nach oben

European Journal of Applied Physiology

Erschienen in:

03.01.2022 | Original Article

How fiber dynamics of plantarflexor and dorsiflexor muscles based on EMG-driven approach can explain the metabolic cost at different gait speeds

verfasst von: Pauline Gerus, Elodie Piche, Olivier Guérin, Frederic Chorin, Raphaël Zory

Erschienen in: European Journal of Applied Physiology | Ausgabe 3/2022

Einloggen, um Zugang zu erhalten

Abstract

Purpose

The aim of this study was to investigate the fiber dynamics of plantarflexor and dorsiflexor muscles and their association with the net metabolic rate (NC_w).

Methods

Metabolic, kinematic, kinetic, and electromyography measurements were made on seven young subjects while they walked on a force-plate instrumented treadmill at 1.00, 1.20, 1.40, 1.60, and 1.8 m/s for 1:30 min. The net metabolic rate was computed, and a one degree-of freedom EMG-driven approach was used to extract the force generation ability (F_ability), and active force–length (f_AL) and force–velocity (f_V) multiplier of each muscle. A one-way (speeds) repeated measures ANOVA was performed for each muscle and a multiple linear regression model was used to explain NC_w.

Results

F_ability was significantly affected by gait speed for the GasMed and the SOL muscles. The decrease of F_ability for the SOL and the GasMed was accompanied by a decrease in the force–velocity multiplier. The peak muscle force for the SOL increased for the lowest speed compared to the higher speed, and for the TibAnt increased at high speed compared to low speed. In addition, F_ability f_AL, and f_V of the SOL predicted over 58% of NC_w and F_Max of the TibAnt accounts for 39.9% of the variance in NC_w.

Conclusion

The increase of NC_w with gait speed over the preferred walking speed can be partially explained by the decreasing capacity of the SOL muscle to produce muscle force and more specifically by the force–velocity relationship and an increase in muscle force for the TibAnt.

Anderson FC, Pandy MG (2003) Individual muscle contributions to support in normal walking. Gait Posture 17:159–169. https://doi.org/10.1016/S0966-6362(02)00073-5CrossRefPubMed

Arnold EM, Hamner SR, Seth A et al (2013) How muscle fiber lengths and velocities affect muscle force generation as humans walk and run at different speeds. J Exp Biol 216:2150–2160. https://doi.org/10.1242/jeb.075697CrossRefPubMedPubMedCentral

Baxter JR, Hast MW (2019) Plantarflexor metabolics are sensitive to resting ankle angle and optimal fiber length in computational simulations of gait. Gait Posture 67:194–200. https://doi.org/10.1016/J.GAITPOST.2018.10.014CrossRefPubMed

Besier TF, Sturnieks DL, Alderson JA, Lloyd DG (2003) Repeatability of gait data using a functional hip joint centre and a mean helical knee axis. J Biomech 36:1159–1168. https://doi.org/10.1016/S0021-9290(03)00087-3CrossRefPubMed

Bhargava LJ, Pandy MG, Anderson FC (2004) A phenomenological model for estimating metabolic energy consumption in muscle contraction. J Biomech 37:81–88. https://doi.org/10.1016/S0021-9290(03)00239-2CrossRefPubMed

Bohannon RW (1997) Comfortable and maximum walking speed of adults aged 20–79 years: reference values and determinants. Age Ageing 26:15–19. https://doi.org/10.1093/ageing/26.1.15CrossRefPubMed

Buchanan TS, Lloyd DG, Manal K, Besier TF (2004) Neuromusculoskeletal modeling: estimation of muscle forces and joint moments and movements from measurements of neural command. J Appl Biomech 20:367–395. https://doi.org/10.1123/jab.20.4.367CrossRefPubMedPubMedCentral

Das Gupta S, Bobbert MF, Kistemaker DA (2019) The metabolic cost of walking in healthy young and older adults—a systematic review and meta analysis. Sci Rep 9:1–10. https://doi.org/10.1038/s41598-019-45602-4CrossRef

