Citation: Sawada, T.; Okawara, H.;
Nakashima, D.; Ikeda, K.; Nagahara,
J.; Fujitsuka, H.; Hoshino, S.; Maeda,
Y.; Katsumata, Y.; Nakamura, M.;
et al. Constant Load Pedaling
Exercise Combined with Electrical
Muscle Stimulation Leads to an Early
Increase in Sweat Lactate Levels.
Sensors 2022, 22, 9585. https://
doi.org/10.3390/s22249585
Academic Editors: Gian Marco Revel
and Sara Casaccia
Received: 9 November 2022
Accepted: 6 December 2022
Published: 7 December 2022
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sensors
Article
Constant Load Pedaling Exercise Combined with Electrical
Muscle Stimulation Leads to an Early Increase in Sweat
Lactate Levels
Tomonori Sawada 1
, Hiroki Okawara 1
, Daisuke Nakashima 1,*
, Kaito Ikeda 1, Joji Nagahara 1,
Haruki Fujitsuka 1, Sosuke Hoshino 1, Yuta Maeda 1, Yoshinori Katsumata 2,3, Masaya Nakamura 1
and Takeo Nagura 1,4
1
Department of Orthopaedic Surgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku,
Tokyo 160-8582, Japan
2
Institute for Integrated Sports Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku,
Tokyo 160-8582, Japan
3
Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku,
Tokyo 160-8582, Japan
4
Department of Clinical Biomechanics, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku,
Tokyo 160-8582, Japan
*
Correspondence: nakashima@keio.jp; Tel.: +81-3-5363-3812
Abstract: A novel exercise modality combined with electrical muscle stimulation (EMS) has been
reported to increase cardiovascular and metabolic responses, such as blood lactate concentration. We
aimed to examine the effect of constant load pedaling exercise, combined with EMS, by non-invasively
and continuously measuring sweat lactate levels. A total of 22 healthy young men (20.7 ± 0.8 years)
performed a constant load pedaling exercise for 20 min at 125% of the pre-measured ventilatory
work threshold with (EMS condition) and without (control condition) EMS stimulation. Blood lactate
concentration was measured by blood samples obtained from the earlobe every minute. Sweat lactate
was monitored in real time using a sensor placed on the forearm. The sweat lactate threshold (sLT)
was deﬁned as the point of increase in sweat lactate. sLT occurred signiﬁcantly earlier in the EMS
condition than in the control condition. In the single regression analysis, the difference in sLT between
the two conditions, as the independent variable, was a signiﬁcant predictor of the difference in blood
lactate concentrations at the end of the exercise (p < 0.05, r = −0.52). Sweat lactate measurement may
be a noninvasive and simple alternative to blood lactate measurement to determine the effectiveness
of exercise combined with EMS.
Keywords: sweat lactate; blood lactate; electrical muscle stimulation; exercise
1. Introduction
Electrical muscle stimulation (EMS) has been widely used in rehabilitation and sports
to assist in exercise therapy or to increase the exercise load, in combination with regular
exercise [1–6]. Adding EMS has a signiﬁcant impact on muscle metabolism and induces
substantial physiological adaptations [7,8]. Stimulated contractions caused by adding
EMS intensively activates anaerobic glycolysis for energy production by phosphocreatine
and glycogen degradation, leading to an increase in blood lactate concentration [9–11].
