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European Journal of Sport Science logoLink to European Journal of Sport Science
. 2024 Feb 9;24(3):279–288. doi: 10.1002/ejsc.12076

Effect of hypoxic sprint interval exercise and normoxic recovery on performance and acute physiological responses

Naoya Takei 1,✉, Gaku Kakehata 1, Takeru Inaba 1, Yuki Morita 1, Hinata Sano 2, Olivier Girard 3, Hideo Hatta 1
PMCID: PMC11235708

Abstract

Hypoxic exercise, which can induce arterial and tissue deoxygenation, promotes physiological adaptations. However, reduced oxygen availability can lower the absolute training intensity (i.e., mechanical stress). Adding normoxic recovery to sprint interval exercise (SIE) is one potential approach to strike a balance between providing a hypoxic stimulus and maintaining the absolute training intensity. However, the effects of adding normoxic recovery to SIE on performance and physiological responses are uncertain. We tested the hypothesis that hypoxic SIE with normoxic recovery enhances arterial deoxygenation and muscle deoxygenation levels without impeding performance compared to an entirely normoxic condition. On separate days, seven male sprinters performed 4 × 30‐s ‘all‐out’ cycle sprints with 4.5‐min recovery with hypoxic exposure (FiO2: 12.7%O2) applied continuously (hypoxia, HYP), intermittently during sprint periods only (intermittent, INT), or not at all (normoxia, NOR). Power output, oxygen saturation, muscle oxygenation, surface electromyography (EMG) activity, heart rate, blood lactate concentration, and ratings of perceived exertion were measured. The total work significantly decreased in HYP than NOR (p < 0.05) and INT (p < 0.01). The aTrterial oxygen saturation was lower during HYP than NOR (∼86% vs. ∼97%; p < 0.001), while lower values were also obtained for INT than NOR during sprint periods (∼85% vs. ∼97%; p < 0.001) but not during recovery periods (∼96% vs. ∼97%). The heart rate differed (p < 0.05) between conditions (NOR: ∼164 bpm; INT: ∼160 bpm; HYP: ∼156 bpm). No other variables demonstrated significant differences between conditions. Adding hypoxia during exercise while recovering in normoxia did not compromise exercise capacity during SIE, despite inducing larger arterial deoxygenation levels compared to normoxia.

Keywords: altitude training, environmental stress, hypoxia, intermittent hypoxic training, wingate

Highlights

  • Utilizing severe hypoxia during exercise and normoxia during recovery induces a substantial hypoxic stimulus while safeguarding mechanical performance in sprinters.

  • This approach maintains neuromuscular, metabolic, and perceptual parameters without any detrimental effects, ensuring athletes can perform at their best.

  • Alternating hypoxia and normoxia during active and passive phases shows potential for optimizing hypoxic training, striking an ideal balance between the hypoxic stimulus and training intensity and load.

1. INTRODUCTION

Exercising under systemic hypoxia induces arterial and tissue deoxygenation, promoting physiological adaptations through oxygen‐sensing signaling pathways in reference to equivalent normoxic exercise (Hoppeler et al., 2001). Compared to normoxia, training in hypoxia can upregulate mitochondrial biogenesis (Schmutz et al., 2010; Vogt et al., 2001), oxidative and glycolytic enzymes (Puype et al., 2013; Vogt et al., 2001), monocarboxylate transporters (Faiss et al., 2013), and angiogenesis (Vogt et al., 2001; Wahl et al., 2013). The downside is that reduced oxygen availability may compromise the mechanical training stimulus, potentially affecting training intensity and/or volume (Michael Niess et al., 2003; Wadley et al., 2006). Consequently, when prescribing hypoxic training, it becomes crucial to increase the physiological stimulus while maintaining training intensity and/or volume to maximize performance benefits.

Sprint interval exercise (SIE), consisting of several ∼30‐s ‘all‐out’ sprints followed by short recovery intervals lasting few minutes, is effective in enhancing physiological responses and performance in normoxia (Gibala et al., 2012). When SIE is performed under moderate hypoxia (14.5% O2), it can increase phosphofructokinase activity without necessarily improving exercise performance (Puype et al., 2013). One potential explanation could be the significant yet modest arterial deoxygenation observed (Takei et al., 2021). Supporting this notion, a previous study using more severe hypoxia (13% O2) reported superior training benefits, including a significant increase in peak power output compared to equivalent training in moderate hypoxia (14.5% O2) (Warnier et al., 2020).

It is essential to consider that SIE under severe hypoxia (<13%O2) might negatively impact exercise performance and compromise training intensity and/or load. Furthermore, individual responses to hypoxia can vary significantly (Chapman, 2013), and individuals with lower tolerance to hypoxia or fatigue resistance (e.g., sprinters) may encounter challenges when exercising in severe hypoxia. Therefore, when prescribing training in such conditions, it becomes important to implement methods that maintain absolute exercise intensity and training load to ensure effectiveness of the training. Striking the right balance between delivering a sufficient hypoxic stimulus and sustaining exercise intensity and/or training load should be a priority to optimize the benefits of hypoxic training protocols.

