Abstract
Purpose
The time course of maximal voluntary isometric contraction (MVIC) force is of particular interest whenever force capacities are a limiting factor, e.g., during heavy manual work or resistance training (RT) sessions. The objective of this work was to develop a mathematical model of this time course that is suitable for optimization of complex loading schemes.
Materials and methods
We compiled a literature overview of existing models and justified the need for a new model. We then constructed a phenomenological ordinary differential equation model to describe the time course of MVIC force during voluntary isometric contractions and at rest. We validated the model with a comprehensive set of published data from the elbow flexors. For this, we estimated parameters from a subset of the available data and used those estimates to predict the remaining data. Afterwards, we illustrated the benefits of our model using the calibrated model to (1) analyze fatigue and recovery patterns observed in the literature (2) compute a work–rest schedule that minimizes fatigue (3) determine an isometric RT session that maximizes training volume.
Results
We demonstrated that our model (1) is able to describe MVIC force under complex loading schemes (2) can be used to analyze fatigue and recovery patterns observed in the literature (3) can be used to optimize complex loading schemes.
Conclusions
We developed a mathematical model of the time course of MVIC force that can be efficiently employed to optimize complex loading schemes. This enables an optimal use of MVIC force capacities.
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Abbreviations
- FTI:
-
Force-time integral
- MAE:
-
Mean absolute error
- MVIC:
-
Maximal voluntary isometric contraction
- ODE:
-
Ordinary differential equation
- SD:
-
Standard deviation
- RT:
-
Resistance training
- WRSS:
-
Weighted residual sum of squares
References
Allen DG, Lamb GD, Westerblad H (2008) Skeletal muscle fatigue: cellular mechanisms. Physiol Rev 88(1):287–332. https://doi.org/10.1152/physrev.00015.2007. http://physrev.physiology.org/content/88/1/287
American College of Sports Medicine (2009) American College of Sports Medicine position stand. Progression models in resistance training for healthy adults. Medicine and Science in Sports and Exercise 41(3):687. http://journals.lww.com/acsm-msse/Fulltext/2009/03000/Progression_Models_in_Resistance_Training_for.26.aspx
Barnes WS (1980) The relationship between maximum isometric strength and intramuscular circulatory occlusion. Ergonomics 23(4):351–357. https://doi.org/10.1080/00140138008924748 PMID: 7202390
Bauer I (1999) Numerische Verfahren zur Lösung von Anfangswertaufgaben und zur Generierung von ersten und zweiten Ableitungen mit Anwendungen bei Optimierungsaufgaben in Chemie und Verfahrenstechnik. Dissertation, Heidelberg University. https://doi.org/10.11588/heidok.00001513
Bigland-Ritchie BR, Dawson NJ, Johansson RS, Lippold OC (1986) Reflex origin for the slowing of motoneurone firing rates in fatigue of human voluntary contractions. J Physiol 379(1):451–459. https://doi.org/10.1113/jphysiol.1986.sp016263/full
Bock HG (1981) Numerical treatment of inverse problems in chemical reaction kinetics. Springer, Berlin Heidelberg, pp 102–125. https://doi.org/10.1007/978-3-642-68220-9_8
Bock HG (1987) Randwertproblemmethoden zur Parameteridentifizierung in Systemen nichtlinearer Differentialgleichungen. Bonner Mathematische Schriften 183
Bock HG, Plitt KJ (1984) A multiple shooting algorithm for direct solution of optimal control problems. In: Proceedings of the 9th IFAC World Congress, Pergamon Press, Oxford, pp 242–247
