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Acute Photobiomodulation by LED Does Not Alter Muscle Fatigue and Cycling Performance


Author Information
Medicine & Science in Sports & Exercise: November 2020 - Volume 52 - Issue 11 - p 2448-2458
doi: 10.1249/MSS.0000000000002394



The authors of “Acute Photobiomodulation by LED Does Not Alter Muscle Fatigue and Cycling Performance” () report an amendment to the acknowledgments in their article. They add the following:

The authors thank Ph.D. Fábio Augusto Barbieri who lent us his EMG device for data acquisition and thank Luiz Henrique Palucci Vieira who lent us his MatLab algorithm for calculating graphs standard deviation.

Medicine & Science in Sports & Exercise. 53(5):1099, May 2021.

Muscle fatigue is defined as the temporary impairment in the ability of the neuromuscular system to voluntarily produce desired levels of strength and power (1). The fatigue process may be caused by changes at any level of the motor pathway (central and/or peripheral components) and is also linked to disturbances in acid–base balance, cardiorespiratory control, and the homeostatic milieu of skeletal muscle and the bloodstream (1,2). Because much attention is placed toward optimizing human performance, the discovery of ergogenic aids to delay the onset of fatigue has been a focus among sport and exercise scientists (3).

Photobiomodulation therapy (PBMT) is a nonthermal electromagnetic radiation that utilizes visible or invisible lights through laser or light-emitting diode sources. Recent research has suggested that PBMT may be an effective strategy for improving physical performance or attenuating fatigue after exercise (4–7). The underlying mechanisms that explain the ergogenic effects of PBMT seem to be linked to improved mitochondrial activity and adenosine triphosphate synthesis (8), microcirculation (9), tissue oxygenation (10), and clearance of metabolic by-products (5). Several studies have demonstrated positive effects of PBMT on fatigue and performance in a range of single-joint and multijoint exercises (5–7,11,12). However, contradictory findings are also presented among other studies that show no effect of PBMT in this scenario (13–16). It is argued that the lack of agreement in the reported effects of PBMT could be due to different configurations of treatment parameters between studies (4,17) and flaws in the experimental design (i.e., inappropriate selection of the exercise to assess performance and of the tests to assess muscle fatigue).

The treatment parameters of PBMT include light wavelength (in nanometers), power of the light (in millliwats), time of irradiation (in seconds), and the total dose delivered over the target tissue (in joules; which is calculated as seconds multiplied by milliwatts). Of these, varying the total dose delivered seems to provide the greatest effect on the effects of PBMT. Indeed, high exposure dosages to the target tissue(s) will suppress cell activity, whereas low doses show no effect (18). Although the delivery of a range between 60 and 300 J to a given muscle group has been suggested as an effective dose window for improving performance, the supportive findings are not consistent (4), and hence, further research is warranted.

Furthermore, most of the previous studies investigating the effects of PBMT on muscle fatigue have utilized exhaustive exercise trials, such as running and cycling, or involved only flexion/extension repetitions of a single joint (5–7,11,12). Unfortunately, such methodologies have failed to fully address muscle fatigue because it differs from task failure and specifically relates to the production of muscular strength and power (1). Consequently, there are no available studies that have determined whether PBMT affects neuromuscular system force production immediately after strenuous exercise. Likewise, the extent to which PBMT influences the central and peripheral physiological mechanisms that underpin muscle fatigue is currently unknown.

The assessment of force generation through supramaximal peripheral nerve stimulation during rest and maximal isometric contractions (i.e., twitch interpolation technique) while EMG activity is concurrently monitored has been suggested as a robust protocol for providing insight toward the central and peripheral contributions of neuromuscular fatigue (19). However, this type of assessment protocol has never been investigated in the realm of PBMT. Such research is needed for a more complete understanding toward the mechanisms and effectiveness of PBMT on mitigating fatigue and improving performance.

The main purpose of the present study was to investigate the possible ergogenic effect of PBMT in comparison to a placebo on muscle fatigue, from global, central, and peripheral perspectives, induced by severe-intensity cycling at a constant load. The selected outcome measures in the study were exploring EMG activity of selected knee and hip extensor muscles, blood acid–base balance, metabolite and ion concentrations, and respiratory gas-exchange responses during exercise. A secondary purpose was to investigate the effects of two different doses of PBMT. Considering the supposed influences of PBMT to increase mitochondrial activity and blood supply to active skeletal muscle, it was hypothesized that both treatment doses would elicit a longer duration of exercise until exhaustion, and less impairment of the selected markers of global, central, and peripheral neuromuscular function.


The present investigation was composed of two independent studies. Study 1 investigated the effect of two treatments of PBMT in comparison to a placebo on the following: 1) EMG activity during constant-load, severe-intensity cycling, and 2) markers of global, central, and peripheral neuromuscular function after different exercise bouts that were duration matched. Study 2 aimed to investigate the effects of the two treatments of PBMT in comparison to a placebo on time until exhaustion and markers of physiological disturbance with similar bouts of cycling exercise as study 1. It was determined that this design was necessary in order to investigate the specific indicators of muscle fatigue by controlling for duration in study 1, but address the effect regarding time to exhaustion in study 2.


