±0.023 ) and the cross-correlation coefficient ( CORR=0.883±0.030 ) than the estimations from the MLR model ( NRMSE=0.164±0.030 , CORR=0.846±0.033 ) . The estimation results from the same-subject validation test were significantly better than those of the cross-subject validation test . Thus , using an ANN model on a subject-by-subject basis to quantify and track changes in the temporal and spectral responses of MMG signals to estimate the elbow flexion force is a reliable method The purpose of this investigation was to determine the mechanomyographic ( MMG ) and electromyographic ( EMG ) amplitude and mean power frequency ( MPF ) versus torque relationships during isokinetic muscle actions of the biceps brachii . Twelve adults [ mean ( SD ) age , 22.2 ( 2.7 ) years ] performed submaximal to maximal isokinetic muscle actions of the dominant forearm flexors . Following determination of isokinetic peak torque ( PT ) , the subjects r and omly performed submaximal muscle actions in 20 % increments from 20 % to 80 % PT . Polynomial regression analyses indicated linear increases in both MMG ( r2=0.984 ) and EMG ( r2=0.988 ) amplitude to 100 % PT . There were no significant ( P>0.05 ) relationships , however , for MMG and EMG MPF versus isokinetic torque . The results demonstrated similar responses for MMG and EMG in both the time and frequency domains . These findings suggested that simultaneous examination of MMG and EMG amplitude and MPF may be useful for describing the unique motor control strategies that modulate dynamic torque production . Furthermore , the results indicated that dynamic muscle actions can be used when applying techniques that require a linear EMG amplitude versus torque relationship Purpose To determine whether mechanomyographic ( MMG ) determined contractile properties of the biceps brachii change during exercise-induced hypertrophy and subsequent disuse atrophy . Methods Healthy subjects ( mean ± SD , 23.7 ± 2.6 years , BMI 21.8 ± 2.4 , n = 19 ) performed unilateral biceps curls ( 9 sets × 12 repetitions , 5 sessions per week ) for 8 weeks ( hypertrophic phase ) before ceasing exercise ( atrophic phase ) for the following 8 weeks ( non-dominant limb ; treatment , dominant limb ; control ) . MMG measures of muscle contractile properties ( contraction time ; Tc , maximum displacement ; Dmax , contraction velocity ; Vc ) , electromyographic ( EMG ) measures of muscle fatigue ( median power frequency ; MPF ) , strength measures ( maximum voluntary contraction ; MVC ) and measures of muscle thickness ( ultrasound ) were obtained . Results Two-way repeated measures ANOVA showed significant differences ( P < 0.05 ) between treatment and control limbs . During the hypertrophic phase treatment MVC initially declined ( weeks 1–3 ) , due to fatigue ( decline in MPF ) , followed by improvement against control during weeks 6–8 . Between weeks 5 and 8 treatment , muscle thickness was greater than control , reflecting gross hypertrophy . MMG variables Dmax ( weeks 2 , 7 ) and Vc ( weeks 7 , 8) declined . During the atrophic phase , MVC ( weeks 9–12 ) and muscle thickness ( weeks 9 , 10 ) initially remained high before declining to control levels , reflecting gross atrophy . MMG variables Dmax ( weeks 9 , 14 ) and Vc ( weeks 9 , 14 , 15 ) also declined during the atrophic phase . No change in Tc was found throughout the hypertrophic or atrophic phases . Conclusions MMG detects changes in contractile properties during stages of exercise-induced hypertrophy and disuse atrophy suggesting its applicability as a clinical tool in musculoskeletal rehabilitation The purpose of this study was to compare a piezoelectric contact sensor with an accelerometer for measuring the mechanomyographic ( MMG ) signal from the biceps brachii during submaximal to maximal isokinetic and isometric forearm flexion muscle actions . Following determination of isokinetic peak torque ( PT ) and the isometric maximum voluntary contraction ( MVC ) , 10 adults ( mean+/-SD age=22.8+/-2.7yrs ) performed r and omly ordered , submaximal step muscle actions of the dominant forearm flexors in 20 % increments from 20 % to 80 % PT and MVC . Surface MMG signals were recorded simultaneously from a contact sensor and an accelerometer placed over the belly of the biceps brachii muscle . During the isokinetic and isometric muscle actions , the contact sensor and accelerometer result ed in linear increases in normalized MMG amplitude with torque ( r(2 ) range=0.84 - 0.97 ) but the linear slope of the normalized MMG amplitude versus isokinetic torque relationship for the accelerometer was less ( p<0.10 ) than that of the contact sensor . There was no significant ( p>0.05 ) relationship for normalized MMG mean power frequency ( MPF , % max ) versus isokinetic and isometric torque for the contact sensor , but the accelerometer demonstrated a quadratic ( R(2)=0.94 ) or linear ( r(2)=0.83 ) relationship for the isokinetic and isometric muscle actions , respectively . There were also a number of significant ( p<0.05 ) mean differences between the contact sensor and accelerometer for normalized MMG amplitude or MPF values . These findings indicated that in some cases involving dynamic and isometric muscle actions , the contact sensor and accelerometer result ed in different torque-related responses that may affect the interpretation of the motor control strategies involved The aim of this study was to analyse the trends of the first three power spectral moments of the  mechanomyogram ( MMG ) signal recorded by a microphone ( MMGMIC ) and an accelerometer ( MMGACC ) during sustained contractions .  