Lactate, which is produced in the glycolytic pathway, is widely recognized as an efﬁcient
energy source used by systemic organs [12]. Additionally, it has been reported that lactate
increases the peroxisome proliferator-activated receptor-γ coactivator- (PGC-) 1α mRNA
expression and mitochondrial biogenesis [13–17]. PGC-1α is the master controller of mi-
tochondrial biogenesis and promotes mitochondrial biogenesis through the activation of
various transcription factors [18]. Since mitochondrial content is generally considered an
indicator of endurance performance [19], increasing mitochondrial biogenesis induced by
Sensors 2022, 22, 9585. https://doi.org/10.3390/s22249585
https://www.mdpi.com/journal/sensors
Sensors 2022, 22, 9585
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exercise training is believed to be an important adaptative event that improves exercise
tolerance capacity [20,21]. Further, an exercise-induced increase in PGC-1α mRNA was
observed above the ﬁrst lactate threshold, but not below it [22]. Therefore, it is important
to determine the EMS intensity that increases the blood lactate levels without fatigue, as
compared to exercise without EMS, to establish an efﬁcient program of exercise training
combined with EMS. However, measuring the blood lactate levels frequently to determine
the appropriate EMS output is not feasible, since it requires invasive blood sampling. Addi-
tionally, it is unclear whether the optimal measurement time should be at the moment of
puncture, or when the blood is discharged after a time lag of 5–10 s following the puncture.
Thus, establishing a noninvasive method of monitoring the dynamics of metabolism during
exercise combined with EMS is necessary.
To date, noninvasive biosensors of lactate using sweat from the body surface have
been reported [23] and have shown that sweat lactate levels increase in conjunction with
exercise intensity [24–26]. In a recent study, the point of sweat lactate level elevation
during incremental exercise was well correlated with the lactate threshold determined
from the blood lactate concentration and the ventilatory threshold (VT), determined using
a respiratory gas analyzer in patients with cardiovascular disease, as well as healthy
individuals [27]. When this technology is applied to exercise combined with EMS, the
noninvasive and continuous monitoring of lactate behavior during exercise could be
possible, and increased blood lactate levels may be more easily detected by measuring
sweat lactate levels. In particular, it would be suitable for the remote rehabilitation of
patients and athletes outside of medical institutions and may enable effective and safe
exercise based on daily physical conditions.
Thus, the current study aimed to examine whether sweat lactate concentrations could
be used to detect increased blood lactate levels during exercise combined with EMS. We
hypothesized that the increase in blood lactate concentration during exercise combined
with EMS would be predicted, to some extent, by the increase in sweat lactate levels.
2. Materials and Methods
2.1. Participants
After recruiting participants from one university starting in May 2021, 22 healthy
recreationally trained men (average age, 20.3 years) participated in this study conducted
between June and September 2021 (Table 1). The inclusion criteria were (1) age ≥18 years
and (2) no medical history of illness or injury, and not currently taking any medication.
The exclusion criteria were (1) lower extremity injury or disorder that hinders complete
participation in exercise, (2) metabolic, cardiac, respiratory, and psychiatric diseases, and
(3) severe skin disease. The study protocol was conducted in compliance with the ethical
guidelines for medical and health research involving human subjects and was approved
by the Institutional Review Board of our institution (approval number: 20190229). Written
informed consent was obtained from the individuals for study participation and publication
of the ﬁndings before enrollment.
Table 1. Participant characteristics (n = 22).
Mean (SD)
Range
Age (years)
20.7 (0.8)
19–22
Height (cm)
174.0 (5.4)
161.0–184.0
Weight (kg)
66.8 (9.0)
46.8–91.5
BMI (kg/m2)
22.0 (2.2)
18.1–27.0
Body fat ratio (%)
15.4 (4.3)
8.6–23.8
Fat mass (kg)
10.5 (4.0)
4.0–20.1
Lean body mass (kg)
56.4 (6.2)
42.8–71.4
Muscle mass (kg)
53.4 (5.9)
40.5–67.7
Total body water (kg)
40.5 (6.5)
30.3–57.6
Body water (%)
59.7 (4.7)
49.6–65.9
BMI, body mass index.