Brown LE, Weir JP (2001) ASEP procedures recommendation I: accurate assessment of muscular strength and power. Prof Exerc Physiol 4(11). https://www.asep.org/asep/asep/Brown2.pdf
Callahan DM, Umberger BR, Kent-Braun JA (2013) A computational model of torque generation: neural, contractile, metabolic musculoskeletal components. PLOS One 8(2):1–11. https://doi.org/10.1371/journal.pone.0056013
Callahan DM, Umberger BR, Kent JA (2016) Mechanisms of in vivo muscle fatigue in humans: investigating age-related fatigue resistance with a computational model. J Physiol 594(12):3407–3421. https://doi.org/10.1113/JP271400
Carolan B, Cafarelli E (1992) Adaptations in coactivation after isometric resistance training. J Appl Physiol 73(3):911–917. http://jap.physiology.org/content/73/3/911
Carroll TJ, Taylor JL, Gandevia SC (2017) Recovery of central and peripheral neuromuscular fatigue after exercise. J Appl Physiol 122(5):1068–1076. https://doi.org/10.1152/japplphysiol.00775.2016 PMID: 27932676
Clarke DH (1962) Strength recovery from static and dynamic muscular fatigue. Res Q Am Assoc Health Phys Educ Recreat 33(3):349–355. https://doi.org/10.1080/10671188.1962.10616463
Contessa P, Luca CJD (2013) Neural control of muscle force: indications from a simulation model. J Neurophysiol 109(6):1548–1570. https://doi.org/10.1152/jn.00237.2012. http://jn.physiology.org/content/109/6/1548
Deeb JM, Drury CG, Pendergast DR (1992) An exponential model of isometric muscular fatigue as a function of age and muscle groups. Ergonomics 35(7–8):899–918. https://doi.org/10.1080/00140139208967370 PMID: 1633796
Dideriksen JL, Farina D, Baekgaard M, Enoka RM (2010) An integrative model of motor unit activity during sustained submaximal contractions. J Appl Physiol 108(6):1550–1562. https://doi.org/10.1152/japplphysiol.01017.2009. http://jap.physiology.org/content/108/6/1550
El Ahrache K, Imbeau D, Farbos B (2006) Percentile values for determining maximum endurance times for static muscular work. Int J Ind Ergon 36(2):99–108. https://doi.org/10.1016/j.ergon.2005.08.003
Enoka RM, Duchateau J (2008) Muscle fatigue: what, why and how it influences muscle function. J Physiol 586(1):11–23. https://doi.org/10.1113/jphysiol.2007.139477
Eriksson A (2008) Optimization in target movement simulations. Comput Methods Appl Mech Eng 197(49):4207–4215. https://doi.org/10.1016/j.cma.2008.04.017
Eriksson A, Nordmark A (2011) Activation dynamics in the optimization of targeted movements. Comput Struct 89(11):968–976. https://doi.org/10.1016/j.compstruc.2011.01.019 (Special Issue: Computational Fluid and Solid Mechanics 2011)
Fayazi SA, Wan N, Lucich S, Vahidi A, Mocko G (2013) Optimal pacing in a cycling time-trial considering cyclist’s fatigue dynamics. In: 2013 American Control Conference, pp 6442–6447. https://doi.org/10.1109/ACC.2013.6580849. http://alirezafayazi.com/docs/06580849.pdf
Fleck SJ, Kraemer W (2014) Designing Resistance Training Programs, 4E. Human Kinetics
Freund J, Takala EP (2001) A dynamic model of the forearm including fatigue. J Biomech 34(5):597–605. https://doi.org/10.1016/S0021-9290(01)00009-4
Fuglevand AJ, Winter DA, Patla AE (1993) Models of recruitment and rate coding organization in motor-unit pools. J Neurophysiol 70(6):2470–2488. http://jn.physiology.org/content/70/6/2470
Gandevia SC (2001) Spinal and supraspinal factors in human muscle fatigue. Physiol Rev 81(4):1725–1789. http://physrev.physiology.org/content/81/4/1725
Gandevia SC, Allen GM, Butler JE, Taylor JL (1996) Supraspinal factors in human muscle fatigue: evidence for suboptimal output from the motor cortex. J Physiol 490(2):529–536. https://doi.org/10.1113/jphysiol.1996.sp021164
