Journal of Physical Education and Sport ® (JPES), Vol. 24 (issue 8), Art 213, pp. 1920 - 1926, August 2024
online ISSN: 2247 - 806X; p-ISSN: 2247 – 8051; ISSN - L = 2247 - 8051 © JPES

Original Article
Comparing muscle oxygen saturation patterns in swimmers of different
competitive levels
MARIA TERESA BENINCASA1, ENRICO SERRA2, DANIELE ALBANO3, RODOLFO VASTOLA4
1,2,3
Department of Human, Philosophical and Educational Sciences, University of Salerno, ITALY.
2
Department Neuroscience, Biomedicine and Movement Sciences, University of Verona, ITALY.
4
Department of Political and Social Studies, University of Salerno, ITALY.
Published online: August 31, 2024
Accepted for publication : August 15, 2024
DOI:10.7752/jpes.2024.08213
Abstract:
Monitoring training intensity through physiological parameters is crucial for understanding athletes' adaptive
responses. Research has identified maximum muscle deoxygenation and the cumulative time with muscle
oxygen saturation below 90% (SmO2 ≤ 10%) as key indicators of acute peripheral demand and effective muscle
adaptations. This study examines variations in SmO2 among swimmers of different competitive levels using the
Moxy® device during typical training sessions. The Moxy® device uses NIRS, an emerging technique that isincreasingly valued for its ability to directly and non-invasively monitor tissue oxygenation and hemodynamic
parameters during physical activity. The objective is to determine whether the intensity during a typical swim
training session (code B1) can reduce SmO2 to 10% or lower and to assess differences in athletes' ability tomaintain low muscle oxygen saturation for an extended period. The study sample consists of four malecompetitive swimmers with varying levels of competition, with SmO2 measurements taken from the deltoid, a
key muscle in swimming. The results reveal that national-level swimmers spend significantly more time below
the 10% SmO2 threshold compared to regional-level swimmers, indicating a higher peripheral muscle demand
and a greater capacity to maintain training intensity. This study emphasizes the importance of SmO2
measurements for personalizing training and optimizing athletic performance, facilitating the creation of more
effective training programs to enhance overall performance. Additionally, it highlights the significant potentialof NIRS technology in sports science research and its application in refining training methodologies acrossvarious athletic disciplines.
Keywords: Muscle deoxygenation; Peripheral adaptations; Near-infrared spectroscopy (NIRS); Swimming
training; Anaerobic threshold
Introduction
Monitoring training intensity through physiological parameters is crucial for understanding athletes'
adaptive responses to training (Dalamitros et al., 2021). This assessment allows the identification of potential
areas for improvement and limiting factors of physical performance (Perrey, 2022) and helps prevent the risk of
injuries (Vallance et al., 2020). The study of systemic physiological changes induced by physical exercise, suchas heart rate, oxygen consumption, and blood lactate concentration, is a key element in estimating exercise
intensity and evaluating individual adaptation to training (Perrey, 2022). These measurements are widely used in
sports, particularly in swimming (Smith, Norris & Hogg, 2002; Keskinen, Keskinen & Mero, 2007; Pyne, Lee &Swanwick, 2001). However, traditional methods such as lactate measurements are invasive and not always
precise (Swart & Jennings, 2004). Additionally, one of the main challenges in monitoring heart rate in highlevel athletes is the low sensitivity of heart rate response to workload (Klusiewicz et al., 2021).
Considering these limitations of traditional methods, it may be useful to explore other methodologies
for monitoring muscle behavior and intensity. The two main methodologies for monitoring local muscle
behavior during exercise are surface electromyography (EMG) for measuring muscle activity and Near-Infrared
Spectroscopy (NIRS) for detecting muscle oxygenation (Ferrari, Muthalib & Quaresima, 2011). Both techniques
are applied in both field and laboratory settings (Perrey & Ferrari, 2018; Yogev et al., 2023). NIRS is an
emerging technique increasingly valued for its ability to directly and non-invasively monitor changes in tissue
oxygenation and hemodynamic parameters during physical activity (Perrey & Ferrari, 2018; Hamaoka et al.,2007; Bhambhani, 2004). Recent studies indicate that skeletal muscle oxygen saturation (SmO2), which
represents the balance between oxygen supply and consumption at the local muscle level (Hamaoka et al., 2007),can be used to describe and predict an individual's efficiency in performing endurance physical activities(Batterson et al., 2023). Measuring this variable can help coaches and athletes understand how the body responds
to training and manages oxygen supply and utilization during prolonged exertion in real time (Klusiewicz et al.,2021; Farzam, Starkweather & Franceschini, 2018).
1920---------------------------------------------------------------------------------------------------------------------------------Corresponding Author: MARIA TERESA BENINCASA, E-mail: mariateresabenincasa1@gmail.com

