Motor Units and Muscle Receptors

Celichowski, Jan; Krutki, Piotr

doi:10.1016/b978-0-12-814593-7.00004-9

Cited by 4 publications

(4 citation statements)

References 124 publications

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“…Muscles consist of motor units, which are the smallest possible portions of muscles, which can be activated [ 15 ]. The sum of the action potentials of the respective muscle fiber can be measured invasively with needle electrodes placed directly into the muscle in the area of interest.…”

Section: Electromyographymentioning

confidence: 99%

Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach—Part III: Other Biosignals

Martínek

Ládrová

Šidiková

et al. 2021

Sensors

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Analysis of biomedical signals is a very challenging task involving implementation of various advanced signal processing methods. This area is rapidly developing. This paper is a Part III paper, where the most popular and efficient digital signal processing methods are presented. This paper covers the following bioelectrical signals and their processing methods: electromyography (EMG), electroneurography (ENG), electrogastrography (EGG), electrooculography (EOG), electroretinography (ERG), and electrohysterography (EHG).

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Section: Electromyographymentioning

confidence: 99%

Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach—Part III: Other Biosignals

Martínek

Ládrová

Šidiková

et al. 2021

Sensors

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“…The width of the monophasic current pulse was fixed to 600 µs based on earlier studies in which the pulse width ranged from 200 µs to 1 ms [24,27,28]. The stimulation frequency of 120 Hz and 30 Hz was selected in this study to match the firing rate of afferent fibers in physiological condition [29][30][31]. A manual searching procedure was first performed to find out the anode and cathode electrode combinations with which single or multiple joint movements can be elicited using the two stimulation frequencies, respectively.…”

Section: Stimulation Paradigmmentioning

confidence: 99%

Elicited upper limb motions through transcutaneous cervical spinal cord stimulation

Yang¹,

Hu²

2020

J. Neural Eng.

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Objective. Transcutaneous cervical spinal cord stimulation (tsCSC) has been demonstrated to activate the dorsal root and activate targeted muscles. However, it is unclear whether tsCSC can elicit functionally relevant movements of the upper limb for assistive/rehabilitative purposes. Approach. The current study sought to elicit arm and hand movements by tsCSC by placing an electrode array near the cervical segments of the spinal cord. Anode stimulation current pulses were delivered to the dorsal side at 120 Hz and 30 Hz in separate trials. The elicited joint kinematics were captured using a motion tracking system. Main results. The results revealed that distal and proximal joint movements can be elicited either independently or synergistically. Specifically, different motions, including flexion and extension of the elbow, wrist, and five digits, can be selectively elicited by adjusting the stimulation parameters, such as stimulation location and stimulation intensity. Significance. The findings demonstrated the feasibility of the spinal cord stimulation technique in eliciting functional movements of the upper limb. The outcomes also revealed the potential of the tsCSC technique as a promising assistive or rehabilitative method for individuals with impaired function of the upper limb.

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“…This electrical stimulus is transmitted through an axon terminal of the motor neuron to a neuromuscular junction (Deschenes, Covault, et al, 1994;. The summation of electrical signals generates an action potential, triggering the release of the neurotransmitter Acetylcholine (ACh) and stimulating muscle activation in accordance with the "all or nothing" principle (Celichowski & Krutki, 2018;Enoka & Duchateau, 2018;D. Jones, 2004a;Scalettar, 2006).…”

Section: Motor Unit Recruitmentmentioning

confidence: 99%

“…Motor neurons and muscle fibres (motor units) are recruited hierarchically in accordance with their size i.e., size principle, and contain identical metabolic and shortening properties (e.g., fast vs. slow twitch -the tetanic response to an electrical stimulus, high vs. low fatigue and force) and are typically recruited as a "pool" in response to the demands of a task (Celichowski & Krutki, 2018;Duchateau & Enoka, 2011;Henneman, 1957;D. Jones, 2004c;Maffiuletti et al, 2016;Suchomel et al, 2018).…”

Section: Motor Unit Recruitmentmentioning

confidence: 99%

The efficacy of the load-velocity profile to predict one repetition maximum

Thompson

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Autoregulation is the process of acutely manipulating training variables in response to an individual’s fluctuations in strength and fatigue and is vital for optimising programming. Load-velocity profiles (LVPs) have been proposed as effective flexible programming strategies to optimise resistance training load (kg), often through the daily estimation of one repetition maximum (1RM). This PhD, therefore, adopted a pragmatic, mixed methods research design and followed an applied research model (ARMSS) to devise a series of studies to ascertain a novel, efficient, and valid approach to LVP-based 1RM prediction. Prior to choosing an autoregulatory method, strength and conditioning (S&C) practitioners must first determine an appropriate non-flexible programming strategy. A systematic review of literature revealed percentages of 1RM (% 1RM) as the superior method for increasing maximal strength (study one). After thematic analyses (study two) revealed barriers such as inaccurate 1RM predictions, time-costly protocols, and “iPad coaching” to the implementation of LVPs within practice; common velocity-based technology used by coaches; and the combination of ballistic and non-ballistic exercise when profiling, a new LVP method addressing these factors was devised in a key training, but under-researched exercise, the free-weight back squat. The new approach to LVP-based 1RM prediction developed from this thesis utilised the Gymaware linear-position transducer given its superior reliability and validity (study three); individualised profiling due to stronger load-velocity relationships and large between-participant variability observed (study four); ballistic (jump squat) exercise after larger mechanical output was revealed in 0-60% 1RM when compared to non-ballistic (back squat) (study five); a submaximal point of extrapolation (80% 1RM mean velocity) due to poor within-participant reliability of loads > 85% 1RM (study four); quadratic modelling (study four); and as few as four incremental loads. Results revealed this combination to be an effective method for estimating 1RM and autoregulating daily load for S&C coaches.

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Motor Units and Muscle Receptors

Cited by 4 publications

References 124 publications

Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach—Part III: Other Biosignals

Advanced Bioelectrical Signal Processing Methods: Past, Present, and Future Approach—Part III: Other Biosignals

Elicited upper limb motions through transcutaneous cervical spinal cord stimulation

The efficacy of the load-velocity profile to predict one repetition maximum

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