Gede G (2014) Optimal pacing strategies for cyclist time trials. PhD thesis, University of California, Davis. https://search.proquest.com/docview/1665571951
Gede G, Hubbard M (2014) A bioenergetic model for simulating athletic performance of intermediate duration. J Biomech 47(14):3448–3453. https://doi.org/10.1016/j.jbiomech.2014.09.017
Granata KP, Gottipati P (2008) Fatigue influences the dynamic stability of the torso. Ergonomics 51(8):1258–1271. https://doi.org/10.1080/00140130802030722 PMID: 18608477
Grandjean E (1979) Fatigue in industry. Occup Environ Med 36(3):175–186. https://doi.org/10.1136/oem.36.3.175. http://oem.bmj.com/content/36/3/175
Hawkins D, Hull M (1993) Muscle force as affected by fatigue: mathematical model and experimental verification. J Biomech 26(9):1117–1128. https://doi.org/10.1016/S0021-9290(05)80010-7
Hawkins DA (1990) A cellular-based muscle model: Formulation and application for studying muscle mechanics. PhD thesis, University of California, Davis, aAI9102077
Henneman E, Somjen G, Carpenter DO (1965) Functional significance of cell size in spinal motoneurons. J Neurophysiol 28(3):560–580. http://jn.physiology.org/content/28/3/560
Herzog W (2004) History dependence of skeletal muscle force production: Implications for movement control. Human Mov Sci 23(5):591–604. https://doi.org/10.1016/j.humov.2004.10.003 (Special Issue: European Workshop on Movement Science)
Iguchi M, Baldwin K, Boeyink C, Engle C, Kehoe M, Ganju A, Messaros AJ, Shields RK (2008) Low frequency fatigue in human quadriceps is fatigue dependent and not task dependent. J Electromyogr Kinesiol 18(2):308–316. https://doi.org/10.1016/j.jelekin.2006.09.010
James A, Green S (2012) A phenomenological model of muscle fatigue and the power-endurance relationship. J Appl Physiol 113(10):1643–1651. https://doi.org/10.1152/japplphysiol.00800.2012. http://jap.physiology.org/content/113/10/1643
Kennedy DS, McNeil CJ, Gandevia SC, Taylor JL (2013) Firing of antagonist small-diameter muscle afferents reduces voluntary activation and torque of elbow flexors. J Physiol 591(14):3591–3604. https://doi.org/10.1113/jphysiol.2012.248559
Keyserling MW, Herrin GD, Chaffin DB (1980) Isometric strength testing as a means of controlling medical incidents on strenuous jobs. J Occup Environ Med 22(5):332–336. https://www.ncbi.nlm.nih.gov/pubmed/7381613
Kircheis R (2015) Structure exploiting parameter estimation and optimum experimental design methods and applications in microbial enhanced oil recovery. Dissertation, Heidelberg University, https://doi.org/10.11588/heidok.00022098. http://www.ub.uni-heidelberg.de/archiv/22098
Kisner C, Colby LA, Borstad J (2017) Therapeutic exercise: foundations and techniques, 7th edn. F.A Davis Company, Philadelphia
Kosterina N, Westerblad H, Eriksson A (2012) History effect and timing of force production introduced in a skeletal muscle model. Biomech Model Mechanobiol 11(7):947–957. https://doi.org/10.1007/s10237-011-0364-5
Körkel S (2002) Numerische Methoden für Optimale Versuchsplanungsprobleme bei nichtlinearen DAE-Modellen. Dissertation, Heidelberg University. https://doi.org/10.11588/heidok.00002980. http://www.ub.uni-heidelberg.de/archiv/2980
Law LAF, Avin KG (2010) Endurance time is joint-specific: a modelling and meta-analysis investigation. Ergonomics 53(1):109–129. https://doi.org/10.1080/00140130903389068 PMID: 20069487
Leetun DT, Ireland ML, Willson JD, Ballantyne BT, Davis IM (2004) Core stability measures as risk factors for lower extremity injury in athletes. Med Sci Sports Exerc 36(6):926–934. https://doi.org/10.1249/01.MSS.0000128145.75199.C3