MARIA TERESA BENINCASA, ENRICO SERRA, DANIELE ALBANO, RODOLFO VASTOLA--------------------------------------------------------------------------------------------------------------------------------------Several authors (Kirby et al., 2021; Rodrigo-Carranza et al., 2021; Crum et al., 2017; Borges & Driller,
2016; Racinais, Buchheit & Girard, 2014; Grassi et al., 1999) have emphasized that NIRS measurements can be
an effective method for determining training intensity zones, which are based on metabolic changes occurring in
the active muscle along with heart rate. Additionally, it is possible to identify a specific level of oxygenation towhich the muscles return after a certain type of physical exertion, thereby enabling the monitoring of recovery
periods (Buchheit et al., 2011; Stöcker et al., 2016; Kime et al., 2003). Consequently, this technology can be
useful in various sports research fields to customize an athlete's training. One sport where the data obtained can
assist in creating a specific athletic practice for the individual is swimming. In swimming, where small variationsin technique and physical condition can significantly impact performance, it is essential to explore how NIRSderived measurements can improve our understanding of SmO2 during cyclic and characteristic movements(Jones, Parry & Cooper, 2018). Some researchers (Pratama & Yimlamai, 2020; Dalamitros et al., 2019; Jones,
Parry & Cooper, 2018; Wu, Song & Xu, 2015) have recently applied this technology in swimming as acomplementary method to improve understanding of recovery processes, training, and peripheral adaptations.
However, despite its potential, the use of NIRS in this sport is still underexplored, leaving a gap in understanding
how swimmers manage oxygen delivery and utilization during high-intensity efforts, highlighting the need forfurther research in this area.
Swimming workouts consist of intervals of varying intensity, which differentially stimulate aerobic andanaerobic metabolic processes. Additionally, in sports where arm muscles are dominant, such as swimming,
which show a larger cross-sectional area of type II muscle fibers, muscle power dependency is greater thancardiorespiratory dependency. Therefore, it is necessary to identify training sessions that elicit a high peripheral
demand to introduce sessions that target muscle oxidative adaptations (Paquette, Bieuzen & Billaut, 2019).
In the study by Paquette et al. (2019), it is suggested that maximum muscle deoxygenation and cumulative timeat maximum muscle deoxygenation in canoe athletes, below 90% (SmO2 ≤ 10%), are good indicators of acuteperipheral demand and key factors for effective muscle adaptations. Therefore, the objective of this study is toinvestigate variations in peripheral muscle oxygen saturation (SmO2) using the Moxy® device in swimmers
during a typical training session to understand if anaerobic threshold intensity allows reaching an SmO2 of 10%
or lower and to determine optimal peripheral adaptations. Additionally, the study aims to evaluate whether there
are significant differences in the ability of athletes of different levels to maintain significant low muscle
desaturation for an extended period.
Material and methods
Participants
The sample consists of 4 male competitive swimmers (average age 18.5 ± 2.9 years; height 177.54 ±0.10 cm; body mass 70.5 ± 7.4 kg) from the Youth (n = 2), Junior (n = 1), and Senior (n = 1) categories, all withseveral years of experience in swimming and participation in regional and national competitions. Athletes 1 and
2 are classified as national-level athletes due to their participation for national competitions with high qualifying
times. In contrast, athletes 3 and 4 are classified as regional-level athletes, as they have not achieved highqualifying times and predominantly participate in regional competitions. Additionally, they do not present any
respiratory, cardiovascular, metabolic, musculoskeletal, or neoplastic diseases, nor any infectious or
inflammatory processes at the time of measurement.
Procedures and Measures
Participants were asked to abstain from consuming drugs, antioxidants, and nutritional supplements 24hours before the experimental session. All athletes were informed of the potential risks and provided written
informed consent for participation in this study. Informed consent was obtained from parents or guardians forparticipants under 18 years of age. The study was conducted in accordance with the Declaration of Helsinki. The
study was designed and coordinated by the research staff of the Laboratory of the Laboratory for Innovative
Teaching and Sports Performance Analysis at the University of Salerno (Unisa).
SmO2 was measured using the MOXY® monitor, a continuous wave NIRS device (Fortiori Design
LLC, Hutchinson, MN, USA). The device employs four wavelengths (680, 720, 760, and 800 nm) to assess