The required sample size of 9 participants in study 1 and 13 in study 2 was estimated previously using G*power software (20). An α of 0.05 and power of 0.80 were used as input parameters. Power was determined for study 1 by utilizing the previously demonstrated percent change in peak isometric force of knee extensors after a fatiguing protocol that was preceded by either a placebo treatment (−30.64%) or PBMT at a dosage of 10 J (−13.45%) (11). The parameters that were used to determine power for study 2 were the time to exhaustion during cycling at a maximal power output during a placebo treatment (149 s) versus the one preceded by PBMT at 135-J dosage (171 s) as reported by Lanferdini et al. (6). The SD of the conditions was calculated with a specific algorithm from MatLab R2015a software (version:; The MathWorks, Inc., Natick, MA; see text file, Supplemental Digital Content 1, which describes in detail the algorithm used,

Forty-one healthy male cyclists (track or road cyclists) volunteered to participate. After completing a medical and health history questionnaire, 31 met the following inclusion criteria: 1) absence of any cardiovascular or metabolic disorders, 2) absence of recent (<6 months) musculoskeletal and joint injuries, and 3) absence of recent (<6 months) regular use of any substance that could act as ergogenic aids (e.g., creatine, β-alanine). The exclusion criteria were being absent from two or more experimental trials (n = 1), performing exercise or ingesting a substance known to alter physical performance (e.g., caffeine, sodium bicarbonate, alcoholic drinks) within 24 h before experimental sessions (n = 2), presented any musculoskeletal disorder, initiated the use of nutritional or pharmacological substances during the experiments, or did not reach exhaustion during trials based on self-report (n = 1). In the end, 27 participants completed the data collection and analysis processes. Fourteen participants completed study 1 (age, 32 ± 6 yr; height, 178.7 ± 7.0 cm; body mass, 78.5 ± 14.1 kg; weekly training volume, 103 ± 52 km·wk−1, peak oxygen uptake (V˙O2peak),: 48.86 ± 6.69 mL·kg−1·min−1). Thirteen participants completed study 2 (age, 30 ± 9 yr; height, 176.7 ± 7.0 cm; body mass, 72.4 ± 10.4 kg; weekly training volume, 118 ± 72 km·wk−1; V˙O2peak, 48.10 ± 4.81 mL·kg−1·min−1; Figure, Supplemental Digital Content 2, which presents the flowcharts of both studies, Participants were classified as recreational cyclists according to specific guidelines to categorize subject groups in sport science research (21). In addition, women were not included primarily because of the potential effect that the variation in menstrual cycle phases could have on the performance variables included in the study (22).

Before starting the data collection processes, the participants were informed of all potential risks and benefits involved in the procedures and then provided written informed consent. All experimental procedures were approved by the São Paulo State University Research Committee (Protocol n.78657817.9.0000.5398) and were conducted in accordance with the Declaration of Helsinki (1964).

Experimental Design

Both studies were conducted in a pseudorandomized and balanced, double-blind, and crossover design. All participants visited the laboratory on six different occasions in each study. The participants performed all procedures during the same time of the day, with laboratory visits separated by a minimum of 48 h and a maximum of 72 h. All cycling trials were performed on an electromagnetic-braked cycle ergometer (Lode-Excalibur Sport; Lode BV, Groningen, the Netherlands). Before the start of data collection, each participant self-selected a specific, steady-state cadence (±5 rpm) between a range of 60 and 85 rpm for the exercise trials. During the experiments, the temperature in the laboratory was 19°C ± 1°C.

In both studies, the participants initially completed a maximal graded exercise test on the electromagnetic-braked cycle ergometer with gas-exchange analysis to determine the V˙O2peak, the maximal aerobic power, and the power output at respiratory compensation point. During the second visits, the participants completed a bout of constant-load, severe-intensity cycling until exhaustion.

For the third visit of study 1, the same bout of cycling until exhaustion was repeated and considered the control condition as the specific time until exhaustion (tlim) was recorded and used to equalize the duration of the subsequent laboratory trials. From the fourth to sixth visits, participants received one of the treatments of PBMT at 260, 130, or 0 J. After PBMT, the same bout of cycling as the control condition (i.e., identical intensity and duration) was performed. EMG activity of rectus femoris, vastus lateralis, biceps femoris, and gluteus maximus of the dominant lower limb (determined by self-report) was monitored. The evaluation of neuromuscular function took place before and immediately after each bout of cycling exercise. Data collection was carried out even if the tlim of the control condition was not obtained, to investigate the possible negative influence of PBMT. In addition, capillary blood samples were collected 5 and 7 min after exercise for all conditions to measure the peak of blood lactate concentration (Fig. 1).

General experimental design (study 1 and study 2). GXT, graded exercise test until exhaustion; NA, neuromuscular assessment; PMBTs, photobiomodutalion therapies; PBMT130, PBMT with 130 J-dose; PBMT260, PBMT with 260-J dose; PBMPLA, PBMT with 0-J dose (placebo condition).

During the third visit of study 2, the participants again performed the cycling exercise until exhaustion as familiarization to reduce variation in tlim in subsequent visits. From the fourth to sixth visits, participants received one of the treatments of PBMT (i.e., 260, 130, or 0 J) and then performed the cycling exercise until exhaustion. Respiratory gas-exchange measures, EMG activity of selected lower limb musculature (i.e., the same procedures of study 1), and capillary blood samples were collected during and immediately after each exercise trial (Fig. 1).