Leineweber DB, Bauer I, Bock HG, Schlöder JP (2003a) An efficient multiple shooting based reduced SQP strategy for large-scale dynamic process optimization. Part 1: theoretical aspects. Comput Chem Eng 27(2):157–166. https://doi.org/10.1016/S0098-1354(02)00158-8
Leineweber DB, Schäfer A, Bock HG, Schlöder JP (2003b) An efficient multiple shooting based reduced SQP strategy for large-scale dynamic process optimization. Part II: Software aspects and applications. Comput Chem Eng 27(2):167–174. https://doi.org/10.1016/S0098-1354(02)00195-3
Linnamo V, Bottas R, Komi P (2000) Force and EMG power spectrum during and after eccentric and concentric fatigue. J Electromyogr Kinesiol 10(5):293–300. https://doi.org/10.1016/S1050-6411(00)00021-3
Liu JZ, Brown RW, Yue GH (2002) A dynamical model of muscle activation, fatigue, and recovery. Biophys J 82(5):2344–2359. https://doi.org/10.1016/S0006-3495(02)75580-X
Looft JM (2014) Adaptation and validation of an analytical localized muscle fatigue model for workplace tasks. PhD thesis, The University of Iowa. http://ir.uiowa.edu/etd/1482/
Ma L, Chablat D, Bennis F, Zhang W (2009) A new simple dynamic muscle fatigue model and its validation. Int J Ind Ergon 39(1):211–220. https://doi.org/10.1016/j.ergon.2008.04.004
Ma L, Chablat D, Bennis F, Zhang W, Guillaume F (2010) A new muscle fatigue and recovery model and its ergonomics application in human simulation. Virtual Phys Prototyp 5(3):123–137. https://doi.org/10.1080/17452759.2010.504056
Ma L, Zhang W, Wu S, Zhang Z (2015) A new simple local muscle recovery model and its theoretical and experimental validation. Int J Occup Saf Ergon 21(1):86–93. https://doi.org/10.1080/10803548.2015.1017961 PMID: 26327267
Maffiuletti NA (2010) Physiological and methodological considerations for the use of neuromuscular electrical stimulation. Eur J Appl Physiol 110(2):223–234. https://doi.org/10.1007/s00421-010-1502-y
Maffiuletti NA, Martin A (2001) Progressive versus rapid rate of contraction during 7 wk of isometric resistance training. Med Sci Sports Exerc 33(7):1220–1227. https://doi.org/10.1097/00005768-200107000-00022
Marina M, Rios M, Torrado P, Busquets A, Angulo-Barroso R (2014) Force-time course parameters and force fatigue model during an intermittent fatigue protocol in motorcycle race riders. Scand J Med Sci Sports 25(3):406–416. https://doi.org/10.1111/sms.12220
Mitchell M, Muftakhidinov B, Winchen T, et al (2017) Engauge digitizer software. http://markummitchell.github.io/engauge-digitizer
Monod H, Scherrer J (1957) Capacité de travail statique d’un groupe musculaire synergique chez l’homme. Comptes Rendus des Séances de la Société de Biologie et de ses Filiales 151(7):1358–1362
Monod H, Scherrer J (1965) The work capacity of a synergic muscular group. Ergonomics 8(3):329–338. https://doi.org/10.1080/00140136508930810
Morel B, Clémençon M, Rota S, Millet GY, Bishop DJ, Brosseau O, Rouffet DM, Hautier CA (2015) Contraction velocity influence the magnitude and etiology of neuromuscular fatigue during repeated maximal contractions. Scand J Med Sci Sports 25(5):e432–e441. https://doi.org/10.1111/sms.12358
Neyroud D, Rüttimann J, Mannion AF, Millet GY, Maffiuletti NA, Kayser B, Place N (2013) Comparison of neuromuscular adjustments associated with sustained isometric contractions of four different muscle groups. J Appl Physiol 114(10):1426–1434. https://doi.org/10.1152/japplphysiol.01539.2012. http://jap.physiology.org/content/114/10/1426