absorbance through a modified version of the Beer-Lambert law. This calculation aims to determine the ratio
between the concentrations of oxygenated hemoglobin and myoglobin relative to the total amount of hemoglobin
and myoglobin (Feldmann, Schmitz & Erlacher, 2019; Crum et al., 2017). The ratio is then multiplied by 100
and expressed as a percentage (Fortiori Design LLC, 2015; Barstow, 2019). The obtained value, defined asmuscle oxygenation (SmO2), is expressed as a percentage on a scale from 0 to 100% (Kirby et al., 2021;
Feldmann, Schmitz & Erlacher, 2019) and is useful for understanding the oxidative metabolism of skeletal
muscle in real-time during exercise (Grassi & Quaresima, 2016). The default sampling frequency is 0.5 Hz,
allowing data acquisition at the four wavelengths used for 80 consecutive cycles. The average output isgenerated every 2 seconds (Feldmann, Schmitz & Erlacher, 2019; Batterson et al., 2023). The distance between
the emitter and the two detectors is 12.5 and 25 mm, respectively, allowing a penetration depth of 12.5 mm(Feldmann, Schmitz & Erlacher, 2019; McManus, Collison & Chris, 2018). The muscle oxygen saturation
measurement device has built-in memory to record training parameters and offers non-invasive measurements,
wireless connectivity, small size, and waterproofing (Klusiewicz et al., 2021). Thanks to the built-in memory, it----------------------------------------------------------------------------------------------------------------------------1921
JPES ® www.efsupit.roMARIA TERESA BENINCASA, ENRICO SERRA, DANIELE ALBANO, RODOLFO VASTOLA--------------------------------------------------------------------------------------------------------------------------------------was possible to transfer data from the Moxy monitor to the “Moxy Monitor Setting” app version 1.5.5, fromwhich they were then downloaded using the default filter to reduce signal noise.
Measurements were conducted at the indoor swimming pool of the University Sports Center (CUS) in
Salerno, with a length of 25 meters that meets semi-Olympic standards. The operations were carried out at aconstant water temperature of 28°C during the general period of the competitive season. Before the training
sessions began, all Moxy devices were carefully positioned and checked to ensure proper functioning. Resting
SmO2 and Thb measurements were recorded for each athlete. Before each training session, the deltoid area wasprepared by shaving the skin and sanitizing it with alcohol before applying the device. The deltoid was selected
as the muscle of study because it is part of the upper limb musculature, which plays a predominant role inpropulsion during swimming (Morouço et al., 2015), and due to its significant involvement, both during therecovery phase and the propulsion phase in freestyle swimming (McLeod, 2011; Marugo, 2018). The dominantside was chosen as it provides more accurate information on overall oxygen utilization (Reinpõld & Rannama,2023).
To measure the SmO2 of the deltoid, a Moxy device was placed along the line connecting the acromionand the epicondyle following the SENIAM project for electromyographic measurements (Hermens et al., 2000).
The emitter and detectors were aligned in the direction of the muscle fibers and secured to the skin using thematerial suggested by the manufacturer, in addition to extra fixation with a waterproof and transparent bandage
to ensure a secure hold. SmO2 data were consistently recorded during all training sessions.
The training protocol consists of a standardized warm-up detailed in Table 1 and a training session
outlined in Table 2. The warm-up includes a total of 1800 meters of continuous swimming with specificexercises for arms and legs, followed by a passive rest of two minutes before the main part of the training andthus the examined protocol. The training session was performed using the freestyle stroke. Freestyle was chosen
as it is the most commonly used swimming style in training due to its efficiency and suitability for long-duration
activities (Bartolomeu, Costa & Barbosa, 2018; Gonjo et al., 2018). Other styles, particularly breaststroke andbutterfly, are more demanding both technically and energetically and cannot always be sustained over long
distances at moderate speeds (Di Prampero, 2015; Zamparo, Cortesi & Gatta, 2020; Barbosa et al., 2006).
The intensity zone of the examined training (B1) was determined based on the communication codes used in
Italian swimming, defined by the Italian Swimming Federation (FIN), which identify various work zones from
low to high intensities (Rossetto, 2022; Bottalico, 2022). These zones are defined based on the stimulation ofdifferent metabolic energy systems (Puce et al., 2018). The pace to be maintained during the training sessions
was calculated using the differential test. Water starts with a push from the edge were used to eliminate theinfluence of diving.
Table 1. Warm-up
Set
1x400mTotal Volume