One potential strategy to augment arterial and tissue deoxygenation induced by severe hypoxia while maintaining exercise performance (mechanical training stimulus) involves adding normoxic recovery periods during hypoxic interval exercise. To our knowledge, only one study has explored this approach in aerobic interval exercise, applying severe hypoxia intermittently during 6 × 5‐min submaximal exercise (Sanchez and Borrani, 2018). Although this previous study focused on submaximal interval exercise, recent research highlights the importance of higher intensity or ‘all‐out’ efforts to boost the effects of hypoxic training (McLean et al., 2014). Recently, repeated sprint training in hypoxia (RSH), involving brief (<30 s) maximal efforts with short incomplete recoveries (<60 s), has gained recognition as an effective intervention to improve sea‐level performance (Brocherie et al., 2017; Faiss et al., 2013; McLean et al., 2014). Some RSH studies have incorporated normoxic inter‐set recovery, but none have examined the effects of normoxic inner‐set recovery (i.e., between sprints recovery), possibly due to the short duration of the inner‐set recovery (<60 s), making it challenging to alter inhaled air conditions (Brocherie et al., 2023; Girard et al., 2015; Soo et al., 2020). Similar to RSH, SIE also encompasses ‘all‐out’ efforts with a sufficiently long recovery interval (∼5‐min) that facilitates the switch in inhaled air conditions. However, to date, no investigation has explored the effects of intermittent hypoxic exposure during SIE.

Evaluating surface electromyographic (EMG) activity of lower limb muscles has been a common method to shed light on neuromuscular factors contributing to fatigue‐induced decrease in pedaling performance (Dorel et al., 2008; Girard et al., 2015; Soo et al., 2020). For instance, EMG amplitudes were notably decreased under conditions of severe fatigue (FiO2: 0.12) during exhaustive cycling (Osawa et al., 2011; Racinais et al., 2007). Thus, considering not only physiological responses but also the neuromuscular factors (i.e., muscle activation) is crucial when assessing performance during SIE (Racinais et al., 2007).

Therefore, this study examined the effects of adding normoxic recovery periods during severe hypoxic SIE on performance, physiological, neuromuscular, and perceptual responses in sprinters. It was hypothesized that severe hypoxia would impede SIE performance, while adding normoxic recovery (i.e., intermittent hypoxia) would preserve performance and physiological responses (arterial and tissue oxygenation) compared to entirely normoxic SIE.

2. MATERIALS & METHODS

2.1. Participants

The sample size was determined using power analysis software (G*Power 3.1.9.7, Heinrich‐Heine‐Universität Düsseldorf) based on the mean effect (d = 1.48) of the between‐condition response in performance variables during repeated sprint exercise, comparing normoxia (20.9% O2) and hypoxia (12.7% O2) (Goods et al., 2014). The power analysis calculated a total sample size of six participants. For this study, we recruited nine male athletic sprinters after obtaining written informed consent, considering a potential 25% dropout rate. Finally, seven participants completed the study and were included in the data analysis (Age: 21.9 ± 1.3 y; Body weight: 65.7 ± 5.3 kg; 100m‐personal best: 11.36 ± 0.32 s ranging from 10.85 to 11.85 s). They belonged to the same athletics club and followed a uniform training regimen, categorized as ‘Trained/Developmental’ (Tier 2) using established criteria (McKay et al., 2022). All participants were born and lived near sea‐level and had not been exposed to hypoxic environments in the 6 months prior to the study. The study was conducted according to the Declaration of Helsinki and was approved by the Research Ethics Committee at the University of Tokyo (No. 891).

2.2. Experimental design

This study employed a single‐blinded, randomized‐order, cross‐over design. Prior to the cross‐over trial, participants underwent familiarization by completing half of the experimental procedure (2 × 30‐s ‘all‐out’ sprints with 4.5‐min recovery) in normoxia. Subsequently, on separate visits participants performed the SIE protocol (4 × 30‐s ‘all‐out’ sprints with 4.5‐min recovery) under three distinct conditions: normoxic sprint/normoxic recovery (NOR, normoxia throughout the session), hypoxic sprint/hypoxic recovery (HYP; hypoxia [12.7%O2] throughout the session), and hypoxic sprint/normoxic recovery (INT; hypoxia [12.7%O2] during the exercise periods only). Testing occurred at a constant temperature of ∼22°C and 50% relative humidity. Two hours before each visit, participants consumed a light meal and were instructed to replicate it as closely as possible for each visit. Participants were also directed to avoid consuming ergogenic‐aid supplements (e.g., caffeine and creatine) and engaging in heavy exercise 48 h prior to the tests. All tests were separated by 7 days and conducted at the same time of day to eliminate the circadian effects.