Study 1 Procedures

Graded exercise test

Initially, a warm-up of 5 min at 75 W was performed. After 5 min of passive recovery, the graded exercise test was initiated at 100 W with increases of 25 W occurring at 2-min increments until voluntary exhaustion, defined as the inability to maintain the preset cadence range for 5 s (23). During the graded exercise test, respiratory responses were registered breath-by-breath using a stationary gas analyzer (Quark CPET; Cosmed, Rome, Italy), which was previously calibrated in accordance with the manufacturer’s instructions. Data were smoothed every 10 points and interpolated every 1 s using OriginPro version 8.0 software (OriginLab Corporation, Northampton, MA). Oxygen uptake (V˙O2) was determined as the average of the final 30 s of each stage. The highest V˙O2 average attained during graded exercise test was recorded as V˙O2peak. The maximal aerobic power was assumed as the highest power reached during graded exercise test of the last completed stage. For uncompleted stages lasting more than 30 s, the maximal aerobic power was estimated using equation 1 (24). The E/V˙CO2 versus power output curve was divided into two regions fitted by a two-line regression, and the respiratory compensation point was considered the intersection point (25).

maximal aerobic power=final stageW+duration of the uncompleted stage in seconds/120×25[1]

Constant-load, severe-intensity cycling

The exercise intensity was determined by using equation 2 as 60% of the difference between maximal aerobic power and power output at respiratory compensation point ([Δ60%], severe-intensity domain) (26). This specific cycling until exhaustion protocol has been shown to elicit impairments in the neuromuscular system (26) and hence is useful for determining the effect of PBMT on muscle fatigue. Before all exercises, participants performed a 5-min warm-up at 60% of maximal aerobic power, followed by four all-out sprints of 5 s. The constant-load, severe-intensity bout of cycling began after 4 min of passive recovery.

Δ60%=((maximal aerobic powerpower outputatrespiratory compensation point)×0.6)+power outputatrespiratory compensation point[2]

Force data acquisition

Participants performed two 5-s knee extension maximal voluntary contractions (MVC) with the dominant lower limb, interspaced by 1 min, before and immediately (1 min and 26 ± 30 s) after the bouts of cycling exercise. MVC was carried out in a specially designed chair maintaining knee and hip flexion at 90°, with the thorax and waist of the participants secured by specialized straps. A metal rod was attached to the ankle and connected to a load cell (MK Controle, São Paulo, Brazil) to ensure that the same angle torque was repeated during contractions, while avoiding peak noises in the force measurement. The load cell signal was acquired by an analog data acquisition mode (NI 6009; NI Instruments, Austin, TX) with a sample rate of 1000 Hz, and digitally filtered by a second-order Butterworth filter in MatLab R2015a (version:; The MathWorks, Inc.). Before each test, the load cell was calibrated using known weights to construct a linear regression (r2 > 0.99). The peak force (Fpeak) of MVC was determined as the mean of 100 ms during the force plateau and was used as a marker of global neuromuscular function (intraclass correlation coefficient of 0.99) (27).

Peripheral nerve stimulation

Peripheral nerve stimulation was delivered on the most sensitive site of the femoral triangle (cathode) and anterior to the greater trochanter of the femur (anode) by the high-voltage electrical stimulator (Bioestimulador V2 400 V peak-to-peak; Insight, São Paulo, Brazil) through carbon-rubber electrodes (dimensions, 5 × 5 cm). The optimal intensity of stimulations was determined individually before each assessment by the application of consecutive incremental doublet stimulus on the relaxed muscle (100 Hz, starting with 80 mA with 20-mA increments) until reaching the force plateau (observed with an average of 195 ± 25 mA for all participants in the last three sessions of the study 1). The maximal electrical current achieved (in milliamperes) was recorded, and supramaximal stimulation was ensured by increasing the final intensity by 20% (28).

Doublet high-frequency stimulation (i.e., square wave, 100 Hz, pulse duration of 1 ms) was delivered during MVC (~2nd s). With relaxed muscle, doublet high-frequency, single, and doublet low-frequency (i.e., 10 Hz) stimulations were respectively delivered 5, 10, and 15 s after MVC. The amplitude of the force signal superimposed by the doublet high-frequency stimuli during MVC and the force produced by the high-frequency stimuli at rest after MVCs (HFForce) were used to measure the percentage of voluntary central neuromuscular activation (i.e., central fatigue, VA%) through Equation 3 (28). Furthermore, the HFForce was used to measure general peripheral neuromuscular function, and the ratio between the force amplitudes produced by the doublets of low and high frequency at rest (HFForce/LFForce) was calculated and used as an indicator of low-frequency muscle fiber function (19).

VA%=(1(superimposed force×(force levelatstimulation/Fpeak)/HFForce))×100[3]

Surface EMG

EMG signals were acquired through two devices in the study, each with a signal frequency of 2000 Hz. The Wave Wireless EMG device (Cometa System, Milan, Italy) was utilized during the exercise bouts. However, considering that it was incompatible with the peripheral nerve stimulation procedure, a New Miotool EMG device (Miotec, Rio Grande do Sul, Brazil) was used during MVC. Before electrode placement, the skin sites were shaved, lightly abraded, and cleaned with rubbing alcohol. Ag/AgCl electrodes (recording area, 78.5 mm2; Medi-trace, Dublin, Ireland) were placed over the vastus lateralis (1/3 distal) of the dominant lower limb to measure EMG responses during MVCs, with a ground electrode placed on the patella (29). To assess responses during cycling, electrodes were positioned on the rectus femoris, vastus lateralis, biceps femoris, and gluteus maximus of the dominant lower limb according to the Surface Electromyography for Non-Invasive Assessment of Muscles recommendations (30).