Neyroud D, Kayser B, Place N (2016) Are there critical fatigue thresholds? Aggregated vs. individual data. Front Physiol 7:376. https://doi.org/10.3389/fphys.2016.00376
Place N, Maffiuletti NA, Ballay Y, Lepers R (2005) Twitch potentiation is greater after a fatiguing submaximal isometric contraction performed at short vs. long quadriceps muscle length. J Appl Physiol 98(2):429–436. https://doi.org/10.1152/japplphysiol.00664.2004. http://jap.physiology.org/content/98/2/429
Potvin JR, Fuglevand AJ (2017) A motor unit-based model of muscle fatigue. PLoS Comput Biol 13(6):1–30. https://doi.org/10.1371/journal.pcbi.1005581
Rashedi E, Nussbaum MA (2017) Quantifying the history dependency of muscle recovery from a fatiguing intermittent task. J Biomech 51:26–31. https://doi.org/10.1016/j.jbiomech.2016.11.061. http://www.sciencedirect.com/science/article/pii/S0021929016312404
Rich GQ (1960) Muscular fatigue curves of boys and girls. Res Q Am Assoc Health Phys Educ Recreat 31(3):485–498. https://doi.org/10.1080/10671188.1960.10762056
Riener R, Quintern J, Schmidt G (1996) Biomechanical model of the human knee evaluated by neuromuscular stimulation. J Biomech 29(9):1157–1167. https://doi.org/10.1016/0021-9290(96)00012-7. http://www.sciencedirect.com/science/article/pii/0021929096000127
Rodríguez-Rosell D, Pareja-Blanco F, Aagaard P, González-Badillo JJ (2017) Physiological and methodological aspects of rate of force development assessment in human skeletal muscle. Clin Physiol Funct Imaging. https://doi.org/10.1111/cpf.12495
Rohmert W (1960) Ermittlung von Erholungspausen für statische Arbeit des Menschen. Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie 18(2):123–164. https://doi.org/10.1007/BF00698869
Rozand V, Cattagni T, Theurel J, Martin A, Lepers R (2015) Neuromuscular fatigue following isometric contractions with similar torque time integral. Int J Sports Med 36(01):35–40. https://doi.org/10.1055/s-0034-1375614
Sadamoto T, Bonde-Petersen F, Suzuki Y (1983) Skeletal muscle tension, flow, pressure, and EMG during sustained isometric contractions in humans. Eur J Appl Physiol 51(3):395–408. https://doi.org/10.1007/BF00429076
Sahlin K, Tonkonogi M, Söderlund K (1998) Energy supply and muscle fatigue in humans. Acta Physiol Scand 162(3):261–266. https://doi.org/10.1046/j.1365-201X.1998.0298f.x/full
Schlöder JP (1988) Numerische Methoden zur Behandlung hochdimensionaler Aufgaben der Parameteridentifizierung. Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn
Shield A, Zhou S (2004) Assessing voluntary muscle activation with the twitch interpolation technique. Sports Med 34(4):253–267. https://doi.org/10.2165/00007256-200434040-00005
Sih B, Ng L, Stuhmiller J (2012) Generalization of a model based on biophysical concepts of muscle activation, fatigue and recovery that explains exercise performance. Int J Sports Med 33(04):258–267. https://doi.org/10.1055/s-0031-1297958. https://www.thieme-connect.com/products/ejournals/html/10.1055/s-0031-1297958
Smith JL, Martin PG, Gandevia SC, Taylor JL (2007) Sustained contraction at very low forces produces prominent supraspinal fatigue in human elbow flexor muscles. J Appl Physiol 103(2):560–568. https://doi.org/10.1152/japplphysiol.00220.2007. http://jap.physiology.org/content/103/2/560
Søgaard K, Gandevia SC, Todd G, Petersen NT, Taylor JL (2006) The effect of sustained low-intensity contractions on supraspinal fatigue in human elbow flexor muscles. J Physiol 573(2):511–523. https://doi.org/10.1113/jphysiol.2005.103598
Sonne MW, Potvin JR (2016) A modified version of the three-compartment model to predict fatigue during submaximal tasks with complex force-time histories. Ergonomics 59(1):85–98. https://doi.org/10.1080/00140139.2015.1051597 PMID: 26018327