Sensors 2022, 22, 9585
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2.2. Experimental Protocol
All participants were asked to visit our laboratory three times. For each of the three vis-
its, an interval of at least 3–14 days was allowed. In all three sessions, the room temperature
was set to the same level and pedaling exercises were performed using an electromagneti-
cally braked ergometer (POWER MAX V3 Pro; Konami Sports Co., Ltd., Tokyo, Japan) with
a target of 70 rpm. At the ﬁrst visit, prior to an incremental load test, body composition
was measured using a multi-frequency body composition meter (MC780A-N; TANITA Cor-
poration, Tokyo, Japan). Then, the exercise test was performed, and the VT was determined
for each individual with a respiratory gas analyzer using the ventilatory equivalent, excess
carbon dioxide, and modiﬁed V-slope methods [28]. Speciﬁcally, following a 2 min rest
to stabilize the heart rate and respiration, the participants performed a 4 min warm-up,
pedaling at 20 W, and then exercised at increasing intensity until they could no longer
maintain the pedaling rate (volitional exhaustion). The resistance was increased in 25 W
increments from 50 W at 1 min intervals. Once the exercise tests were terminated, the
participants were instructed to stop pedaling and remain on the ergometer for 3 min. The
expired gas ﬂow was measured using a breath-by-breath automated system (Aeromonitor®;
Minato Medical Science Co., Ltd., Osaka, Japan). Prior to the second and third visits, the
participants were instructed to keep a fast for 3 h prior to the measurements and to refrain
from caffeine and alcohol intake and engaging in intensive exercises within 12 h. Partici-
pants were also asked to drink 500 mL of water before the exercise. On the second visit,
constant load pedaling exercise, without EMS stimulation (control condition, hereinafter
called “CR condition”), was performed. To perform the exercise, the sweat lactate level
was monitored with a sweat lactate sensor (Grace Imaging Inc., Tokyo, Japan) attached to
the left forearm, and a Fitbit Inspire HR (Fitbit Inc., San Francisco, CA, USA) was attached
to the left wrist, two-ﬁnger widths above the ulnar styloid process, to measure the heart
rate. After an initial 2 min of rest and measurement of sweat and blood lactate levels, a
20 min pedaling exercise was performed at a constant load of 125% of the pre-measured
ventilatory work threshold. The loading of VT125% was determined based on a previous
study [11] reporting that the difference in blood lactate concentrations between conditions
with and without EMS was signiﬁcantly greater in the VT125% exercise loading than in the
VT50% and VT75% exercise loading. During the pedaling exercise, the sweat lactate level
was measured at 1 Hz, and the blood lactate level was measured (Lactate Pro 2; ARKRAY,
Inc., Kyoto, Japan) by drawing blood from the earlobe every minute. The exercise was
stopped under the following conditions, even if the duration was <20 min: when the heart
rate exceeded 190 bpm; when the examiner judged the exercise to be dangerous to the
patient; when the participant requested to stop; when the participant became exhausted;
or when it became difﬁcult to maintain the target speed of 70 rpm. In such cases, blood
lactate levels were measured at the end of the exercise. At the third visit, the exercise was
performed in the same way as the second visit, but with EMS stimulation. In the EMS
condition, participants wore a commercially available EMS suit separated into a top and a
bottom section (Powersuit; MTG Ltd., Nagoya, Japan) and performed pedaling exercises
while seven muscles on each side of the upper and lower trunk were stimulated (biceps
brachii, triceps brachii, rectus abdominis, oblique abdominis, gluteus medius, quadriceps
femoris, and hamstrings). In accordance with a previous study [11], all electrode pairs were
synchronized and biphasic square current pulses with a 100 µs duration were constantly
applied at a stimulation frequency of 4 Hz. The EMS intensity was set to a maximum
intensity at which each participant did not feel pain or discomfort. The maximal electrical
potential and current of this device were 50 V and 4.85 mA, respectively.
Sensors 2022, 22, 9585
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2.3. Sweat Lactate Threshold Measurements
The sweat lactate level was measured using a wearable sensor, which quantiﬁes lactate
concentration as a current value because it reacts with sweat lactate and generates an
electric current [27]. The current value can be obtained as continuous data within 0.1–80 µA
in 0.1-µA increments. After calibration using saline for approximately 3 min, the sensor
chip connected to the sensor device was attached to the participants’ dorsal left forearm,
which was cleaned with an alcohol-free cloth. Additionally, the data were recorded at a
sampling frequency of 1 Hz for mobile applications using a Bluetooth connection. The
recorded data were converted to moving average values over 13 s intervals and individually
underwent zero correction using the baseline value. Sweat lactate threshold (sLT) was
deﬁned as the ﬁrst signiﬁcant increase in the sweat lactate level above baseline, based on
graphical plots [27] by three researchers in consultation.
