Repeatability of surface EMG variables during voluntary isometric contractions of the biceps brachii muscle

Rainoldi, Alberto; Galardi, Giuseppe; Maderna, Luca; Comi, Giancarlo; Conte, Loredana Lo; Merletti, Roberto

doi:10.1016/s1050-6411(98)00042-x

Cited by 167 publications

(154 citation statements)

References 40 publications

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“…Indeed, in spite of a similar decline of EMG-MF throughout contraction, EMG-RMS at 60% MVC was significantly higher in noFB-2 and noFB-3 in the second half of contraction. Taking into account that EMG-MF parameter is mainly influenced by sarcolemmal conduction velocity (Rainoldi et al 1999), it may be argued that changes in central command due to neuromuscular fatigue throughout contraction were similar among noFB conditions in terms of decrease in average motor unit conduction velocity. However, a possible tendency toward a synchronization/grouping effect, reflected in the higher EMG-RMS values, to maintain the same level of force output may have taken place at 60% MVC (Krogh-Lund and Jorgensen 1993).…”

Section: Effect Of Repeated Contractions Without Visual Feedback (Nofmentioning

confidence: 99%

Effects of visual feedback absence on force control during isometric contraction

et al. 2014

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Section: Effect Of Repeated Contractions Without Visual Feedback (Nofmentioning

confidence: 99%

Effects of visual feedback absence on force control during isometric contraction

et al. 2014

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“…These VRs indicate a high degree of repeatability and compare favorably with those of EMG. For example, EMG Mwaves from the biceps brachii were judged to be "very reproducible" with a VR of 0.24 ± 0.17 [23]. Also, comparison of the surface EMG of musculus flexor digitorum supericialis between skilled archers and nonarchers yielded VRs of 0.08 and 0.70, respectively [24].…”

Section: Taskmentioning

confidence: 99%

“…The ProController ® (Motion Control, Inc; Salt Lake City, Utah) offers the most advanced force-controlled prosthesis through use of EMG levels and force feedback for control, but its limitation to a few discrete states has not significantly improved since its introduction in the 1980s [25]. Many studies have demonstrated the potential of EMG models and advanced signal processing to predict grip force, but none has demonstrated that these modalities have been practically implemented in a prosthesis [23,[26][27][28][29][30][31]. However, we expect that the inherently low frequency information associated with FMG measurement of superficial changes in muscle conformation will more precisely render subtle changes in grasp dynamics.…”

Section: Force Myography As Control Modalitymentioning

confidence: 99%

Pressure signature of forearm as predictor of grip force

Wininger

Kim

Craelius

2008

JRRD

111

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Abstract-We studied the relationship between grip force and external forearm pressure in nondisabled subjects using force myography (FMG). FMG uses a sensorized cuff surrounding the forearm to register the distributed mechanical force, detecting pressure on the sensors generated by the volumetric changes of the underlying musculo-tendinous complex. Each of nine nondisabled subjects donned the FMG cuff and applied grip forces to a cylindrical dynamometer; grip forces ranged from 0% to 100% of the subjects' maximum voluntary contraction. The cuff was positioned with seven force sensors located on both the anterior and posterior surfaces of the proximal forearm, but no attempt was made to match sensor placement with particular muscles or sites. Grip prediction was simply encoded as the rectified sum of the FMG sensor outputs. During grip and release cycles, the FMG waveforms of each subject correlated closely with his or her force waveforms (r > 0.89). FMG also correlated highly with the timing of grip onset and release (intraclass correlation coefficient (ICC(A,2)) = 0.99) and time to peak (ICC(A,2) = 0.91), with negligible lag. These results demonstrate that when applied to the forearm, FMG represents a grip force signature that may be useful for near-real-time proportional control of upper-limb prosthetic devices.

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“…There are several possible causes for the continuing divergence of results about the effect of the force of contraction on MNF and MDF. These are based in part on results from studies with small population samples 28,29,32 , different demographic groups 24,26,28 , different study designs 22 involving the levels of muscle contraction, the range of joint angles and the difference in the length of the data measured 24,35,36,38 , the existence of muscle fatigue 48,49 , as well as varying evaluating methods. A number of causes that may influence the MNF and MDF features were discussed in more detail in the following.…”

Section: Identification and Possible Causes For The Conflicting Resultsmentioning

confidence: 99%

The effects of the force of contraction and elbow joint angle on mean and median frequency analysis for muscle fatigue evaluation

Thongpanja¹,

Phinyomark²,

Hu³

et al. 2015

ScienceAsia

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Mean frequency (MNF) and median frequency (MDF) are often used to assess muscular fatigue from surface electromyography (sEMG) signals. To determine muscle fatigue at different levels of isometric and dynamic contractions, it is necessary to know the relationship between the force of contraction and the MNF/MDF methods. Despite numerous studies, no unique answer has been found. This study re-examines this relationship by investigating 19 subjects and performing isometric and dynamic contractions over a full elbow range of motion measured from the biceps brachii muscle. We obtained the following key results: (i) a strong positive relationship between MNF/MDF methods and the force of contraction was found frequently during isometric contractions at an angle less than 90°and during dynamic contractions in 3 subjects (16%); (ii) a strong negative relationship during isometric contractions at an angle greater than 90°and during dynamic contractions in 8 subjects (42%), and (iii) no strong linear relationship during isometric contractions for all the angles and during dynamic contractions in 8 subjects (42%). After possible causes for these conflicting results are discussed, the study then investigates if it is possible to use anthropometric variables of subjects as the criteria to create homogeneous subgroups of relationships. A number of anthropometric variables were used to separate the subgroups, i.e., the forearm and biceps circumferences for males and the hand and shoulder breadths for females.

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Repeatability of surface EMG variables during voluntary isometric contractions of the biceps brachii muscle

Cited by 167 publications

References 40 publications

Effects of visual feedback absence on force control during isometric contraction

Effects of visual feedback absence on force control during isometric contraction

Pressure signature of forearm as predictor of grip force

The effects of the force of contraction and elbow joint angle on mean and median frequency analysis for muscle fatigue evaluation

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