Tan B (1999) Manipulating resistance training program variables to optimize maximum strength in men: a review. J Strength Cond Res 13(3):289–304. https://insights.ovid.com/strength-conditioning-research/jscr/1999/08/000/manipulating-resistance-training-program-variables/19/00124278
Taylor JL, Butler JE, Gandevia SC (1999) Altered responses of human elbow flexors to peripheral-nerve and cortical stimulation during a sustained maximal voluntary contraction. Exp Brain Res 127(1):108–115. https://doi.org/10.1007/s002210050779
Taylor JL, Allen GM, Butler JE, Gandevia SC (2000) Supraspinal fatigue during intermittent maximal voluntary contractions of the human elbow flexors. J Appl Physiol 89(1):305–313. http://jap.physiology.org/content/89/1/305
Taylor JL, Amann M, Duchateau J, Meeusen R, Rice CL (2016) Neural contributions to muscle fatigue: from the brain to the muscle and back again. Med Sci Sports Exerc 48(11):2294–306. https://www.ncbi.nlm.nih.gov/pubmed/27003703
Todd G, Taylor JL, Gandevia SC (2003) Measurement of voluntary activation of fresh and fatigued human muscles using transcranial magnetic stimulation. J Physiol 551(2):661–671. https://doi.org/10.1113/jphysiol.2003.044099
Vøllestad NK (1997) Measurement of human muscle fatigue. J Neurosci Methods 74(2):219–227. https://doi.org/10.1016/S0165-0270(97)02251-6. http://www.sciencedirect.com/science/article/pii/S0165027097022516
Wood DD, Fisher DL, Andres RO (1997) Minimizing fatigue during repetitive jobs: optimal work-rest schedules. Hum Factors 39(1):83–101. https://doi.org/10.1518/001872097778940678 PMID: 9302881
Xia T, Law LAF (2008) A theoretical approach for modeling peripheral muscle fatigue and recovery. J Biomech 41(14):3046–3052. https://doi.org/10.1016/j.jbiomech.2008.07.013. http://www.sciencedirect.com/science/article/pii/S0021929008003692
Acknowledgements
We gratefully thank Dr. Janet L. Taylor of Neuroscience Research Australia, Sydney, Australia for providing and explaining the experimental data of the studies Taylor et al. (1999, 2000), Søgaard et al. (2006), and Smith et al. (2007). We furthermore would like to thank the anonymous reviewers whose comments helped to improve this manuscript significantly.
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JLH acknowledges support from the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences (Graduate School 220), funded by the Deutsche Forschungsgemeinschaft (DFG) within the German Excellence Initiative.
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JLH and CK conceived the idea for this work. JLH conducted the literature research, developed the model, performed the numerical experiments, and drafted the manuscript. JLH, CK, and JPS discussed and edited the draft. JLH, CK, and JPS revised the manuscript. JLH, CK, and JPS approved the final version of the manuscript.
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A preprint of this work is available on bioRxiv.org. URL https://www.biorxiv.org/content/early/2018/01/30/256578, DOI https://doi.org/10.1101/256578.
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Communicated by Jean-René Lacour.
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Herold, J.L., Kirches, C. & Schlöder, J.P. A phenomenological model of the time course of maximal voluntary isometric contraction force for optimization of complex loading schemes. Eur J Appl Physiol 118, 2587–2605 (2018). https://doi.org/10.1007/s00421-018-3983-z
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DOI: https://doi.org/10.1007/s00421-018-3983-z