2.3. Experimental sessions

Upon arrival, participants were seated for 10 min while being instrumented. They then completed a standardized warm‐up comprising 10‐min of low‐intensity cycling (100 W, 90 rpm), followed by three 10‐s sprints with increasing voluntary efforts (60%, 80%, and 100% of maximal voluntary effort), using a workload set at 7.5% of each participant's body weight. Following the warm‐up, participants recovered passively for 10 min while the facemask was attached. Throughout the trial, participants inhaled the gas mixture dispensed by the portable hypoxic generator, which corresponded to their experimental condition.

The SIE comprised four 30‐s ‘all‐out’ cycle sprints interspersed with 4.5‐min passive recovery periods, with a workload set at 7.5% of each participant's body weight. Testing employed an electrically braked cycle ergometer (PowerMax VIII, Konami, Japan), enabling measurement of peak power output (PPO), mean power output (MPO), and total work for the four sprint bouts. Seat and handle positions were individually adjusted and replicated for every session. All recovery phases were conducted while seated on the cycle ergometer. Strong verbal encouragement was given throughout all sprints.

2.4. Altitude simulation

Participants inhaled either hypoxic or normoxic air through a facemask secured with a Velcro headset, connected to plastic tubes. To switch between the two air conditions, three‐way valves were used in conjunction with either a hypoxic generator (Everest Summit II, Hypoxico, USA) producing hypoxic air (12.7% O2 or a simulated altitude of ∼4000 m; ∼116 L/min) or an air compressor (SRL‐0.75DSN, Hitachi, Japan) supplying normoxic air (20.9% O2; 80–100 L/min) into the tubes. For HYP and NOR, participants began inhaling the respective air 5 min before the start of the first 30‐s sprint, continuing until 5 min after completing the last sprint. For INT, participants also began inhaling normoxic air through the facemask 5 min before the first 30‐s sprint and continued until 5 min after the last sprint. However, the inhaled air was switched to hypoxic air ∼45 s before each sprint and then immediately reverted to normoxic air after each sprint. All tests were conducted at an elevation of ∼37 m above sea level.

2.5. Oxygen saturation

Oxygen saturation (SpO2) was continuously monitored at a 4‐s weighted average using pulse oximetry (N‐BSJ, Nellcor, USA) and a forehead adhesive sensor (MAXFAST, Nellcor, USA). This forehead sensor exhibits high responsiveness and can detect changes in SpO2 in 10.1 ± 5.4 s when the fraction of inspired oxygen is altered, whereas a finger pulse oximeter requires 77.5 ± 28.4 s (De et al., 2017). To measure SpO2, the sensor was attached to the forehead, specifically covering the supraorbital artery, and then gently secured with a headband designed to apply the correct pressure. SpO2 values were calculated as follows: Baseline (average of 105 to 45 s before the sprint), Pre (4‐s average before the sprint), Post (lowest 4‐s average after the sprint), and Recovery (average of 60–120 s after the sprint).

2.6. Muscle oxygenation

Muscle oxygenation trends of the left vastus lateralis muscle were measured at 10 Hz using a near‐infrared spectroscopy (NIRS) device (Portamon, Artinis, Netherlands) with wavelengths of 760 and 850 nm (Boushel et al., 2000). The NIRS device was positioned on the lower third of the vastus lateralis muscle and secured with Transpore surgical tape. To ensure minimal movement and block ambient light, it was further wrapped with black kinesiology tape and a black elastic bandage. The device's placement was marked with a marker pen and replicated in every session. The sampled signals were filtered using a 10th‐order low‐pass Butterworth filter with a cutoff frequency of 0.1 Hz to reduce artifacts and perturbations induced by cycling. Tissue saturation index (ΔTSI), oxyhemoglobin (ΔO2Hb), and deoxyhemoglobin (ΔHHb) values were calculated as the difference between the baseline (30‐s average before each sprint) and the lowest 5‐s average during each sprint effort. To establish the 30‐s baseline, participants were instructed to keep their legs stationary for 30 s before each sprint initiation.

2.7. Surface electromyography

Surface electromyography (EMG) data were sampled at 2000 Hz using wireless EMG sensors (Trigno Wireless Sensor, Delsys, USA) on seven lower limb muscles in the right leg: rectus femoris (RF), biceps femoris (BF), gluteus maximus (G max), vastus lateralis (VL), tibialis anterior (TA), lateral head of gastrocnemius (GAS), and soleus (SOL). Before attaching the sensors, the skin was prepared by shaving, abrasion, and cleaning with alcohol to reduce interelectrode impedance. To minimize motion artifacts, the sensors were attached with double‐sided tape and Transpore surgical tape, then wrapped with Underwrap tape. The sensor positions were marked with a marker pen and reproduced for every visit. Surface EMG signals were filtered (bandwidth frequency: 20–450 Hz) using dedicated software (LabChart 8, ADInstruments, Australia), after which muscle activation levels were calculated as root mean squares (RMSs) values. The RMS values were averaged over a 30‐s period for each sprint bout.