Delp SL, Anderson FC, Arnold AS et al (2007) OpenSim: open-source software to create and analyze dynamic simulations of movement. IEEE Trans Biomed Eng 54:1940–1950. https://doi.org/10.1109/TBME.2007.901024CrossRefPubMed

Detrembleur C, Dierick F, Stoquart G et al (2003) Energy cost, mechanical work, and efficiency of hemiparetic walking. Gait Posture 18:47–55. https://doi.org/10.1016/S0966-6362(02)00193-5CrossRefPubMed

Deusinger RH (1978) Biomechanics and energetics of muscular exercise, 1st edn. Oxford University

di Prampero PE, Atchou G, Brückner JC, Moia C (1986) The energetics of endurance running. Eur J Appl Physiol Occup Physiol 55:259–266. https://doi.org/10.1007/BF02343797CrossRefPubMed

Donelan JM, Kram R, Kuo AD (2001) Mechanical and metabolic determinants of the preferred step width in human walking. Proc R Soc B Biol Sci 268:1985–1992. https://doi.org/10.1098/rspb.2001.1761CrossRef

Farris DJ, Sawicki GS (2012) The mechanics and energetics of human walking and running: a joint level perspective. J R Soc Interface 9:110–118. https://doi.org/10.1098/rsif.2011.0182CrossRefPubMed

Gerus P, Rao G, Berton E (2011) A method to characterize in vivo tendon force-strain relationship by combining ultrasonography, motion capture and loading rates. J Biomech 44:2333–2336. https://doi.org/10.1016/j.jbiomech.2011.05.021CrossRefPubMed

Gerus P, Rao G, Berton E (2012) Subject-specific tendon-aponeurosis definition in hill-type model predicts higher muscle forces in dynamic tasks. PLoS ONE. https://doi.org/10.1371/journal.pone.0044406CrossRefPubMedPubMedCentral

Gerus P, Rao G, Berton E (2013) Ultrasound-based subject-specific parameters improve fascicle behaviour estimation in Hill-type muscle model. Comput Methods Biomech Biomed Engin 5842:37–41. https://doi.org/10.1080/10255842.2013.780047CrossRef

Guidetti L, Meucci M, Bolletta F et al (2018) Validity, reliability and minimum detectable change of COSMED K5 portable gas exchange system in breath-by-breath mode. PLoS ONE 13:1–12. https://doi.org/10.1371/journal.pone.0209925CrossRef

Homsher E, Kean CJ (1978) Skeletal muscle energetics and metabolism. Annu Rev Physiol 40:93–131CrossRef

Homsher E, Mommaerts WFHM, Ricchiuti NV, Wallner A (1972) Activation heat, activation metabolism and tension-related heat in frog semitendinosus muscles. J Physiol 220:601–625. https://doi.org/10.1113/jphysiol.1972.sp009725CrossRefPubMedPubMedCentral

Hermens HJ, Freriks B, Disselhorst-Klug C, Rau G (2000) Development of recommendations for SEMG sensors and sensor placement procedures. J Electromyogr Kinesiol 10:361–374. https://doi.org/10.1016/S1050-6411(00)00027-4CrossRefPubMed

Himann JE, Cunningham DA, Rechnitzer PA, Paterson DH (1988) Age-related changes in speed of walking. Med Sci Sports Exerc 20:161–166. https://doi.org/10.1249/00005768-198820020-00010CrossRefPubMed

Kalron A, Menascu S, Frid L et al (2020) Physical activity in mild multiple sclerosis: contribution of perceived fatigue, energy cost, and speed of walking. Disabil Rehabil 42:1240–1246. https://doi.org/10.1080/09638288.2018.1519603CrossRefPubMed