The EMG activity was posteriorly band-pass filtered (20–500 Hz). During MVC, the root mean square (RMS) and median frequency (MdF) of 1 s of force plateau were calculated (RMSMVC and MdFMVC, respectively) and used as indicators of general neuromuscular discharge magnitude and rate, respectively (19). The peak-to-peak maximal amplitude and duration evoked by single stimulus (M-wave, [M-waveamp], [M-wavedur]) were calculated and used as an indicator of peripheral neural system conductibility function (19). During the exercise trials in study 1, the average RMS and MdF for four bands (0%–25%, 25%–50%, 50%–75%, and 75%–100%) were calculated, based on the tlim reached in the control condition. In study 2, the RMS and MdF for four bands (0%–25%, 25%–50%, 50%–75%, and 75%–100%) were calculated based on the shortest tlim reached between the three conditions, and for exhaustion, considering the mean values of the last 30 s of exercise in each condition. In both studies, the RMS and MdF values were expressed relative to the peak values observed in the placebo condition of each study. The software MatLab R2015a was also used to perform this analysis, and the values were normalized by the highest values observed in the control condition.

Blood sample collection and analysis

Blood samples (25 μL) were collected from the ear lobe using heparinized capillary tubes 5 and 7 min after the bouts of constant-load, severe-intensity cycling to measure the peak of blood lactate concentration [La] after exercise. Immediately after all collections, blood samples were deposited into microtubes containing 50 μL of sodium fluoride at 1% and posteriorly analyzed in an electrochemical analyzer (YSI 2900 Stat Plus, Yellow Springs Instruments, OH).

PBMT and placebo intervention

The interventions were performed ~15 min before cycling exercises on the fourth, fifth, and sixth visits using a multidiode array (Fig. 2). The hip and knee extensor muscles were chosen to be treated because of their essential contributions to cycling exercises (31). A multidiode array was used in an attempt to cover the primary muscle groups active during cycling, providing large and homogenous tissue irradiation as shown previously (32) and recently (33). The PBMT doses (total energy delivered [in joules]) in the current study were based on systematic reviews (33,34) regarding PBMT effects on physical performance improvements, consisting of 260 J (PBMT260) and 130 J (PBMT130). The placebo condition (PBMTPLA) consisted of fake irradiation with the multidiode array turned off while the timer was running (i.e., 0 J). An investigator not involved in data collection and processing performed all interventions. The order of treatments was chosen through simple balanced pseudorandomization. In all conditions, the multidiode array was kept in direct contact with the skin surface (i.e., 90° angle), applying slight pressure. In order to ensure blinding, participants were blindfolded and wore headphones (listening to a standard song) during the treatments.

Parameters of multidiode array and photobiomodulation therapy. IR, infrared; PBMT130, photobiomodulation therapy with 130-J dose; PBMT260, photobiomodulation therapy with 260-J dose; PBMTPLA, PBMT with 0-J dose (placebo condition); R, red.

Study 2 Procedures

The graded exercise test and the treatments procedures (PBMT and placebo) were performed following the same procedures as study 1. The constant-load, severe-intensity cycling bouts were performed similar to study 1, except at the third visit, which was also used for familiarization, and from the fourth to sixth visits, where exercise was performed until exhaustion.

Respiratory gas-exchange measure and analysis during cycling exercise

During the constant-load, severe-intensity cycling exercises, the respiratory responses were recorded following the same procedures of the graded exercise test. Before the cycling exercise, resting responses were collected during the final 2 min of a 5-min period of motionless, quiet sitting. Two time windows were calculated (i.e., 50% and 100%) based on the shortest tlim reached in the final three visits, to control for duration for comparison between the three conditions. The mean data of the final 30 s were used to represent each time window, and the analysis was carried out similar to the graded exercise test with the following variables recorded: V˙O2, E, RER, ventilatory equivalent for oxygen (E/V˙O2), and ventilatory equivalent for carbon dioxide (E/V˙O2). In addition, the energy contribution from the oxidative pathway was estimated by the trapezoidal method using specialized software (OriginPro version 8.0; OriginLab Corporation), assuming the value as the difference between the areas under the curve of V˙O2 measured during cycling versus the resting state (35).

Blood sample collection and analysis

Blood sample collections were also performed in study 2 to measure the peak of [La] after exercise (as described in study 1). Collections at rest and during four time windows of the cycling exercise bouts were carried out matched at 25%, 50%, 75%, and 100% of the time to attain 90% of effort recorded during the familiarization trial. These outcomes were used to calculate the mathematical area under the curve of [La] during exercise, through the software OriginPro 8.0, and the results obtained plotted (Y axis) versus the four moments of collection (X axis), deducting the area of rest concentration. All these blood samples were analyzed following the same protocol described in study 1.