2.8. Heart rate, blood lactate concentration and RPE

Heart rate was monitored at a frequency of 1 Hz using a chest belt sensor (Polar H10, Polar, Finland). Pre‐exercise heart rate was calculated as the 5‐s average before each sprint (Pre), whereas post‐exercise heart rate was determined as the highest 5‐s average following each sprint (Post). For blood lactate concentration analysis, a capillary blood sample was taken from the fingertip and assessed using an automated analyzer (Lactate Pro 2 portable analyzer, Arkray, Japan). Measurements were taken immediately before the first 30‐s sprint and 3 min after each of the four sprint bouts. Participants rated their rate of perceived exertion (RPE; 6–20 Borg scale) 1 min after completing each of the four efforts.

2.9. Statistical analysis

To assess normality, the Shapiro–Wilk test was performed. One‐ and two‐way repeated measures ANOVA [time (before, bout 1, bout 2, bout 3, and bout 4) × condition (NOR, HYP, and INT)] were used to compare dependent variables, followed by Bonferroni post‐hoc analysis adjusted for multiple comparisons. To assess the assumptions of variance, Mauchly's test of sphericity was employed for all ANOVA results. If assumptions were violated, a Greenhouse–Geisser correction was applied to adjust degrees of freedom. Additionally, if a significant main effect was detected, effect sizes were calculated to determine the magnitude of differences for pairwise comparisons using Cohen's d values (0.20–0.49 = small effect, 0.50–0.79 = moderate effect; and ≥0.80 = large effect). All values are presented as mean ± standard deviation. Statistical analysis was carried out in Prism (v9.5.1; GraphPad Software, USA). The statistical significance level was set at p < 0.05.

3. RESULTS

MPO (Δbout 1–4: −32.8 ± 10.1%) and PPO (Δbout 1–4: −31.0 ± 12.9%) significantly decreased across repetitions (MPO: p < 0.001, d = 4.53, PPO: p < 0.001, d = 3.76), yet with significant difference between conditions (p < 0.05) observed only for MPO (Figure 1). Total work was significantly reduced only in HYP (0.93 ± 0.04 kJ/kg, d = 0.67) compared to NOR (0.97 ± 0.04 kJ/kg, p < 0.001) and INT (0.96 ± 0.04 kJ/kg p < 0.05).

FIGURE 1.

FIGURE 1

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Mean (MPO, A) and peak (PPO, B) power output for sprint interval exercise. All values are expressed as mean ± SD. Each bar graph and plots represent the average value for the normoxic (NOR, white bar and black circle), intermittent (INT, blue bar and white triangle), and hypoxic (HYP, orange bar and white square) conditions. R, C, and I, respectively refer to ANOVA main effects of repetition, condition, and interaction between these two factors. a p < 0.05 different from bout 1, b p < 0.05 different from bout 2, c p < 0.05 different from bout 3.

Changes in SpO2 over the entire SIE protocol for the three conditions are shown in Figure 2. SpO2 was significantly lower in HYP (86.5 ± 4.0%) versus NOR (97.1 ± 1.6%; p < 0.001, d = 3.49) (Figure 2). In INT, SpO2 was significantly lower (p < 0.001, d = 5.02) during the exercise period (i.e., pooled value for four bouts, Pre: 92.9 ± 2.4%; Post: 85.4 ± 2.6%) compared to NOR (Pre: 97.6 ± 1.5%; Post: 96.6 ± 1.8%), and significantly higher (p < 0.001, d = 4.21) during the recovery period (Baseline: 97.1 ± 0.9%; Recovery: 95.9 ± 1.1%) compared to HYP (Baseline: 88.3 ± 2.8%; Recovery: 84.1 ± 2.8%) (Figure 2).

FIGURE 2.

FIGURE 2

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Changes in arterial oxygen saturation during exercise and recovery periods of sprint interval exercise. All values are expressed as mean ± SD. Each line graph represents the average value of arterial oxygen saturation for the normoxic (NOR, black line and white circle), intermittent (INT, blue line and blue triangle), and hypoxic (HYP, orange line and orange square) conditions. Gray vertical boxes indicate the timing of the 30‐s sprint. R, C, and I, respectively refer to ANOVA main effects of repetition, condition, and interaction between these two factors. a p < 0.05 different from hypoxia, b p < 0.05 different from normoxia.

ΔO2Hb significantly decreased across repetitions (Δbout 1–4: −31.1 ± 10.4%) (p < 0.001, d = 1.75), while ΔTSI, ΔO2Hb and ΔHHb did not differ between conditions (Table 1).

TABLE 1.

Physiological and perceptual variables.