8x50m (25REM/25GB)

400m

2x(4x75m)(25GB+25TECHNIQUE+25COMPLETE)
2x(4x50m) PROGRESSION

600m

400m

400m

Table 2. Training
Code
B1

Training
24x100 a 1’40’’

Analysis
For each trial and each athlete, the central portion equivalent to 150 data points was analyzed. The data
were normalized based on the minimum and maximum values recorded during the trial itself. For the analyzed
data portion, the mean and standard deviation were calculated. The number of data points below the 10%threshold was measured, subsequently converted into seconds, and used for comparison between athletes. To
quantify the difference between national-level and regional-level athletes, the time spent below the 10% SmO2
threshold was used to calculate Cohen's d, a measure of effect size.
This method allows for understanding the magnitude of the difference between the two groups in astandardized way. All analyses were conducted in MATLAB (The MathWorks, Inc. 2024) using a code
specifically written for this study.
Results
In Fig. 1, 2, 3, and 4, the SmO2 curves for each athlete are shown, along with the 10% threshold. The
SmO2 data, including means and standard deviations, are presented in Table 3, along with the time spent below
the 10% SmO2 threshold.
1922---------------------------------------------------------------------------------------------------------------------------JPES ® www.efsupit.roMARIA TERESA BENINCASA, ENRICO SERRA, DANIELE ALBANO, RODOLFO VASTOLA--------------------------------------------------------------------------------------------------------------------------------------Figure 1. Muscle Oxygen Saturation (SmO2) Curve of Athlete 1 during the Training Session

Figure 2. Muscle Oxygen Saturation (SmO2) Curve of Athlete 2 during the Training Session

Figure 3. Muscle Oxygen Saturation (SmO2) Curve of Athlete 3 during the Training Session

Figure 4. Muscle Oxygen Saturation (SmO2) Curve of Athlete 4 during the Training Session

Table 3. Mean and Std. Dev. of SmO2 and Time Spent Below the 10% Threshold
AthleteMean (%)

Std. Dev. (%)