In addition, blood gasometry analyses were performed in study 2. For capillary gasometry analyses, blood samples (60 μL) from the ear lobe were collected at rest and during two moments of the severe-intensity cycling in a design that controlled for duration (i.e., 50% and 100% of the highest tlim reached between the familiarization sessions). Immediately after collections, samples were analyzed in a RAPIDLab 348EX gasometer (Siemens Healthcare Diagnostics, Camberley, United Kingdom) to measure blood pH, bicarbonate(HCO3), base excess, potassium (K+), calcium (Ca2+), capillary oxygen pressure (pO2), and capillary carbon dioxide pressure (pCO2)

Statistical Analysis

Data are presented as mean ± SD and 95% confidence interval. Two-way repeated-measures ANOVA procedures were used to assess the effect of exercise (i.e., main time effect) and PBMT (interaction between main condition effect–main time effect) on EMG activity, respiratory and blood gasometry during exercise, and changes in the indicators of neuromuscular system function. One-way repeated-measures ANOVA assessed the effect of PBMT on time to exhaustion, metabolic indicators, and the percent change of neuromuscular system function. In all cases, the Mauchly test of sphericity was applied and the Greenhouse–Geisser epsilon correction was used when the sphericity criteria were not met (36). When necessary, the analyses were completed with SIDAK post hoc. The partial η2 (ηp2) was reported for interaction effects, and the threshold values were >0.001 (small), >0.06 (moderate), and >0.14 (large) (37). A significance level of 5% was assumed in all cases. All analyses were performed using the software package SPSS, version 20.0 (IBM Corp., Armonk, NY).


Study 1

The intensity of the constant-load, severe-intensity cycling was 262 ± 8 W (245–279 W), which represented 91.9% ± 2.2% (90.6%–93.2%) of maximal aerobic power (285 ± 32 W [266–304 W]). The tlim that was reached in the control condition was 634 ± 177 s (531–737 s). During PBMT treatment trials, one participant at 130-J condition and one at 260-J condition reached 72% and 96%, respectively, of the control tlim.

EMG activity during cycling exercise

The results of EMG activity measured during constant-load are shown in Figure 3. No condition effects were observed on RMS in all muscles during exercise (P ≥ 0.230), as well as on MdF of rectus femoris, biceps femoris, and gluteus maximus (P ≥ 0.097). However, a condition effect on MdF of vastus lateralis (P = 0.028) was observed, evidencing higher values at 130-J condition in comparison to placebo (P = 0.029). Time effect on RMS was observed in all muscles during exercise (P < 0.001), evidencing higher values in the 75%–100% time band compared with the other bands (post hoc, P < 0.001). However, no significant interactions were observed in RMS values for any muscle monitored (P ≥ 0.346, ηp2 0.086). Likewise, a time effect on MdF for all muscles (P < 0.001) was observed during exercise, evidencing smaller values in the 75%–100% time band compared with the other bands. However, no significant interactions were observed in MdF values for any muscle monitored (P ≥ 0.055, ηp2 0.147).

EMG activity measured during constant-load, severe-intensity cycling isotime to control, normalized by the highest values observed in placebo condition (not all participants attained the same peak value in the same time moment). Note: error bars not included for clarity. PBMT130, PBMT with 130 J-dose; PBMT260, PBMT with 260-J dose; PBMTPLA, PBMT with 0-J dose (placebo condition).

Neuromuscular assessments

No condition effects were observed for any neuromuscular system function indicator (P ≥ 0.100). After exercise, a decrease in global function was observed through reductions in Fpeak (time effect, P < 0.001) and RMSMVC (time effect, P = 0.008), but with no changes in MdFMVC (time effect, P = 0.410). However, no interaction effects were observed for any of these parameters (P ≥ 0.130, ηp2 0.145), as well as no differences in percent changes values (Fpeak, P = 0.167, ηp2 = 0.128; RMSMVC,P = 0.135, ηp2 = 0.182). Peripheral function was also reduced after exercise, as evidenced by the decrease in HFForce (time effect, P < 0.001) and the HFForce/LFForce ratio (time effect, P < 0.001), but with no changes in M-waveamp (time effect, P = 0.426) and M-wavedur (time effect, P = 0.309). No interaction effects were observed for peripheral function indicators (P ≥ 0.176, ηp2 0.127) as well as no differences in the values of percent change (P ≥ 0.171, ηp2 0.127). Concerning central function indicators, VA% decreased after exercise (time effect, P = 0.001), but no interaction effects (P = 0.189, ηp2 = 0.154) or differences in the values of percent change were found (P = 0.190, ηp2 = 0.153). All results of indicators of muscle fatigue are shown in Table 1.