Variables Pre 1 (post warm‐up) Post 1 Pre 2 Post 2 Pre 3 Post 3 Pre 4 Post 4 p value
R C I
HR, bpm
NOR 120 ± 12 186 ± 6# 145 ± 14a 185 ± 7# 157 ± 13b 184 ± 8# 157 ± 13c 185 ± 8# <0.001 0.04 0.45
INT 122 ± 17 182 ± 6# 139 ± 12a 179 ± 7# 153 ± 13b 179 ± 8# 152 ± 11c 179 ± 8#
HYP 122 ± 12 176 ± 11# 136 ± 18a 176 ± 5# 146 ± 18b 173 ± 10# 148 ± 16c 176 ± 7#
BLa, mmol/l
NOR 5.3 ± 1.4 14.4 ± 1.7# — 19.0 ± 3.3a — 19.6 ± 3.0a,b — 19.3 ± 3.2a,b <0.001 0.76 0.44
INT 5.6 ± 1.4 15.6 ± 1.8# — 19.0 ± 1.8a — 19.6 ± 2.3a,b — 19.2 ± 2.1a,b
HYP 5.6 ± 1.8 14.8 ± 3.0# — 18.4 ± 2.1a — 20.1 ± 2.5a,b — 20.2 ± 2.5a,b
RPE, A.U.
NOR — 14.6 ± 1.9 — 17.4 ± 1.9a — 19.3 ± 1.0a,b — 19.6 ± 0.7a,b <0.001 0.34 0.33
INT — 15.7 ± 1.4 — 17.9 ± 0.8a — 19.7 ± 0.5a,b — 19.9 ± 0.3a,b
HYP — 15.7 ± 2.0 — 17.9 ± 2.2a — 19.3 ± 1.7a,b — 19.7 ± 0.7a,b
O2Hb, μM
NOR — −20.5 ± 4.5 — −25.7 ± 6.6a — −31.3 ± 7.7a,b — −31.4 ± 7.8a,b <0.001 0.90 0.32
INT — −19.3 ± 3.4 — −26.0 ± 6.1a — −27.6 ± 5.6a,b — −30.6 ± 5.2a,b
HYP — −22.4 ± 6.4 — −25.5 ± 7.2a — 29.7 ± 6.4a,b — −29.6 ± 6.8a,b
HHb, μM
NOR — 19.9 ± 5.7 — 18.9 ± 5.1 — 19.3 ± 4.3 — 20.5 ± 5.3 0.26 0.32 0.80
INT — 17.9 ± 2.2 — 17.6 ± 2.8 — 18.0 ± 2.7 — 17.9 ± 2.3
HYP — 16.0 ± 4.7 — 15.1 ± 3.3 — 16.1 ± 4.4 — 16.6 ± 3.5
TSI, %
NOR — −17.9 ± 11.4 — −20.2 ± 13.4 — −22.5 ± 11.3a — −21.9 ± 15.3a,b 0.08 0.86 0.59
INT — −16.2 ± 9.2 — −16.7 ± 10.4 — −17.6 ± 11.2a — −20.3 ± 9.5a,b
HYP — −16.7 ± 11.6 — −16.3 ± 11.7 — −18.8 ± 11.3a — −18.4 ± 11.5a,b
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Note: The repeated‐sprint exercise protocol consisted of four 30‐s cycle sprints with 4.5‐min of inter‐sprint recovery. The exercise was performed with hypoxic exposure (inspired oxygen fraction: 12.7%O2) applied continuously (hypoxia or HYP), intermittently during inter‐sprint periods (intermittent or INT) only, or not at all (normoxia or NOR). All values are expressed as mean ± SD. R, C, and I, respectively refer to ANOVA main effects of repetition, condition, and interaction between these two factors.

Abbreviations: BLa, blood lactate concentration; HHb, deoxyhemoglobin; HR, heart rate; O2Hb, oxyhemoglobin; RPE, Rating of perceived exertion; TSI, Tissue saturation index.

# p < 0.05 compared to Pre in same bout. a p < 0.05 compared to Post 1, b p < 0.05 compared to Post 2, c p < 0.05 compared to Post 3.

Surface EMG activities of TA (Δbout 1–4: −19.5 ± 21.8%, d = 0.98), GAS (Δbout 1–4: −32.1 ± 21.3%, d = 0.98) and BF (Δbout 1–4: −41.4 ± 31.2%, d = 1.17) significantly decreased across repetitions (all p < 0.05), irrespectively of condition. However, surface EMG activities of SOL, RF, VL and Gmax did not differ across repetitions or between conditions (Table 2).

TABLE 2.

Surface EMG root mean square activities.

