Neuromuscular Fatigue in Running: What EMG Reveals
Runners rarely blame their quadriceps. When a session unravels, the story is usually about lungs, a heart rate drifting upward, or legs that simply feel heavy. Strip away the subjective language and something more specific is happening in the tissue itself: force output falls, activation patterns shift, and individual muscles fatigue at different rates, often long before the cardiovascular system is anywhere near its ceiling.
This is the layer of running fatigue that a watch cannot see and a runner cannot accurately self-report. It is also the layer surface EMG was built to measure.
Why This Matters
Strength training has an enormous evidence base on muscle-level fatigue, and it is well covered elsewhere. Running is different. The dominant feedback loop for most runners is pace, heart rate, and perceived effort, three signals that describe the whole-body response but say very little about what any single muscle is doing under load, rep after rep, kilometre after kilometre.
That gap matters more as hybrid training becomes normal. Lifters are running, runners are lifting, and the muscles doing the work, quadriceps, hamstrings, and calves, are shared across both. Understanding how those muscles actually fatigue during running, not just how the runner feels, is directly relevant to anyone using EMG to interpret a session.
Central and Peripheral Fatigue Are Not the Same Signal
Exercise physiologists split fatigue into two broad categories. Central fatigue is a drop in the nervous system's drive to the muscle, the brain and spinal cord asking for less than they could. Peripheral fatigue is contractile failure within the muscle fibre itself, the tissue unable to produce the same force even when it is fully activated.
A 2021 study of trail runners after 40 to 170 km races isolated where plantar flexor fatigue (the calf muscles driving push-off) was actually coming from. Maximal voluntary contraction fell by 29%, with voluntary activation down 12%.¹ The more revealing detail was in the reflex data: V-wave amplitude, a proxy for the signal reaching the muscle, dropped 35% in the soleus and 28% in the gastrocnemius medialis, while the H-reflex, a marker of spinal excitability, stayed unchanged. The fatigue was originating above the spinal cord, not within it.¹ That distinction matters because central and peripheral fatigue respond to completely different interventions, and a single global "fatigue score" collapses two different problems into one number.
What Ultra-Distance Racing Reveals About Muscle-Specific Fatigue
Ultra-distance events make muscle-specific fatigue easy to see because the scale of the stress is so large. In a study of a 166 km mountain ultra-marathon with 9,500 m of elevation change, knee extensor strength fell by 35% and plantar flexor strength by 39% immediately after finishing, alongside a creatine kinase rise from 144 to over 13,600 UI/L.² Full recovery of force capacity took roughly 16 days.²
Pacing changes the picture substantially. A study following runners through the world's most demanding mountain ultra-marathon, a 330 km race with 24,000 m of elevation gain and a finishing time over 122 hours, found strength losses of only 24 to 26% post-race, smaller than the 166 km event above despite covering twice the distance.³ The authors attributed this to pacing strategy: runners moving at an intensity low enough, for long enough, appear to protect contractile function even as total work performed climbs dramatically.³
Sex also shapes the fatigue profile. Comparing matched male and female runners across trail races from 40 to 171 km, women showed smaller knee extensor strength losses than men (27% vs 36%), and in shorter races showed less peripheral fatigue in the plantar flexors as well.⁴ Despite these differences, running economy (the metabolic cost of covering ground) degraded similarly in both sexes, suggesting muscle-level fatigue and whole-body efficiency loss are not perfectly linked.⁴
You Do Not Need an Ultramarathon
Muscle-level fatigue is not an ultra-distance phenomenon. It shows up inside a single easy session.
In a study of recreational runners completing a 5 km high-intensity run, quadriceps maximal voluntary isometric contraction dropped from an average of 305 N to 259 N, a statistically significant fall with no change on muscle ultrasound, pointing to metabolic and neural causes rather than structural damage.⁵ Blood lactate rose from 0.8 to 6.9 mmol/L over the same run.⁵
Recovery timelines are longer than most runners assume. A study comparing three different high-intensity running protocols totalling roughly 8 km found voluntary activation was still depressed four hours after finishing, with peak force reduction persisting past six hours.⁶ Neural drive reduction was largest for runners working near their respiratory compensation point, a common training intensity for tempo-style sessions, and subjective leg heaviness stayed elevated for at least six hours post-run.⁶
Terrain changes the fatigue mechanism rather than just its size. A review of graded running noted that downhill running produces low-frequency fatigue, a pattern linked to mechanical stress at the interface between the sarcoplasmic reticulum and T-tubule inside the muscle fibre, while uphill running is driven more by metabolite accumulation, particularly inorganic phosphate.⁷ Two runs that feel similarly hard on a watch can be fatiguing the muscle through entirely different pathways.⁷
The Muscle Does Not Fatigue Evenly
A fatigued muscle is not simply a weaker version of a fresh one. It recruits differently.
Research on the medial gastrocnemius during fatigued locomotion found that both the spatial location and the frequency characteristics of myoelectric activation shift as fatigue develops, meaning the region of the muscle doing the most work moves during a run, not just the total amount of activity.⁸ Separate work on lower-limb muscle synergies during running-induced fatigue found the coordination patterns across muscle groups reorganise as fatigue accumulates, changing how load is distributed between synergist muscles rather than simply reducing output uniformly.⁹ A related study on activation characteristics and synergistic patterns during fatiguing running reported the same trend: the muscles sharing a movement do not fatigue in lockstep, they redistribute the work between themselves.¹⁰ In runners with a higher body mass, fatiguing running has also been shown to alter co-contraction between opposing muscle groups at the joint, a pattern with plausible relevance to overuse injury risk given the altered loading it implies.¹¹
The practical implication is that a single "how fatigued am I" number, whatever the input, is always a simplification. The underlying reality is regional and dynamic.