TABLE 1 - Neuromuscular system function indicators before and after constant-load, severe-intensity cycling.
Before After Δ% Before After Δ% Before After Δ%
Global fatigue indicators
 Fpeak, N 638.69 ± 155.46
(548.92 to 728.44)
576.24 ± 157.31*
(485.41 to 667.07)
−10.05 ± 7.60
(−14.45 to −5.67)
648.49 ± 162.72
(554.54 to 742.45)
547.40 ± 143.74*
(464.40 to 630.39)
−14.97 ± 11.55
(−21.64 to −8.29)
681.79 ± 173.94
(581.40 to 782.27)
567.5 ± 163.26*
(473.20 to 661.74)
−16.50 ± 10.80
(−22.75 to −10.28)
 RMSMVC, μV 434.54 ± 183.16
(311.50 to 557.59)
348.84 ± 210.49*
(207.43 to 490.25)
−21.70 ± 33.50
(−44.15 to 0.79)
520.21 ± 127.19
(434.76 to 605.66)
436.737 ± 120.45*
(355.80 to 517.65)
−16.10 ± 11.80
(−24.03 to −8.22)
450.95 ± 180.28
(329.83 to 572.06)
429.63 ± 175.28*
(311.87 to 547.39)
−3.20 ± 16.60
(−14.36 to 7.94)
 MdFMVC, Hz 84.18 ± 13.94
(74.81 to 93.55)
78.31 ± 14.09
(68.84 to 87.77)
−5.11 ± 21.18
(−19.34 to 9.11)
76.55 ± 16.76
(65.29 to 87.81)
77.40 ± 14.80
(67.42 to 87.37)
4.88 ± 29.09
(−14.66 to 24.42)
74.37 ± 12.76
(65.79 to 82.95)
70.61 ± 15.05
(60.50 to 80.73)
−2.90 ± 26.58
(−20.76 to 14.96)
Peripheral fatigue indicators
 HFForce, N 230.70 ± 89.03
(179.29 to 282.11)
201.26 ± 77.98*
(156.23 to 246.28)
−12.29 ± 10.20
(−18.18 to −6.39)
248.90 ± 51.82
(218.98 to 278.82)
197.97 ± 60.17*
(163.22 to 232.71)
−20.80 ± 15.80
(−30.02 to −11.76)
276.11 ± 73.21
(233.83 to 318.38)
224.5 ± 63.95*
(187.59 to 261.45)
−17.90 ± 12.20
(−24.98 to −19.85)
 HFForce/LFForce, N 0.72 ± 0.11
(0.64 to 0.78)
0.51 ± 0.12*
(0.43 to 0.57)
−29.10 ± 13.70
(−37.01 to −21.25)
0.69 ± 0.15
(0.60 to 0.78)
0.47 ± 0.18*
(0.36 to 0.58)
−32.59 ± 17.40
(−42.67 to −22.57)
0.74 ± 0.16
(0.65 to 0.83)
0.53 ± 0.14*
(0.44 to 0.61)
−28.50 ± 1.80
(−36.50 to −20.51)
 M-waveamp, mV 14.42 ± 1.74
(12.97 to 15.88)
13.73 ± 1.61
(12.38 to 15.08)
−4.41 ± 6.09
(−9.50 to 0.68)
13.21 ± 3.05
(10.66 to 15.76)
12.75 ± 2.77
(10.42 to 15.07)
−2.68 ± 9.57
(−10.68 to 5.31)
13.52 ± 3.10
(10.92 to 16.12)
14.12 ± 3.71
(11.01 to 17.23)
4.27 ± 11.88
(−5.65 to 14.20)
 M-wavedur, ms 15.00 ± 5.63
(10.30 to 19.71)
14.88 ± 5.54
(10.24 to 19.51)
−0.52 ± 8.97
(−8.03 to 7.00)
15.63 ± 3.93
(12.34 to 18.91)
14.25 ± 3.41
(11.40 to 17.10)
−8.06 ± 10.47
(−16.82 to 0.70)
13.75 ± 3.45
(10.87 to 16.64)
13.88 ± 3.09
(11.29 to 16.46)
1.54 ± 10.19
(−6.99 to 10.06)
Central fatigue indicators
 VA, % 92.56 ± 5.29
(89.00 to 96.12)
92.19 ± 4.22*
(89.34 to 95.02)
−0.27 ± 4.10
(−3.05 to 2.50)
95.22 ± 4.08
(92.47 to 97.07)
92.11 ± 3.63*
(89.66 to 94.54)
−3.22 ± 3.10
(−5.30 to −1.12)
95.39 ± 4.46
(92.39 to 98.39)
92.46 ± 5.05*
(89.06 to 95.85)
−3.04 ± 3.76
(−5.57 to −0.52)
Values are expressed in mean ± SD (95% confidence interval).
*P < 0.05 comparing after and before moments considering the values of all conditions.
Fpeak, MVC peak force; HFForce, mechanical response evoked by femural motor nerve stimulation at 100 Hz; HFForce/LFForce, ratio of mechanical response evoked by femural motor nerve stimulation at 10 and 100 Hz; VA%, percentage of voluntary central neuromuscular function; RMSMVC, RMS of vastus lateralis muscle during MVC; MdFMVC, MdF of vastus lateralis muscle during MVC; M-waveamp, maximal amplitude of M-wave; M-wavedur, duration of M-wave; PBMT130, photobiomodulation therapy with 130-J dose; PBMT260, photobiomodulation therapy with 260-J dose; PBMPLA, PBMT with 0-J dose (placebo condition); Δ%, percent change between results after and before exercise.

The peaks of [La] after cycling for PBMT260, PBMT130, and PBMTPLA were, respectively, 8.2 ± 2.1 (6.9–9.5), 8.8 ± 2.2 (7.3–9.9), and 9.2 ± 2.4 (7.7–10.7) mmol·L−1, and no significant difference was observed (P = 0.106, ηp2 = 0.170).

Study 2

The intensity of the constant-load, severe-intensity cycling was 243 ± 8 W (225–261 W), which represents 91.5% ± 0.7% (89.9%–93.0%) of maximal aerobic power (266 ± 9 W [246–286 W]).

No significant differences were observed in tlim (P = 0.353, ηp2 = 0.083), area under the curve of V˙O2 (P = 0.089, ηp2 = 0.113), area under the curve of [La] during exercise (P = 0.082, ηp2 = 0.189), or peak of [La] after exercise (P = 0.376, ηp2 = 0.078; Table 2).