2.4. Statistical Analysis
All data are presented as the mean plus standard deviation. For the heart rate and
blood lactate concentration data, in a population who performed 20 min of exercise in
both conditions, two-way analysis of variance with repeated measures was used to test
the main effects under two conditions (CR and EMS) and ﬁve time points (baseline, 5, 10,
15, and 20 min), as well as the interaction effect between the time point and the condition.
Bonferroni correction was performed for post hoc pairwise comparison. For sLTs, paired
t-tests were conducted on participants for whom sLTs could be deﬁned in order to compare
values between the two conditions. Additionally, to predict the increase in blood lactate
concentration in the EMS condition relative to the CR condition, a single regression analysis
was performed, with the blood lactate concentration change between the two conditions as
the dependent variable, and the change in the time to reach sLT between the two conditions
as the independent variable. In the regression analysis, the blood lactate concentration
was used as the value after 20 min, or at the end of exercise, because the analysis included
patients who could not exercise for 20 min. All statistical analyses were performed using
SPSS Statistics version 27.0 (IBM Corp., Armonk, NY, USA), with statistical signiﬁcance set
at 0.05.
3. Results
Representative data of sweat and blood lactate concentrations during a constant load
pedaling exercise are shown in Figure 1. Of the 22 participants, 15 completed 20 min of
constant load exercise in both conditions, and the remaining 7 had difﬁculty maintaining
the target speed of 70 rpm due to fatigue and stopped the exercise before 20 min. Four of the
seven participants had difﬁculty completing 20 min in both conditions, two had difﬁculty
completing 20 min only in the EMS condition, and one had difﬁculty completing 20 min
only in the CR condition. Additionally, detecting sLT was difﬁcult in 2 out of 22 participants,
as the sensor did not respond, due to lack of sweating in one participant, and the sensor
chip was poorly connected in the other participant. Therefore, only 20 participants were
included in the analysis of sLT.
Sensors 2022, 22, 9585
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Figure 1. Representative data of sweat lactate and blood lactate concentrations during constant load 
pedaling exercise. EMS, electrical muscle stimulation; CR, without EMS stimulation; bLA, blood 
lactate; sLA, sweat lactate; sLT, sweat lactate threshold. 
 
Figure 2 shows the comparison of the heart rate under the two conditions. As a result, 
there was a main effect of time point observed [F (4, 56) = 167.831, p < 0.01]. Post hoc test 
results showed significant differences between BL and other measurement time points (5, 
10, 15, and 20 min), between 5 and 10, 5 and 15, and 5 and 20 min. Contrastingly, there 
was no main effect for condition, and no interaction effect between condition and meas-
urement point. Figure 3 also depicts the comparison of blood lactate concentration be-
tween the two conditions. For blood lactate concentration, there was a main effect of time 
point [F (4, 56) = 19.703, p < 0.01] and condition [F (1, 14) = 11.050, p < 0.01] and an interac-
tion effect between time point and condition [F (4, 56) = 4.069, p < 0.01]. Post hoc test results 
showed significant differences between BL and other measurement points (5, 10, 15, and 
20 min). Additionally, significant differences were observed between the conditions at 10, 
15, and 20 min, with the EMS condition showing an increase in blood lactate concentration 
compared to the CR condition. 
-1
0
0
120
240
360
480
600
720
840
960
1080
1200
1320
Time [s]
Figure 1. Representative data of sweat lactate and blood lactate concentrations during constant load
pedaling exercise. EMS, electrical muscle stimulation; CR, without EMS stimulation; bLA, blood
lactate; sLA, sweat lactate; sLT, sweat lactate threshold.