Variables (%Bout 1) Bout 2 Bout 3 Bout 4 p value
R C I
Tibialis anterior, %
NOR 83.0 ± 10.2a 85.0 ± 22.6a,b 91.2 ± 31.9a,b 0.02 0.35 0.25
INT 85.4 ± 12.7a 75.9 ± 7.7a,b 70.8 ± 10.2a,b
HYP 88.0 ± 7.6a 79.9 ± 11.9a,b 79.4 ± 15.3a,b
Soleus, %
NOR 105.7 ± 13.8 111.4 ± 17.5 121.7 ± 23.2 0.12 0.52 0.62
INT 104.3 ± 10.4 122.9 ± 24.4 133.0 ± 56.5
HYP 104.7 ± 4.6 116.5 ± 16.3 115.4 ± 15.3
Gastrocnemius, %
NOR 83.7 ± 10.9a 69.2 ± 15.3a,b 66.3 ± 13.3a,b 0.02 0.24 0.28
INT 76.2 ± 21.9a 59.8 ± 29.6a,b 61.9 ± 31.6a,b
HYP 88.2 ± 13.0a 76.4 ± 16.6a,b 75.4 ± 17.1a,b
Rectus femoris, %
NOR 94.3 ± 8.2 85.3 ± 22.4 86.3 ± 17.4 0.38 0.29 0.52
INT 105.1 ± 15.0 98.4 ± 28.9 97.6 ± 21.3
HYP 96.3 ± 16.8 82.9 ± 29.4 96.8 ± 6.9
Vastus lateralis, %
NOR 96.1 ± 6.5 95.4 ± 10.6 96.3 ± 4.5 0.32 0.97 0.51
INT 103.7 ± 24.9 91.2 ± 15.0 92.6 ± 18.2
HYP 97.4 ± 10.0 94.8 ± 9.3 96.6 ± 12.4
Biceps femoris, %
NOR 77.7 ± 9.0a 63.7 ± 29.0a,b 60.9 ± 23.5a,b 0.02 0.59 0.70
INT 79.5 ± 17.7a 55.0 ± 34.6a,b 54.1 ± 36.4a,b
HYP 86.4 ± 19.7a 64.4 ± 34.5a,b 60.5 ± 37.3a,b
Gluteus maximus, %
NOR 96.6 ± 17.5 89.5 ± 16.6 85.6 ± 14.5 0.07 0.91 0.48
INT 93.6 ± 8.1 88.4 ± 13.1 83.9 ± 18.0
HYP 95.0 ± 8.6 84.5 ± 11.4 92.3 ± 14.4
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Note: The repeated‐sprint exercise protocol consisted of four 30‐s cycle sprints with 4.5‐min of inter‐sprint recovery. The exercise was performed with hypoxic exposure (inspired oxygen fraction: 12.7%O2) applied continuously (hypoxia or HYP), intermittently during inter‐sprint periods (intermittent or INT) only, or not at all (normoxia or NOR). All values are expressed as mean ± SD. R, C, and I, respectively refer to ANOVA main effects of repetition, condition, and interaction between these two factors.

a p < 0.05 compared to bout1 (baseline), b p < 0.05 compared to bout 2.

Heart rate significantly increased after each sprint bout (Post: 180 ± 8 bpm) and decreased after each recovery interval (Pre: 141 ± 18 bpm) (p < 0.001, d = 2.70), with a significant difference (p < 0.05) between conditions (NOR: 165 ± 25 bpm; INT: 161 ± 23 bpm; HYP: 157 ± 24 bpm) (Table 1). Both blood lactate concentration (Δbout 1–4: +33.4 ± 25.1%, d = 6.28) and RPE (Δbout 1–4: +30.3 ± 15.7%, d = 3.07) increased across sprint repetitions (p < 0.001), irrespectively of condition (Table 1).

4. DISCUSSION

4.1. Exercise performance

We observed that severe hypoxia compromised MPO in HYP compared to NOR and INT. Additionally, total work exhibited a decline only in HYP compared to NOR and INT. It can therefore be concluded that, in comparison to INT, HYP resulted in a decrease in training intensity (−2.3%) and load (−2.8%). These findings therefore substantiate our hypothesis that severe hypoxia compromises exercise SIE performance by decreasing MPO and total work, while the INT approach demonstrated the potential to restore exercise performance compared to normoxia.