Time SmO2 ≤ 10% (s)Athlete 1

29.48

32.62

152.00Athlete 2

36.61

35.63

126.00Athlete 3

37.72

30.79

54.00

Athlete 4

45.32

26.80

6.00

The Cohen's d effect size was found to be approximately 3.99 (Table 4). This value indicates a verylarge effect, suggesting a substantial difference between the two groups in the time spent below the 10%
desaturation threshold.
----------------------------------------------------------------------------------------------------------------------------1923
JPES ® www.efsupit.roMARIA TERESA BENINCASA, ENRICO SERRA, DANIELE ALBANO, RODOLFO VASTOLA--------------------------------------------------------------------------------------------------------------------------------------Table 4. Time Spent Below the 10% Threshold with Mean, Std. Dev., and Cohen's d Effect Size
National-level athletesTime SmO2 ≤ 10% (s)Athlete 1

152.00Athlete 2

126.00Mean + Std. Dev. (s)Cohen's d Effect Size

139 ±18.39

Regional-level athletesAthlete 3

54.00

Athlete 4

6.00

3,99
30 ±33.94

Discussion
Muscular oxidative capacity, which refers to the muscles' ability to efficiently extract and utilize oxygen
during physical exercise, improves when there are variations in muscle oxygenation during training (Daussin etal., 2008). Prolonged periods of training with low partial oxygen pressure at the muscle level stimulate
mitochondrial biogenesis (Hoppeler et al., 2003). Consequently, training sessions that induce repeated andsignificant muscle deoxygenation could serve as an effective stimulus to promote positive muscular adaptations.
Understanding the degree of muscle deoxygenation that occurs during training is crucial, as it affects the signals
responsible for post-training metabolic modifications (Paquette, Bieuzen & Billaut, 2019).
The study explored variations in muscle oxygen saturation (SmO2) using the Moxy® device during atypical swimming training session. It was observed that a B1 code training (anaerobic threshold) in swimming
induced significant muscle deoxygenation, as SmO2 dropped below 10%. This low SmO2 value could be
attributed to both increased oxygen utilization by the muscle to sustain the exercise intensity and a lower Thb
concentration, a parameter not analyzed in this context since, unlike SmO2, it is considered less reliable (Crumet al., 2017). As also highlighted by the study by Paquette et al. (2019), high intensities result in significant
levels of deoxygenation, but such intensities often also induce substantial neuromuscular fatigue. Therefore, B1
training performed at a sub-maximal intensity in swimming could still elicit a significant peripheral demand
without causing excessive neuromuscular fatigue. The results also indicate significant differences in the abilityof national-level swimmers compared to regional-level swimmers in reaching and maintaining SmO2 below 10%
during B1 intensity training. National-level swimmers, in fact, spent significantly more time below thisthreshold, suggesting a greater peripheral muscular demand during the training session and a better ability tosustain such intensity.
Conclusions
This study highlights the potential of muscle oxygen saturation (SmO2) measurements as a valuable
tool for monitoring and enhancing athletic performance in swimmers. The results show that swim training
conducted at anaerobic threshold intensity can reduce SmO2 below 10%, serving as a reliable indicator of acuteperipheral demand and a key element for promoting effective muscle adaptations. Maintaining this muscle
deoxygenation threshold could be used to distinguish national-level athletes from those at lower levels.
Additionally, national-level athletes demonstrate a greater capacity for muscle desaturation, which could beleveraged to design more effective training programs aimed at improving overall performance.
The practical implications of this study are relevant and could have a considerable impact on how
coaches manage and optimize training programs. The use of real-time SmO2 monitoring allows coaches to more
precisely adjust the intensity and duration of training sessions, maximizing adaptive benefits while
simultaneously reducing the risk of overtraining. This information can be used to develop personalized programs
that more effectively meet the individual physiological needs of athletes.
From a theoretical perspective, the study enriches the existing literature by offering new insights into
the use of NIRS in sports, particularly in swimming. The research lays the groundwork for further studies aimed
at exploring how muscle oxygenation can be integrated with other physiological parameters for a morecomprehensive assessment of athletes' capabilities.
Disclosure statement: The author reports there are no competing interests to declare.
Data availability statement: Data available on request.
Acknowledgements The authors would like to thank Falcon Scientific Editing (https://falconediting.com) for
proofreading the English language in this paper.
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