Figure 2 shows the comparison of the heart rate under the two conditions. As a result,
there was a main effect of time point observed [F (4, 56) = 167.831, p < 0.01]. Post hoc test
results showed signiﬁcant differences between BL and other measurement time points (5,
10, 15, and 20 min), between 5 and 10, 5 and 15, and 5 and 20 min. Contrastingly, there was
no main effect for condition, and no interaction effect between condition and measurement
point. Figure 3 also depicts the comparison of blood lactate concentration between the
two conditions. For blood lactate concentration, there was a main effect of time point
[F (4, 56) = 19.703, p < 0.01] and condition [F (1, 14) = 11.050, p < 0.01] and an interaction
effect between time point and condition [F (4, 56) = 4.069, p < 0.01]. Post hoc test results
showed signiﬁcant differences between BL and other measurement points (5, 10, 15, and
20 min). Additionally, signiﬁcant differences were observed between the conditions at 10,
15, and 20 min, with the EMS condition showing an increase in blood lactate concentration
compared to the CR condition.
Sensors 2022, 22, x FOR PEER REVIEW 
5 of 11 
 
 
 
Figure 1. Representative data of sweat lactate and blood lactate concentrations during constant load 
pedaling exercise. EMS, electrical muscle stimulation; CR, without EMS stimulation; bLA, blood 
lactate; sLA, sweat lactate; sLT, sweat lactate threshold. 
Figure 2 shows the comparison of the heart rate under the two conditions. As a result, 
there was a main effect of time point observed [F (4, 56) = 167.831, p < 0.01]. Post hoc test 
results showed significant differences between BL and other measurement time points (5, 
10, 15, and 20 min), between 5 and 10, 5 and 15, and 5 and 20 min. Contrastingly, there 
was no main effect for condition, and no interaction effect between condition and meas-
urement point. Figure 3 also depicts the comparison of blood lactate concentration be-
tween the two conditions. For blood lactate concentration, there was a main effect of time 
point [F (4, 56) = 19.703, p < 0.01] and condition [F (1, 14) = 11.050, p < 0.01] and an interac-
tion effect between time point and condition [F (4, 56) = 4.069, p < 0.01]. Post hoc test results 
showed significant differences between BL and other measurement points (5, 10, 15, and 
20 min). Additionally, significant differences were observed between the conditions at 10, 
15, and 20 min, with the EMS condition showing an increase in blood lactate concentration 
compared to the CR condition. 
 
Figure 2. Comparison of the heart rate between the EMS and CR conditions (n = 15). †: p < 0.01 signif-
icant main effect at time point. EMS, electrical muscle stimulation; CR, without EMS stimulation. 
-1
0
1
2
3
4
5
6
7
0
0.5
1
1.5
2
2.5
3
3.5
4
0
120
240
360
480
600
720
840
960
1080
1200
1320
Sweat lactate [µA]
Blood lactate [mmol/l]
Time [s]
bLA_CR
bLA_EMS
sLA_CR
sLA_EMS
20 minutes of constant load pedaling exercise
sLT
369 [sec]
sLT
296 [sec]
Figure 2. Comparison of the heart rate between the EMS and CR conditions (n = 15). †: p < 0.01
signiﬁcant main effect at time point. EMS, electrical muscle stimulation; CR, without EMS stimulation.
Sensors 2022, 22, 9585
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Sensors 2022, 22, x FOR PEER REVIEW 
6 of 11 
 
 
 
Figure 3. Comparison of blood lactate concentrations between the EMS and CR conditions (n = 15). 
†: p < 0.01 significant main effect at time point. * p < 0.05, ** p < 0.01 significant difference between 
conditions. EMS, electrical muscle stimulation; CR, without EMS stimulation. 
Regarding sLT, it occurred significantly earlier in the EMS condition than in the CR 
condition (Figure 4, 215.2 ± 74.5 s and 271.8 ± 104.3 s, respectively; p < 0.05). Additionally, 
in the single regression analysis, the difference in sLT between the two conditions as an 
independent variable was a significant predictor of the difference in blood lactate concen-
trations at the end of the exercise (Figure 5, p < 0.05; r = −0.52). 
