Muscle activation and time to task failure differ with load type and contraction intensity for a human hand muscle

The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models.

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Potentiating and fatiguing cortical reactions in a voluntary fatigue test of a human hand muscle

Experimental Brain Research ◽

10.1007/s002210050055 ◽

2000 ◽

Vol 130 (4) ◽

pp. 529-532 ◽

Cited By ~ 6

Author(s):

Inge Zijdewind ◽

Machiel J. Zwarts ◽

Daniel Kernell

Keyword(s):

Fatigue Test ◽

Human Hand ◽

Hand Muscle

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Role of Interhemispheric Cortical Interactions in Poststroke Motor Function

Neurorehabilitation and Neural Repair ◽

10.1177/1545968319862552 ◽

2019 ◽

Vol 33 (9) ◽

pp. 762-774 ◽

Cited By ~ 5

Author(s):

Jacqueline A. Palmer ◽

Lewis A. Wheaton ◽

Whitney A. Gray ◽

Mary Alice Saltão da Silva ◽

Steven L. Wolf ◽

...

Keyword(s):

Motor Function ◽

Muscle Activation ◽

Primary Motor Cortex ◽

Silent Period ◽

Negatively Associated ◽

Interhemispheric Coherence ◽

Stroke Group ◽

Active Condition ◽

Hand Muscle ◽

Clinical Measures

Background/Objective. We investigated interhemispheric interactions in stroke survivors by measuring transcranial magnetic stimulation (TMS)–evoked cortical coherence. We tested the effect of TMS on interhemispheric coherence during rest and active muscle contraction and compared coherence in stroke and older adults. We evaluated the relationships between interhemispheric coherence, paretic motor function, and the ipsilateral cortical silent period (iSP). Methods. Participants with (n = 19) and without (n = 14) chronic stroke either rested or maintained a contraction of the ipsilateral hand muscle during simultaneous recordings of evoked responses to TMS of the ipsilesional/nondominant (i/ndM1) and contralesional/dominant (c/dM1) primary motor cortex with EEG and in the hand muscle with EMG. We calculated pre- and post-TMS interhemispheric beta coherence (15-30 Hz) between motor areas in both conditions and the iSP duration during the active condition. Results. During active i/ndM1 TMS, interhemispheric coherence increased immediately following TMS in controls but not in stroke. Coherence during active cM1 TMS was greater than iM1 TMS in the stroke group. Coherence during active iM1 TMS was less in stroke participants and was negatively associated with measures of paretic arm motor function. Paretic iSP was longer compared with controls and negatively associated with clinical measures of manual dexterity. There was no relationship between coherence and. iSP for either group. No within- or between-group differences in coherence were observed at rest. Conclusions. TMS-evoked cortical coherence during hand muscle activation can index interhemispheric interactions associated with poststroke motor function and potentially offer new insights into neural mechanisms influencing functional recovery.

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