A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises
Background: Objective training load (TL) indexes used in resistance training lack physiological significance. This study was aimed to provide a muscle physiology-based approach for quantifying TL in resistance exercises (REs). Methods: Following individual torque–velocity profiling, fifteen particip...
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2025-01-01
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| author | Frank Imbach Stéphane Perrey Thomas Brioche Robin Candau |
| author_facet | Frank Imbach Stéphane Perrey Thomas Brioche Robin Candau |
| author_sort | Frank Imbach |
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| description | Background: Objective training load (TL) indexes used in resistance training lack physiological significance. This study was aimed to provide a muscle physiology-based approach for quantifying TL in resistance exercises (REs). Methods: Following individual torque–velocity profiling, fifteen participants (11 healthy males, stature: 178.36 ± 3.95 cm, and body mass (BM): 77.48 ± 7.74 kg; 4 healthy females, stature: 169.25 ± 5.03 cm, and body mass: 60.62 ± 3.91 kg) performed isokinetic leg extension exercise sessions at low, moderate, and high intensities (LI, MI, and HI, respectively). Systemic and local physiological responses were measured, and sessions were volume-equated according to the “volume-load” (VL) method. Results: Significant differences were found between sessions in terms of mechanical work (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.05</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula>, for LI-MI and MI-HI, respectively), averaged normalised torque (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula>), mechanical impulse (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula>), and rate of force development (RFD, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula> for LI-MI). RFD was mainly impacted by the accumulation of repetitions. Muscle function impairments mainly occurred at low intensities–long series, and high intensities, supported by greater RFD rate decay and changes in electromyographic activity. Therefore, accounting for muscle fatigue kinetics within objective TL indexes and using dimension reduction methods better described physiological responses to RE. Conclusions: A generic equation of muscle fatigue rise could add value to TL quantification in RE. Considering other training-related information and TL indexes stands essential, applicable to field situations and supports the multidimensional facet of physiological responses to RE. |
| format | Article |
| id | doaj-art-f1f370f2d270413190f95cb07bb44d7e |
| institution | Kabale University |
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| language | English |
| publishDate | 2025-01-01 |
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| series | Sports |
| spelling | doaj-art-f1f370f2d270413190f95cb07bb44d7e2025-01-24T13:49:52ZengMDPI AGSports2075-46632025-01-011311310.3390/sports13010013A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance ExercisesFrank Imbach0Stéphane Perrey1Thomas Brioche2Robin Candau3Seenovate, 34000 Montpellier, FranceEuroMov Digital Health in Motion, University of Montpellier, IMT Mines Alès, 34000 Montpellier, FranceDMeM, University of Montpellier, INRAE, 34000 Montpellier, FranceDMeM, University of Montpellier, INRAE, 34000 Montpellier, FranceBackground: Objective training load (TL) indexes used in resistance training lack physiological significance. This study was aimed to provide a muscle physiology-based approach for quantifying TL in resistance exercises (REs). Methods: Following individual torque–velocity profiling, fifteen participants (11 healthy males, stature: 178.36 ± 3.95 cm, and body mass (BM): 77.48 ± 7.74 kg; 4 healthy females, stature: 169.25 ± 5.03 cm, and body mass: 60.62 ± 3.91 kg) performed isokinetic leg extension exercise sessions at low, moderate, and high intensities (LI, MI, and HI, respectively). Systemic and local physiological responses were measured, and sessions were volume-equated according to the “volume-load” (VL) method. Results: Significant differences were found between sessions in terms of mechanical work (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.05</mn></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula>, for LI-MI and MI-HI, respectively), averaged normalised torque (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula>), mechanical impulse (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula>), and rate of force development (RFD, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.001</mn></mrow></semantics></math></inline-formula> for LI-MI). RFD was mainly impacted by the accumulation of repetitions. Muscle function impairments mainly occurred at low intensities–long series, and high intensities, supported by greater RFD rate decay and changes in electromyographic activity. Therefore, accounting for muscle fatigue kinetics within objective TL indexes and using dimension reduction methods better described physiological responses to RE. Conclusions: A generic equation of muscle fatigue rise could add value to TL quantification in RE. Considering other training-related information and TL indexes stands essential, applicable to field situations and supports the multidimensional facet of physiological responses to RE.https://www.mdpi.com/2075-4663/13/1/13strength trainingrate of force developmentphysiological responsesmuscle fatiguemodellingprincipal component analysis |
| spellingShingle | Frank Imbach Stéphane Perrey Thomas Brioche Robin Candau A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises Sports strength training rate of force development physiological responses muscle fatigue modelling principal component analysis |
| title | A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises |
| title_full | A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises |
| title_fullStr | A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises |
| title_full_unstemmed | A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises |
| title_short | A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises |
| title_sort | muscle physiology based framework for quantifying training load in resistance exercises |
| topic | strength training rate of force development physiological responses muscle fatigue modelling principal component analysis |
| url | https://www.mdpi.com/2075-4663/13/1/13 |
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