TABLE 2 - Performance and metabolic indicators from a constant-load, severe-intensity cycling until exhaustion.
Performance indicator
tLim (s) 537 ± 185 (424–649) 544 ± 172 (440–648) 519 ± 150 (428–610)
Metabolic indicators
 AUC of V˙O2, mL·kg−1 319.14 ± 134.45 (237.89–400.39) 319.28 ± 129.86 (240.80–397.76) 327.31 ± 137.55 (244.18–410.43)
 AUC of [La], mmol·L−1·% 454.94 ± 172.12 (350.89–558.98) 425.93 ± 161.42 (328.38–523.49) 417.04 ± 164.97 (317.34–516.74)
 [La]peak, mmol·L−1 10.53 ± 2.27 (9.15–11.90) 9.93 ± 2.02 (8.71–11.16) 10.25 ± 2.17 (8.94–11.57)
Values are expressed in mean ± SD (95% confidence interval).
AUC, area under the curve; [La], blood lactate concentration; [La]peak, peak of blood lactate concentration after effort; PBMT130, photobiomodulation therapy with 130-J dose; PBMT260, photobiomodulation therapy with 260-J dose; PBMTPLA, PBMT with 0-J dose (control condition); t Lim, time until exhaustion.

EMG activity during cycling exercise

No condition effects were observed on RMS of rectus femoris, biceps femoris, and gluteus maximus during exercise (P ≥ 0.237) as well as on MdF in all muscles during exercise (P ≥ 0.172). However, a condition effect was observed on RMS of vastus lateralis (P = 0.049), but with no difference in pairwise comparisons (P ≥ 0.061). Time effect on RMS was observed in all muscles during exercise (P < 0.001), evidencing higher values in the 75%–100% time band and at exhaustion compared with the other bands (post hoc, P < 0.001), with no difference between these moments. However, no significant interactions were observed in RMS values for any muscle monitored (P ≥ 0.168, ηp2 0.131). Similarly, to RMS, a time effect on MdF for all muscles (P < 0.001) was observed during exercise, evidencing smaller values in the 75%–100% time band and at exhaustion compared with the other bands (post hoc, P < 0.001), with no difference between these moments. However, no significant interactions were observed in MdF values for any muscle monitored (P ≥ 0.130, ηp2 0.138).

Capillary blood gasometry

All conditions presented a decrease (i.e., time effect, P ≤ 0.001) in pH, HCO3, base excess, and PCO2 outcomes and an increase in K+, comparing the final measure (i.e., 100%) with the rest values (post hoc, P ≤ 0.010). There were no interaction effects for any of these variables (P ≥ 0.250, ηp2 0.158; Table, Supplemental Digital Content 3, which presents the capillary blood gasometry and respiratory gas-exchange values,

Respiratory gas-exchange outcome

V˙O2, E, E/V˙O2, and RER presented an increase at 100% moment compared with the rest values (i.e., time effect, P < 0.001), with no interaction effect for any variable (P ≥ 0.194, ηp2 0.126). E/V˙CO2 presented a decrease at the 50% moment compared with rest levels and an increase comparing the 50% to 100% moment (i.e., time effect, P < 0.001; post hoc, P < 0.001), also with no interaction effect (P = 0.282, ηp2 = 0.100; Table, Supplemental Digital Content 3, which present the capillary blood gasometry and respiratory gas-exchange values,


The present studies showed that PBMT did not produce ergogenic effects in a constant-load, severe-intensity cycling of ~11 min in duration. Specifically, PBMT (both dosages) did not change EMG activity, metabolic and respiratory responses, and capillary gasometry outcomes, as well as indicators of muscle fatigue (i.e., global, central, and peripheral) and performance (i.e., tlim) compared with the placebo condition. Based on the PBMT mechanisms (4), it was hypothesized that PBMT would increase the oxidative contribution to exercise and attenuate some of the exercise-induced changes related to muscle activity and fatigue emergence. Theoretically, these results would have translated to diminished increases in lactate and K+ blood concentrations, decreases in blood pH, HCO3, and base excess levels, and increases in E and E/V˙CO2 that occur with severe-intensity exercise. Thus, it was further hypothesized that these collective effects would decrease the level of muscle fatigue after duration-matched high-intensity exercise in study 1 and increase the time to exhaustion in study 2.

The indicators of neuromuscular system activity (Table 1) demonstrated that constant-load, severe-intensity cycling promoted global (decreased Fpeak and RMSMVC), central (decreased VA%), and peripheral (decrease in HFForce and HFForce/LFForce ratio) muscle fatigue (main time effect) (19). However, no significant interactions were observed in these parameters. Previous studies evidenced that PBMT attenuated strength loss (i.e., global fatigue) after different modes of single-joint fatigue protocols (11,12). The current findings (Table 1) contradict the positive effects reported by other studies after single-joint exercises (11,12) and show that such results may not be transferable to multijoint exercises such as cycling. One possible explanation for this issue may be the distinct physiological demands among such exercises (38). For example, the total work performed by participants in a previous study during a knee-extensor fatiguing protocol was ~4.2 kJ (12). On the other hand, the participants in study 1 of the current investigation performed ~208 kJ of total work during the constant-load, severe-intensity cycling exercise, with a mean cadence of ~75 rpm, power output of ~262 W, and duration of ~635 s. Therefore, the PBMT dosages used to attenuate fatigue induced by single-joint exercises do not seem to be sufficient to also attenuate the level of fatigue induced by cycling. The procedures to prepare the postexercise neuromuscular assessments involved transferring the participants from the cycle ergometer to the chair, as well as allowing sufficient time for stabilization of the EMG signals and reduction of noise from body position changes. The time period to accommodate these aspects was on average ~ 1.5 min. Although this delay may influence the recovery of neuromuscular function between participants, it was kept consistent between trials within each participant. This was done in order to avoid variations in the delay across conditions, which could lead to problems interpreting the results. Likewise, this time period was in accordance with similar investigations (26,39,40).