MMG signals  were recorded from the biceps brachii muscle in 14 healthy male subjects during a 3 min isometric elbow flexion at 30 % of the maximal voluntary contraction . MMG absolute and normalised root mean square ( RMS ) , mean power frequency ( MNF ) , power spectral variance ( Mc2 ) , and skewness ( μ3 ) were computed . For both MMGMIC and MMGACC , absolute and normalised RMS and Mc2 increased while MNF and μ3 decreased with contraction time ( P<0.001 ) . The rates of change of RMS over time were significantly correlated ( P<0.001 ) for MMGMIC and MMGACC but not correlated for spectral moments . The coefficient of variation of RMS was higher for MMGMIC than for MMGACC , while the opposite was observed for μ3 ( P<0.05 ) . It was concluded that higher order spectral moments of the MMG signal change during sustained contraction , indicating a complex modification of the shape of the power spectrum and not just scaling of the b and width . This is most likely due to the additional motor unit recruitment with fatigue and to the non-linear summation of motor unit contributions to the signal . Moreover , the characteristics of MMG signals recorded with microphones and accelerometers have important differences , which should be taken into account when comparing results from different studies The purpose of the study was to verify , by means of torque and mechanomyogram ( MMG ) compared analysis , the validity of MMG as a tool to investigate the contractile changes due to localized muscular fatigue induced by stimulation protocol s usually employed for sport training and rehabilitation programs . Ten healthy sedentary subjects participated in the study . Torque produced by the dominant biceps brachii ( BB ) and vastus lateralis ( VL ) during transcutaneous stimulated contractions has been recorded by a load cell strapped to the subjects ’ wrist and distal one-third of the tibia , respectively . MMG was detected over the muscle bellies during a monopolar supramaximal stimulation of the main motor point . After potentiation , the fatiguing stimulation was administered . It consisted of 50 cycles , with 2 s of 50 Hz and 25 s of 2 Hz . Averaged normalized values of peak torque ( pT ) and MMG peak-to-peak ( MMG-pp ) of the subjects group decreased from their initial 100 % values to 55 % ( pT ) and 60 % ( MMG-pp ) for BB and to 43 % ( pT ) and 47 % ( MMG-pp ) for VL . The pT% and MMG-pp% changes throughout the stimulation protocol presented high correlation ( BB : R=0.95 , P<0.001 ; VL : R=0.94 , P<0.001 ) . This correlation suggests that MMG could be used to follow muscle mechanical fatigue development when torque output is not or hardly detectable such as during electrical stimulation programs employed for sport training or rehabilitation protocol The purpose of this investigation was to determine the mechanomyographic ( MMG ) amplitude and mean power frequency ( MPF ) versus torque ( or force ) relationships during isokinetic and isometric muscle actions of the biceps brachii . Ten adults ( mean + /- SD age = 21.6 + /- 1.7 years ) performed submaximal to maximal isokinetic and isometric muscle actions of the dominant forearm flexors . Following determination of isokinetic peak torque ( PT ) and the isometric maximum voluntary contraction ( MVC ) , the subjects r and omly performed submaximal step muscle actions in 10 % increments from 10 % to 90 % PT and MVC . Polynomial regression analyses indicated that MMG amplitude increased linearly with torque during both the isokinetic ( r2 = 0.982 ) and isometric ( r2 = 0.956 ) muscle actions . From 80 % to 100 % of isometric MVC , however , MMG amplitude appeared to plateau . Cubic models provided the best fit for the MMG MPF versus isokinetic ( R2 = 0.786 ) and isometric ( R2 = 0.940 ) torque relationships , although no significant increase in MMG MPF was found from 10 % to 100 % of isokinetic PT . For the isometric muscle actions , however , MMG MPF remained relatively stable from 10 % to 50 % MVC , increased from 50 % to 80 % MVC , and decreased from 80 % to 100 % MVC . The results demonstrated differences in the MMG amplitude and MPF versus torque relationships between the isokinetic and isometric muscle actions . These findings suggested that the time and frequency domains of the MMG signal may be useful for describing the unique motor control strategies that modulate dynamic versus isometric torque production Force ( F ) reduction is reported with myotendinous junction ( MTJ ) manipulation . Autogenic inhibition reflex ( AIR ) activation is supposed to be the main mechanism . Still , its role remains unclear . The study aim ed at assessing the effects of MTJ direct inhibitory pressure ( DIP ) on neuromuscular activation and F in the elbow flexor ( agonist ) and 
    Output:
    
The review affirms that - 1 ) MMG is suitable for skeletal muscle activity assessment and can be employed potentially for further investigation of the BB muscle activity and condition ( e.g. , force , torque , fatigue , and contractile properties ) , 2 ) a majority of the records focused on static contractions of the BB , and the analysis of dynamic muscle contractions using MMG is thus a research gap , and 3 ) very few studies have focused on the analysis of BB muscle activity under externally stimulated contractions .
Taken together , the findings of this review on BB activity assessment using MMG affirm the potential of MMG as an alternative tool