Our study also revealed significant differences across repetitions for both MPO (Δbout 1–4: −32.8 ± 10.1%) and PPO (Δbout 1–4: −31.0 ± 12.9%). The magnitude of these performance decrements exceeded those observed in previous SIE studies using moderate hypoxia (14.5%O2, Δbout 1–4:∼‐21% to −24%) (Takei et al., 2021). Additionally, despite the fact that severe hypoxia (12.7%O2) compromised exercise performance of SIE (decreased MPO and total work), previous studies have shown that exercise performance is preserved in moderate hypoxic conditions (14.5 to 16.4%O2) (Kon et al., 2015; Takei et al., 2020, 2021). Discrepant results between the current and previous studies could be attributed to distinct levels of hypoxia employed (severe vs. moderate hypoxia). While moderate hypoxia has conventionally been employed in laboratory and field settings, recent studies have focused on severe hypoxia for training applications (Warnier et al., 2020; Sanchez and Borrani, 2018). Severe hypoxia possibly induces a more pronounced physiological training stimulus (decreased SpO2) compared to normoxia or moderate hypoxia (Sanchez and Borrani, 2018; Goods et al., 2014). However, as impaired exercise performance may lead to a reduced mechanical training stimulus (Michael Niess et al., 2003; Wadley et al., 2006; Sanchez and Borrani, 2018), the identification of strategies to mitigate excessive performance impairment becomes pivotal. This study suggests that the INT approach, which applies severe hypoxia only during exercise but recovery in normoxia, could serve as an effective strategy to preserve exercise intensity and training load, thereby optimizing the benefits of hypoxic training.

4.2. Arterial and tissue oxygenation

In this study, performing SIE under severe hypoxia (12.7% O2) induced significant arterial deoxygenation compared to NOR (SpO2: ∼87% vs. ∼97%). Additionally, it was observed that applying hypoxic exposure only during exercise resulted in a comparable level of arterial deoxygenation in reference to hypoxia over four sprint bouts (INT: 83.3 ± 1.2% vs. HYP: 82.9 ± 3.0%). Moreover, during the recovery period, SpO2 for INT quickly returned to a level similar to that observed in NOR (INT: 97.1 ± 1.4% vs. NOR: 97.6 ± 1.4%). These findings support our hypothesis that INT creates an augmented physiological training stimulus (decreased SpO2) in comparison with NOR. Moreover, they indicate that INT allows for higher oxygen availability during recovery periods, thus preserving subsequent exercise performance. Interestingly, SpO2 for INT rapidly returned to baseline in ∼30 s after the switch back to normoxic air, facilitating recovery predominantly under normoxia during most of the recovery period.

In this study, tissue oxygenation significantly decreased (p < 0.001) across repetitions (ΔO2Hb: Δbout 1–4: −31.1 ± 10.4%). However, contrary to our hypothesis, tissue oxygenation did not differ between conditions. A previous study comparing moderate hypoxia (14.5%O2) to nomoxia (20.9%O2) also reported a lack of between‐condition difference in tissue oxygenation during SIE (Takei et al., 2021). Our results suggest that even under severe hypoxia, tissue oxygenation during SIE may not be substantially affected. Although the reduced FiO2 led to significant arterial deoxygenation, SpO2 remained sufficiently high to facilitate oxygen delivery to peripheral skeletal muscles. Similar trends in tissue oxygenation were observed for INT compared to the other two conditions. This finding reveals that the intermittent switch to normoxia during recovery periods did not notably affect tissue re‐oxygenation in the context of SIE. This could be attributed to the relatively extended recovery interval within SIE (work‐to‐rest ratio of 1:9), which provides ample time for recovery to baseline levels. In contrast, repeated sprint training in hypoxia is typically performed with very short and incomplete recovery periods (work‐to‐rest ratio of 1:2‐5), leading to a more pronounced decrease in both arterial and tissue deoxygenation across repetitions compared to equivalent training in normoxic conditions (Bowtell et al., 2014).

4.3. Neuromuscular variables

Although no significant differences were observed between conditions, RMS values of TA, GAS and BF displayed significant reductions across repetitions. Although not a universal finding (Moritani et al., 1986; Osawa et al., 2011), previous studies also found declines in surface EMG amplitudes under conditions of severe fatigue, notably during repeated sprint tests where performance reductions exceed 10% for the first to the last effort (Mendez‐Villanueva et al., 2008; Racinais et al., 2007). Our study protocol involved athletes performing maximal effort cycling, resulting in substantial decline in mechanical output across repetitions (MPO: −32.8 ± 10.8% for Δbout 1–4). This implies that decreased recruitment of motor units in specific muscles might contribute to the notable performance decline with increasing fatigue (Δbout 1–4; TA: −19.5 ± 10.8%, GAS: −32.1 ± 21.3%, BF: −41.4 ± 31.2%). Conversely, some muscles were less affected, and the SOL muscle even showed an increase in EMG amplitude across repetitions. Thus, this suggests that the lower limbs neuromuscular strategy during fatigued conditions does not adhere to a simple linear scaling pattern as observed during cycling under fresh conditions. Additionally, a prior study demonstrated that the neuromuscular consequences during SIE did not differ between hypoxic and normoxic conditions (Takei et al., 2021). Our results support this notion, indicating that neuromuscular responses remain relatively consistent between hypoxic and normoxic conditions.