There is little evidence in the literature on how PBMT can affect the distinct physiological systems that underpin an associated increase in physical performance (5,6,41). Invasive measures related to specific PBMT cell mechanisms in humans are difficult to conduct due to several issues such as voluntary adhesion, demand for specialized technical staff, and high financial support (42). Therefore, the wide monitoring of physiological responses during exercise performed in the present study helps to provide more insight into the PBMT ergogenic effects. Most of the previous studies only investigated the influences of PBMT on respiratory responses and EMG activity during exercise (6,16). In line with our findings (Table 1), there was no influence of PBMT on indicators of aerobic system activity during moderate cycling (41) and incremental running (7), or on the indicators of aerobic and anaerobic thresholds during an incremental running exercise (5).

Hip extensor musculature has been shown to provide the major contribution to power output maintenance in cycling at intensities greater than 80% of the maximal aerobic power (31). However, the previously reported PBMT effect on knee extensors was indicated as a determinant for improvement in cycling performance at maximal aerobic power (6). For instance, Lanferdini and coauthors have demonstrated that PBMT with a dose of 135 J improved the EMG activity of knee extensor musculature (vastus lateralis, vastus medialis, and rectus femoris) during constant-load cycling at maximal aerobic power intensity for ~3 min (6). Nevertheless, the current investigation observed higher values of EMG MdF of vastus lateralis using PBMT at 130 J in comparison to placebo in study 1 (condition effect). However, no significant effects of PBMT on EMG activity or performance in the constant-load bouts of cycling in study 2 were found. These findings may be partially explained by the possible differences between the fatigue etiology of the exercise trials. For example, higher central impairments seem to occur in constant-load submaximal cycling compared with cycling at an intensity equal to maximal aerobic power (26). In addition, the participants of study 2 in the current investigation were less aerobically fit (maximal aerobic power of ~266 W) than the participants of the aforementioned study (maximal aerobic power of ~410 W) (6). There are specific muscular adaptations that are found in elite endurance-trained cyclists that may contribute to the effects of PBMT, such as a greater predominance of oxidative fibers in lower limb musculature, with increased capillary density (43).

In addition, PBMT did not promote changes in peak [La] after exercise. Because it was previously suggested that PBMT improves the oxidative pathway during exercise, lower values of peak [La] were expected after the exercise trials that were duration matched (study 1) in comparison with placebo treatment (4). However, as previously discussed with other findings, the effect on peak [La] has been observed after single-joint (16) but not multijoint (14,44) exercise.

The present study followed specific recommendations for the utility of PBMT. For example, parameters of power output (50 and 80 mW for cluster probes, 50 mW for small probes), mode (continuous output), spectral wavelength (630 and 850 ηm), and dosages (260 and 130 J large muscles) were based on previous research (4,34). Furthermore, the exposure duration of a minimum of 30 s per site, treatment location of covering as much of the area of active muscle as possible, and technique of stationary and with slight pressure were also carried out according to what has been suggested regarding application mode (33). Therefore, the lack of positive findings on muscle fatigue and performance in the present study is intriguing and leads to doubt about the effectiveness of PBMT.

A few biological variations may have contributed to the lack of expected effects of PBMT. For example, differences in skin color and subcutaneous fat composition may have affected light penetration to the muscle tissues (45). However, the current study used an irradiation of ~16 (50 mW per 3.14 cm2) to ~25 (80 mW per 3.14 cm2) mW·cm–2, which agrees with studied irradiation ranges that effectively penetrate light up to 50 mm below the skin surface (46). Unfortunately, though, the sparse research addressing the effects of PBMT on human muscle tissue is inconclusive (10,47). Thus, it is difficult to be certain if the recommended procedures (33,46) that were carried out in the study were sufficient for delivering an adequate amount of treatment to the active musculature. According to the PBMT dose–response characteristic, absorption of high levels of energy by the target tissue will suppress cell activity, whereas low doses will entail no effect (18). However, the novel results of the current study expand previous investigations, collectively providing a solid foundation for the continued research that will lead to the standards for PBMT usage. Incidentally, it is recommended that subsequent investigations use study protocols that utilize multijoint exercises that are more specific to sports performance than single-joint movements. This will provide the clearest understanding of whether PBMT may be an effective ergogenic aid.

In conclusion, the current findings demonstrated that both dosages of PBMT were ineffective toward improving EMG activity, metabolic and respiratory responses, gasometry outcomes, indicators of muscle fatigue, and exercise performance (i.e., time until exhaustion) in male recreational cyclists. Thus, the study did not support the utility of PBMT as an ergogenic aid for male recreational cyclists at severe-intensity cycling of a duration of ~11 min. However, additional studies with designs that vary usage parameters, consider biological individualities, and utilize sport-specific exercises will lead to a clear understanding of whether PBMT can be beneficial for muscle fatigue and increasing performance. Until a sufficient amount of research delivers a consensus regarding the effectiveness of PBMT and standards for its practice, the technique should be used with caution if an ergogenic effect is desired.

Y. M. D., G. M. C., E. S. M., and G. M. P. B. were supported by São Paulo Research Foundation fellowship (Nos. 2017/11255-0, 2017/14187-6, 2017/21724-8, and 2017/03660-2, respectively). This study was also financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brasil, Finance Code 001.

The authors declare no conflict of interest. The results of the current study do not constitute endorsement by the American College of Sports Medicine. All results of the present study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.


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