Can a Single Surface Sensor Actually Track This?
All of the findings above depend on EMG being a reasonably faithful window into muscle activity during a task that involves constant movement, footstrike impact, and postural sway, a much harder recording environment than a seated isometric contraction in a lab.
Foundational reliability work testing EMG across leg, torso, and arm muscles during running found the signal is usable, but precision varies meaningfully by muscle and by stride phase, and motion artifact is a real constraint that has to be managed rather than ignored.¹² That caveat is worth taking seriously. Amplitude and frequency shifts in surface EMG during fatiguing exercise are well documented and physiologically real, but they are not a precise measurement of force output, and a wearable reading them should be interpreted as an estimate of the underlying pattern, not a lab-grade quantification of it.
What This Means in Practice
The calf, specifically the soleus and gastrocnemius, is one of the more informative sites for a runner to have instrumented. It is the last muscle group in the chain before force reaches the ground, it shows measurable central fatigue after prolonged running, and its activation pattern shifts spatially as a session wears on.¹ ⁸ For a hybrid athlete moving between a lifting session and a run in the same week, seeing that the same muscle is starting a run already partially fatigued, rather than relying on how the legs subjectively feel, is a genuinely different piece of information.
None of this replaces pace, heart rate, or perceived effort. It sits alongside them, adding a signal that specifically reflects what the working muscle is doing, which is exactly the layer the existing tools were never built to see.
Key Takeaways
Central fatigue (reduced nervous system drive) and peripheral fatigue (reduced contractile capacity within the muscle) are distinct mechanisms that respond to different training and recovery strategies.
Muscle-level fatigue in the quadriceps and calves is measurable within a single 5 km run, not just after ultramarathon-length efforts.
Recovery of neuromuscular function can lag well behind how quickly heart rate or perceived effort normalises, sometimes by six hours or more after a hard session.
Fatigue changes where and how a muscle activates, not just how much, which is why a single aggregate number will always miss part of the picture.
Surface EMG during running is a real, physiologically grounded signal, but it is an estimate of activation pattern, not a precise measurement of force, and should be read that way.
References
Espeit L, Brownstein CG, Royer N, Besson T, Martin V, Millet GY, Lapole T. Central fatigue aetiology in prolonged trail running races. Experimental Physiology. 2021;106(3):663-672. doi:10.1113/EP089177
Millet GY, Tomazin K, Verges S, Vincent C, Bonnefoy R, Boisson RC, Gergelé L, Féasson L, Martin V. Neuromuscular consequences of an extreme mountain ultra-marathon. PLoS One. 2011;6(2):e17059. doi:10.1371/journal.pone.0017059
Saugy J, Place N, Millet GY, Degache F, Schena F, Millet GP. Alterations of neuromuscular function after the world's most challenging mountain ultra-marathon. PLoS One. 2013;8(6):e65596. doi:10.1371/journal.pone.0065596
Besson T, Parent A, Brownstein CG, Espeit L, Lapole T, Martin V, Royer N, Rimaud D, Sabater Pastor F, Singh B, Varesco G, Rossi J, Temesi J, Millet GY. Sex Differences in Neuromuscular Fatigue and Changes in Cost of Running after Mountain Trail Races of Various Distances. Medicine and Science in Sports and Exercise. 2021;53(11):2374-2387. doi:10.1249/MSS.0000000000002719
Findrik K, Šušnjara P, Kuna D. Indicators of Neuromuscular, Metabolic and Perceptual Fatigue Following a 5 km Run. Sports (Basel). 2026;14(7). doi:10.3390/sports14070262
Dutra YM, Mendonça PT, Goodall S, Zagatto AM. Neuromuscular Fatigue and Perceived Fatigability in the Hours Following a High-Intensity Endurance Running Depend on the Exercise Protocol. European Journal of Sport Science. 2026;26(8):e70176. doi:10.1002/ejsc.70176
Giandolini M, Vernillo G, Samozino P, Horvais N, Edwards WB, Morin JB, Millet GY. Fatigue associated with prolonged graded running. European Journal of Applied Physiology. 2016;116(10):1859-73. doi:10.1007/s00421-016-3437-4
Schlink BR, Nordin AD, Brooks CN, Ferris DP. Fatigue induces altered spatial myoelectric activation patterns in the medial gastrocnemius during locomotion. Journal of Neurophysiology. 2021;125(5):2013-2023. doi:10.1152/jn.00602.2020
Xu Y, Yang Y, He S, Yang C, Zhang S, Fu W, Li L. Running-induced fatigue influences lower extremity muscle synergy and related biomechanics. Gait & Posture. 2025;119:163-170. doi:10.1016/j.gaitpost.2025.03.008
Li Z, He K. Effects of fatigue on the activation characteristics and synergistic patterns of lower limb muscles during running. Frontiers in Physiology. 2026;17:1741432. doi:10.3389/fphys.2026.1741432
Jafarnezhadgero A, Moradzadeh N, Mirzang EF, Sajedi H, Dixon S, Akrami M. Influence of a fatiguing exercise on lower limb electromyographic activities and co-contraction in overweight females during running. PLoS One. 2025;20(5):e0322167. doi:10.1371/journal.pone.0322167
Smoliga JM, Myers JB, Redfern MS, Lephart SM. Reliability and precision of EMG in leg, torso, and arm muscles during running. Journal of Electromyography and Kinesiology. 2010;20(1):e1-9. doi:10.1016/j.jelekin.2009.09.002
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