Evaluation of handgrip force from EMG measurements

Duqué, Julie; Masset, Dominique; Malchaire, Jacques

doi:10.1016/0003-6870(94)00003-h

Cited by 113 publications

(68 citation statements)

References 10 publications

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“…Relationships allowing the assessment of grip force by means of integrated EMG have already been described in the literature (Duque, Masset, & Malchaire, 1995;Meyer, Didry, Herrault, & Horwat, 1994;Ranaivosoa, 1992). However, these relationships, established in isometric isotonic conditions, are rarely observed at the work station.…”

Section: And Individualmentioning

confidence: 97%

Relevance of the EMG/Grip Relationship in Isometric Anisotonic Conditions

Claudon

2003

International Journal of Occupational Safety and Ergonomics

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The aim of the present study was to develop a relationship to evaluate grip force using the electromyogram (EMG) in isometric anisotonic conditions.The EMGs of the flexor digitorum superficialis (FDS) and the extensor digitorum (ED) were recorded in 3 flexion-extension positions of the wrist (30° flexion, 30° extension, and 60° extension) associated with 3 positions of the forearm (70° pronation, prono-supination, and 70° supination). For each position, the participants had to follow linear ramp targets (2 rates of increase and decrease) displayed on an oscilloscope.The results show the best fit is a quadratic type force-EMG relationship. Some aspects such as the rate of force variation and the forearm and wrist positions are then discussed along with the limitations of the relationship. cumulative trauma disorders upper limb electromyogram force isometric contraction anisotonic contraction

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Section: And Individualmentioning

confidence: 97%

Relevance of the EMG/Grip Relationship in Isometric Anisotonic Conditions

Claudon

2003

International Journal of Occupational Safety and Ergonomics

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“…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

113

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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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“…This enables us, for instance, to determine the amount of muscle contractions, as well as co-contraction of antagonist muscle pairs (e.g., biceps and triceps). Similar studies for joystick control are known in literature, 12 but have not been applied to aircraft control.…”

Section: Introductionmentioning

confidence: 90%

Identification of the Feedback Components of the Neuromuscular System in a Pitch Control Task

Damveld

Abbink

Mulder

et al. 2010

AIAA Modeling and Simulation Technologies Conference

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This goal of this study is to understand which parts of the the neuromuscular system contribute during a pitch control task. A novel method developed at the Delft University of Technology allows us to determine the contribution of the neuromuscular feedback system by identifying the admittance, which is the frequency response function of the yielded displacement due to an external force perturbation which applied to control inceptor.In an experiment in a full-motion flight simulator, the neuromuscular admittance was identified during a longitudinal pitch tracking task with a side stick, for two different side stick configurations, an approach configuration with a relatively low stick stiffness, and a cruise configuration with a high stiffness. Besides the admittance, also the muscle activity of eleven muscles was measured. To validate whether the external force perturbation changed the control behavior of the pilot, the visual and vestibular response functions were identified as well.From the measured results it could be concluded that the variations of the control inceptor settings had a significant effect on the neuromuscular feedback system (admittance), although the overall lumped neuromuscular system did not change significantly. A very interesting finding were the very high levels of co-contraction measured during the pitch tracking tasks. And lastly it could be concluded that the required external force perturbation did not affect the control behavior.

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Evaluation of handgrip force from EMG measurements

Cited by 113 publications

References 10 publications

Relevance of the EMG/Grip Relationship in Isometric Anisotonic Conditions

Relevance of the EMG/Grip Relationship in Isometric Anisotonic Conditions

Pressure signature of forearm as predictor of grip force

Identification of the Feedback Components of the Neuromuscular System in a Pitch Control Task

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