Kirkpatrick S, Gelatt CD, Vecchi MP (1983) Optimization by simulated annealing. Science 220:671–680. https://doi.org/10.1126/science.220.4598.671CrossRefPubMed

Koelewijn AD, Dorschky E, van den Bogert AJ (2018) A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait. Comput Methods Biomech Biomed Engin 21:521–531. https://doi.org/10.1080/10255842.2018.1490954CrossRefPubMed

Lai A, Lichtwark GA, Schache AG et al (2015) In vivo behavior of the human soleus muscle with increasing walking and running speeds. J Appl Physiol 118:1266–1275. https://doi.org/10.1152/japplphysiol.00128.2015CrossRefPubMed

Lichtwark GA, Wilson AM (2008) Optimal muscle fascicle length and tendon stiffness for maximising gastrocnemius efficiency during human walking and running. J Theor Biol 252:662–673. https://doi.org/10.1016/j.jtbi.2008.01.018CrossRefPubMed

Liu MQ, Anderson FC, Pandy MG, Delp SL (2006) Muscles that support the body also modulate forward progression during walking. J Biomech 39:2623–2630. https://doi.org/10.1016/j.jbiomech.2005.08.017CrossRefPubMed

Lloyd DG, Besier TF (2003) An EMG-driven musculoskeletal model to estimate muscle forces and knee joint moments in vivo. J Biomech 36:765–776. https://doi.org/10.1016/S0021-9290(03)00010-1CrossRefPubMed

Manal K, Buchanan TS (2003) A one-parameter neural activation to muscle activation model: estimating isometric joint moments from electromyograms. J Biomech 36:1197–1202. https://doi.org/10.1016/S0021-9290(03)00152-0CrossRefPubMed

Mian OS, Thom JM, Ardigò LP et al (2006) Metabolic cost, mechanical work, and efficiency during walking in young and older men. Acta Physiol 186:127–139. https://doi.org/10.1111/j.1748-1716.2006.01522.xCrossRef

Mukaka MM (2012) Statistics corner: a guide to appropriate use of correlation coefficient in medical research. Malawi Med J 24:69–71PubMedPubMedCentral

Neptune RR, Sasaki K (2005) Ankle plantar flexor force production is an important determinant of the preferred walk-to-run transition speed. J Exp Biol 208:799–808. https://doi.org/10.1242/jeb.01435CrossRefPubMed

Neptune RR, Kautz SA, Zajac FE (2001) Contributions of the individual ankle plantar flexors to support, forward progression and swing initiation during walking. J Biomech 34:1387–1398. https://doi.org/10.1016/S0021-9290(01)00105-1CrossRefPubMed

Reid KF, Fielding RA (2012) Skeletal muscle power: a critical determinant of physical functioning in older adults. Exerc Sport Sci Rev 40:4–12. https://doi.org/10.1097/JES.0b013e31823b5f13CrossRefPubMedPubMedCentral

Thomas SA, Vega D, Arellano CJ (2021) Do humans exploit the metabolic and mechanical benefits of arm swing across slow to fast walking speeds? J Biomech. https://doi.org/10.1016/j.jbiomech.2020.110181CrossRefPubMed

Umberger BR (2010) Stance and swing phase costs in human walking. J R Soc Interface 7:1329–1340. https://doi.org/10.1098/rsif.2010.0084CrossRefPubMedPubMedCentral

Umberger BR, Gerritsen KGM, Martin PE (2003) A model of human muscle energy expenditure. Comput Methods Biomech Biomed Engin 6:99–111. https://doi.org/10.1080/1025584031000091678CrossRefPubMed

Winby CR, Lloyd DG, Kirk TB (2008) Evaluation of different analytical methods for subject-specific scaling of musculotendon parameters. J Biomech 41:1682–1688. https://doi.org/10.1016/j.jbiomech.2008.03.008CrossRefPubMed