 
Figure 4. Comparison of sweat lactate threshold between the EMS and CR conditions (n = 20). * p < 
0.05. EMS, electrical muscle stimulation; CR, without EMS stimulation. 
Figure 3. Comparison of blood lactate concentrations between the EMS and CR conditions (n = 15).
†: p < 0.01 signiﬁcant main effect at time point. * p < 0.05, ** p < 0.01 signiﬁcant difference between
conditions. EMS, electrical muscle stimulation; CR, without EMS stimulation.
Regarding sLT, it occurred signiﬁcantly earlier in the EMS condition than in the CR
condition (Figure 4, 215.2 ± 74.5 s and 271.8 ± 104.3 s, respectively; p < 0.05). Additionally,
in the single regression analysis, the difference in sLT between the two conditions as
an independent variable was a signiﬁcant predictor of the difference in blood lactate
concentrations at the end of the exercise (Figure 5, p < 0.05; r = −0.52).
Sensors 2022, 22, x FOR PEER REVIEW 
6 of 11 
 
 
 
Figure 3. Comparison of blood lactate concentrations between the EMS and CR conditions (n = 15). 
†: p < 0.01 significant main effect at time point. * p < 0.05, ** p < 0.01 significant difference between 
conditions. EMS, electrical muscle stimulation; CR, without EMS stimulation. 
Regarding sLT, it occurred significantly earlier in the EMS condition than in the CR 
condition (Figure 4, 215.2 ± 74.5 s and 271.8 ± 104.3 s, respectively; p < 0.05). Additionally, 
in the single regression analysis, the difference in sLT between the two conditions as an 
independent variable was a significant predictor of the difference in blood lactate concen-
trations at the end of the exercise (Figure 5, p < 0.05; r = −0.52). 
 
Figure 4. Comparison of sweat lactate threshold between the EMS and CR conditions (n = 20). * p < 
0.05. EMS, electrical muscle stimulation; CR, without EMS stimulation. 
Figure 4. Comparison of sweat lactate threshold between the EMS and CR conditions (n = 20).
* p < 0.05. EMS, electrical muscle stimulation; CR, without EMS stimulation.
Sensors 2022, 22, 9585
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Sensors 2022, 22, x FOR PEER REVIEW 
7 of 11 
 
 
 
Figure 5. Relationship between the change in blood lactate concentration at the end of exercise and 
the change in sweat lactate threshold (n = 20). The amount of change is calculated as the value of the 
EMS condition minus the value of the CR condition. EMS, electrical muscle stimulation; CR, without 
EMS stimulation. 
4. Discussion 
The primary result of this study was that the increase in blood lactate concentration 
due to exercise combined with EMS could be explained, to some extent, by the sLT 
changes, which can be measured noninvasively. Previous studies have reported that ex-
ercise combined with EMS leads to an increase in blood lactate concentration [9–11]. The 
mechanism of increased blood lactate concentration is considered to be due to the recruit-
ment of high-threshold motor units and muscle fibers by the additional use of EMS [29–
32]. Therefore, to accurately assess the load imposed on the skeletal muscle by exercise 
combined with EMS, it was necessary to frequently measure lactate concentration, which 
is considered to directly reflect an increase in metabolic rate and glycolytic carbon flow in 
the skeletal muscles [33]. Additionally, as lactate is also considered a signal molecule that 
induces mitochondrial neogenesis in skeletal muscle cells [14], it is beneficial to determine 
the EMS loads that increases blood lactate concentration in each individual. However, 
measuring the blood lactate concentration was not feasible because it required blood sam-
pling. Thus, we focused on the lactate contained in sweat. Sweat lactate measurement has 
the potential to compensate for the disadvantages of conventional evaluation methods, as 
it can be measured noninvasively and easily, and this could be demonstrated through 
exercise combined with EMS. The sweat lactate device that we used is capable of measur-
ing sweat lactate continuously and over a long period of time by adjusting the thickness 
and composition of the topcoat applied to the upper layer of lactate oxidase on the sensor 
chip [27]. Therefore, it is able to monitor lactate level changes without deactivation of the 
enzyme in a single measurement. Our results suggest that this device may be applied in 
the future for setting EMS loads and/or determining the effectiveness of exercise in vari-
ous training environments, such as gyms, outdoors, and at home. 