4.4. Physiological and perceptual variables

There were no significant differences between conditions for blood lactate concentration or RPE. These findings may indicate that SIE in all three conditions has similar effects on physiological (rate of glycolysis) and perceptual parameters, regardless of the pattern of hypoxia exposure (continuous or intermittent only during sprints). These results are consistent with our previous study using SIE in moderate hypoxia (14.5%O2) (Takei et al., 2020, 2021). In contrast to our previous study, we observed a significant difference in heart rate between conditions, with lower values for HYP (pooled value; ∼157 bpm) and INT (∼161 bpm) compared to NOR (∼165 bpm). This decrease in heart rate could be attributed to compensatory vasodilatation during hypoxia, as indicated by Casey and Joyner (2012), where the dilation of arteries and arterioles might lead to a decrease in heart rate (Casey et al., 2012). Despite reduced heart rate, it is possible that our study reported no difference in muscle oxygenation between conditions due to preserved muscle oxygen delivery through compensatory vasodilatation.

4.5. Additional considerations and limitations

It is known that individual tolerance to hypoxia can vary significantly (Chapman, 2013). When the same degree of hypoxia is applied to identical exercise training, individual responses can differ widely (Chapman, 2013). In our study, some participants achieved similar total work for SIE under hypoxic exposure, while others experienced more pronounced performance alterations. Interestingly, during HYP, the mean post‐sprint SpO2 value for individuals who achieved similar total work was lower (SpO2: ∼81%) than that of those who experienced pronounced performance decrement (SpO2: ∼88%). It suggests a possibility that individuals with higher arterial oxygen extraction during the sprint may exhibit better performance during SIE. However, two participants found HYP excessively challenging and chose to discontinue the experiment with substantial arterial deoxygenation (SpO2: ∼76%), even though they managed to complete the entire INT session. Therefore, there is also a possibility that excessive arterial deoxygenation may lead to exercise intolerance. Taken together, providing an alternative option such as the INT approach can be a valuable solution to accommodate participants with varying levels of hypoxia tolerance.

While this study primarily focused on the effects of intermittent hypoxic exposures during the active phases of SIE, it is noteworthy that most hypoxic training studies performed at maximal exercise intensity have been conducted as RSH. This involves short (<30 s) ‘all‐out’ efforts with brief (<60 s) incomplete recoveries (Brocherie et al., 2017). Due to the short recoveries of RSH, manipulating the inhaled air condition of inner‐set recoveries becomes challenging. However, some studies have examined the effects of normoxic inter‐set recoveries on performance, physiological, and neuromuscular responses (Brocherie et al., 2023; Girard et al., 2015; Soo et al., 2020). Taken together, there is still a lack of studies investigating hypoxic exposure during the active phases of ‘all‐out’ repetitive exercise with normoxic recoveries.

One limitation of this study was the lack of an investigation into a condition where intermittent hypoxic exposure is applied solely during recovery periods only (i.e., between‐sprints only) (Papoti et al., 2023). In a previous study, the effects of intermittent severe hypoxic exposure (13.6%O2) during recovery periods of high‐intensity interval exercise (1‐min at 120% peak velocity followed by 2‐min passive recovery) were explored (Dellavechia de Carvalho et al., 2023). This study reported lower SpO2 and higher heart rate during recovery periods, yielding results opposite to those observed in our study. Therefore, the timing of intermittent hypoxic exposure (during active or passive phases) may have a different impact on acute performance and/or physiological responses.

Another limitation was our small sample size (n = 7). Although our study met the calculated sample size requirement of six participants based on the mean effect (d = 1.48) observed in performance variables (Goods et al., 2014), recruiting only seven participants may still be considered relatively small for some physiological and neuromuscular variables. However, given that the effect of SpO2 responses between conditions in our study was notably large (d > 3.48), our conclusion asserting that severe hypoxic SIE with normoxic recovery induced significant arterial deoxygenation during the active phases while maintaining the exercise performance compared to normoxia is supported. Nevertheless, future studies with larger sample sizes would be needed to confirm the present physiological and neuromuscular findings.

5. CONCLUSION

In trained sprinters, adding severe hypoxic exposure solely during sprint interval exercise, with recovery in normoxia induced significant decrease in SpO2 while maintaining exercise performance in reference to normoxia. Additionally, EMG, blood lactate concentration and RPE responses did not differ from equivalent training in normoxia.

CONFLICT OF INTEREST STATEMENT

There are no other conflicts of interest related to this study.

PATIENT CONSENT STATEMENT

We recruited participants after obtaining written informed consent.

ACKNOWLEDGMENTS

The author contributions are as follows. Experiment design: Naoya Takei and Gaku Kakehata. Experiment implementation: Naoya Takei, Gaku Kakehata, Takeru Inaba, Yuki Morita and Hinata Sano. Data analysis: Naoya Takei, Gaku Kakehata, Takeru Inaba, Yuki Morita and Hinata Sano. Analyzing and writing advisory: Olivier Girard and Hideo Hatta. This article has undergone review and approval by all listed authors. The present study received financial support from JSPS KAKENHI Grant No. 20K23286.

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