Workman JM, Armstrong BW (1986) Metabolic cost of walking: equation and model. J Appl Physiol 61:1369–1374. https://doi.org/10.1152/jappl.1986.61.4.1369CrossRefPubMed

Zajac F (1989) Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng 17(4):359–411PubMed

Titel: How fiber dynamics of plantarflexor and dorsiflexor muscles based on EMG-driven approach can explain the metabolic cost at different gait speeds
verfasst von: Pauline Gerus
Elodie Piche
Olivier Guérin
Frederic Chorin
Raphaël Zory
Publikationsdatum: 03.01.2022
Verlag: Springer Berlin Heidelberg
Erschienen in: European Journal of Applied Physiology / Ausgabe 3/2022
Print ISSN: 1439-6319
Elektronische ISSN: 1439-6327
DOI: https://doi.org/10.1007/s00421-021-04881-4

Neu im Fachgebiet Arbeitsmedizin

Elterliches Belastungserleben, Unaufmerksamkeits‑/Hyperaktivitätssymptome und elternberichtete ADHS bei Kindern und Jugendlichen: Ergebnisse aus der KiGGS-Studie

Open Access ADHS Leitthema

Die Aufmerksamkeitsdefizit‑/Hyperaktivitätsstörung (ADHS) ist eine der häufigsten psychischen Störungen im Kindes- und Jugendalter [ 1 ]. In Deutschland beträgt die Prävalenz einer elternberichteten ADHS-Diagnose bei Kindern und Jugendlichen 4,4 % …

Substanzkonsum und Nutzung von sozialen Medien, Computerspielen und Glücksspielen unter Auszubildenden an beruflichen Schulen

Open Access Leitthema

Die Begrenzung von Schäden durch Substanzkonsum und andere abhängige Verhaltensweisen von Jugendlichen und jungen Erwachsenen ist ein wichtiges Anliegen der öffentlichen Gesundheit. Der Übergang von der Adoleszenz zum jungen Erwachsenenalter ist …

Berufsbelastung und Stressbewältigung von weiblichen und männlichen Auszubildenden

Leitthema

In der Öffentlichkeit wird die berufliche Ausbildung oftmals unter ökonomischen Gesichtspunkten diskutiert: Mit den geburtenstarken Jahrgängen gehen erfahrene Fachkräfte in Rente und von nachfolgenden Generationen rücken zu wenige Arbeitskräfte …

Rauschtrinken in der frühen Adoleszenz

COVID-19 Leitthema

Alkohol ist in Deutschland die mit Abstand am häufigsten konsumierte psychoaktive Substanz. Mehr als 2 Drittel aller Erwachsenen im Alter von 18 bis 64 Jahren (70,5 %) hat 2021 in den letzten 30 Tagen Alkohol konsumiert [ 1 ]. Von diesen …

Springer Medizin

Abstract

Purpose

Methods

Results

Conclusion

Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten

Weitere Artikel der Ausgabe 3/2022

Bioelectrical impedance analysis versus reference methods in the assessment of body composition in athletes

Fasting-Mimicking-Diet does not reduce skeletal muscle function in healthy young adults: a randomized control trial

Effect of live-fire training on ventricular-vascular coupling

Bi-exponential modelling of reconstitution kinetics in trained cyclists

Effect of a speed ascent to the top of Europe on cognitive function in elite climbers

New kids on the CPET: age-appropriate outdoor cardiopulmonary exercise testing in preschoolers

Neu im Fachgebiet Arbeitsmedizin

Elterliches Belastungserleben, Unaufmerksamkeits‑/Hyperaktivitätssymptome und elternberichtete ADHS bei Kindern und Jugendlichen: Ergebnisse aus der KiGGS-Studie

Substanzkonsum und Nutzung von sozialen Medien, Computerspielen und Glücksspielen unter Auszubildenden an beruflichen Schulen

Berufsbelastung und Stressbewältigung von weiblichen und männlichen Auszubildenden

Rauschtrinken in der frühen Adoleszenz