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Understanding the Effects of Neuromuscular Fatigue on the Loss of Muscle Force Control
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Journal of Advanced Practices in Nursing

ISSN: 2573-0347

Open Access

Mini Review - (2022) Volume 7, Issue 12

Understanding the Effects of Neuromuscular Fatigue on the Loss of Muscle Force Control

Patricia Hodgson*
*Correspondence: Patricia Hodgson, Department of Advanced Nursing, University of Helsinki, Yliopistonkatu, Helsinki, Finland, Email:
Department of Advanced Nursing, University of Helsinki, Yliopistonkatu, Helsinki, Finland

Received: 02-Dec-2022, Manuscript No. APN-23-86107; Editor assigned: 05-Dec-2022, Pre QC No. P-86107; Reviewed: 16-Dec-2022, QC No. Q-86107; Revised: 22-Dec-2022, Manuscript No. R-86107; Published: 29-Dec-2022 , DOI: 10.37421/2573-0347.2022.7.302
Citation: Hodgson, Patricia. “Understanding the Effects of Neuromuscular Fatigue on the Loss of Muscle Force Control.” Adv Practice Nurs 7 (2022): 302.
Copyright: © 2022 Hodgson P. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Since ancient times, astute observers have observed that muscles that have been intensively worked gradually lose performance. This phenomenon is recognised both as performance fatigability and neuromuscular fatigue. Generally speaking, neuromuscular tiredness is a reduction in the maximum force or torque that can be produced during activity. In order to acknowledge that the capacity to produce maximum muscle force is not the only factor determining exercise performance, this definition has been modified to include a drop in any objective measure of performance over a certain time period. In fact, a crucial, though generally disregarded, aspect of determining performance is the capacity to manage submaximal muscular forces, i.e., to produce task-relevant and exact levels of force.

Keywords

Neuromuscular fatigue • Dynamic balance • Sample entropy

Introduction

Variability has long been recognised as an unavoidable feature of voluntary muscle contraction. As a result, muscle force output is neither smooth nor consistent; rather, it exhibits constant inherent fluctuations around the required target force, indicating that force control is not perfect. Leon Binet first commented on the effect of neuromuscular fatigue on the ability to control force in 1920, stating that "tremor increases as a result of muscular contraction and becomes exaggerated under the influence of work [1-3]."A century of subsequent research has revealed increases in the magnitude and, more recently, decreases in the temporal structure (i.e., complexity) of muscle force fluctuations during fatiguing contractions, with both changes indicating a poorer ability to control muscle force.

Description

Recent research has focused on the mechanistic basis of the neuromuscular fatigue-induced reduction in submaximal muscle force control, implying that, as with the mechanisms underlying the reduction in maximal force-generating capacity, both central and peripheral processes may be involved. However, of equal, if not greater, importance is the effect of muscle force control loss on exercise performance, where it serves to impede the ability to exert a desired force and produce an intended movement trajectory; this explains a significant amount of variation in the performance of functional tasks (e.g., static and dynamic balance), and has been proposed to be relevant for exercise tolerance [4,5].

The goal of this review is to provide a comprehensive overview of the changes in muscle force control caused by neuromuscular fatigue. This examination begins with a brief description of muscle force control measurement and quantification during neuromuscular fatigue. We then present evidence for how muscle force control changes with neuromuscular fatigue and discuss the potential mechanistic basis. Finally, we discuss the performance implications of neuromuscular fatigue-induced muscle force control loss. Throughout the review, we also highlight previous research limitations and gaps in our knowledge (and, as a result, areas for future research to focus on) regarding neuromuscular fatigue-induced loss of muscle force control. In summary, traditional magnitude-based measures provide an index of a time series' degree of deviation from a fixed point.

The standard deviation (SD) quantifies the absolute magnitude of fluctuations in muscle force output, whereas the coefficient of variation (CV) quantifies the magnitude of fluctuations normalised to the mean force output, allowing for comparisons between individuals/populations with varying maximal strength. These metrics reflect the consistency of the force. It should be noted, however, that force control and the magnitude of force fluctuations have only been calculated in this manner since the millennium's turn. Previously, force control was frequently measured using the frequency or root mean square of physiological and/or force tremor.

Conclusion

The inability of magnitude-based measures to distinguish outputs with distinctly different dynamics is one of their limitations. Complexity-based measures characterize the moment-to-moment relationship between successive points (or series of points) in an output, allowing the quantification of temporal irregularity, time irreversibility, and long-range fractal correlations. Approximate entropy (ApEn) and sample entropy (SampEn) measure the degree of regularity/randomness in an output, whereas detrended fluctuation analysis (DFA) measures long-range fractal correlations within an output. These metrics reflect force adaptability, or the ability to quickly and accurately adjust force output in response to perturbations.

References

  1. Carbonell Baeza A. "Pain and functional capacity in female fibromyalgia patients.  " Pain Med. (2011);12:1667-1675.
  2. Google Scholar, Crossref, Indexed at

  3. Moe A, Ingstad K, Brataas HV. "Patient influence in home-based reablement for older persons: Qualitative research. " BMC Health Serv Res. (2017); 17:736.
  4. Google Scholar, Crossref, Indexed at

  5. Roshanravan B. "Association between physical performance and all-cause mortality in CKD. " J Am Soc Nephrol. (2013); 24:822-830.
  6. Google Scholar, Crossref, Indexed at

  7. Vijayananthan A, Nawawi O. "The importance of Good Clinical Practice guidelines and its role in clinical trials. " Biomed Imaging Interv J. (2008); 4.
  8. Google Scholar, Crossref, Indexed at

  9. Samuelsson K. "patient-reported outcome of a multidisciplinary pain management program, focusing on occupational performance and satisfaction with performance. " Open Rehabil J. (2011);4:42-50.
  10. Google Scholar, Crossref, Indexed at

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