As for sweat lactate, it reportedly does not reflect the blood lactate levels during ex-
ercise [34,35]. While lactate is produced in sweat reflecting exercise intensity, it is influ-
enced by the body’s production of lactate, the rate of sweating, and metabolic kinetics in 
the sweat glands [34,36]. On the other hand, treating sweat lactate as an elevated point 
during incremental load exercise has been verified in a previous report to be consistent 
with LT obtained from blood [27]. One possible reason for this measurement consistency 
is that increased lactate production from the muscle cells reflecting LT may induce a sim-
ultaneous increase in sweat lactate values through changes in autonomic balance, 
Figure 5. Relationship between the change in blood lactate concentration at the end of exercise and
the change in sweat lactate threshold (n = 20). The amount of change is calculated as the value of the
EMS condition minus the value of the CR condition. EMS, electrical muscle stimulation; CR, without
EMS stimulation.
4. Discussion
The primary result of this study was that the increase in blood lactate concentration
due to exercise combined with EMS could be explained, to some extent, by the sLT changes,
which can be measured noninvasively. Previous studies have reported that exercise com-
bined with EMS leads to an increase in blood lactate concentration [9–11]. The mechanism
of increased blood lactate concentration is considered to be due to the recruitment of high-
threshold motor units and muscle ﬁbers by the additional use of EMS [29–32]. Therefore,
to accurately assess the load imposed on the skeletal muscle by exercise combined with
EMS, it was necessary to frequently measure lactate concentration, which is considered
to directly reﬂect an increase in metabolic rate and glycolytic carbon ﬂow in the skeletal
muscles [33]. Additionally, as lactate is also considered a signal molecule that induces
mitochondrial neogenesis in skeletal muscle cells [14], it is beneﬁcial to determine the EMS
loads that increases blood lactate concentration in each individual. However, measuring
the blood lactate concentration was not feasible because it required blood sampling. Thus,
we focused on the lactate contained in sweat. Sweat lactate measurement has the poten-
tial to compensate for the disadvantages of conventional evaluation methods, as it can
be measured noninvasively and easily, and this could be demonstrated through exercise
combined with EMS. The sweat lactate device that we used is capable of measuring sweat
lactate continuously and over a long period of time by adjusting the thickness and compo-
sition of the topcoat applied to the upper layer of lactate oxidase on the sensor chip [27].
Therefore, it is able to monitor lactate level changes without deactivation of the enzyme in
a single measurement. Our results suggest that this device may be applied in the future
for setting EMS loads and/or determining the effectiveness of exercise in various training
environments, such as gyms, outdoors, and at home.
As for sweat lactate, it reportedly does not reﬂect the blood lactate levels during exer-
cise [34,35]. While lactate is produced in sweat reﬂecting exercise intensity, it is inﬂuenced
by the body’s production of lactate, the rate of sweating, and metabolic kinetics in the
sweat glands [34,36]. On the other hand, treating sweat lactate as an elevated point during
incremental load exercise has been veriﬁed in a previous report to be consistent with LT
obtained from blood [27]. One possible reason for this measurement consistency is that
increased lactate production from the muscle cells reﬂecting LT may induce a simultaneous
increase in sweat lactate values through changes in autonomic balance, hormones, acid-base
equilibrium, and metabolic dynamics [37,38]. Although the exercise protocol used in the
Sensors 2022, 22, 9585
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current study was a constant load rather than an incremental load, because of the load
above AT (VT125%), the lactate discharged from the sweat glands is thought to strongly
reﬂect anaerobic metabolism by the skeletal muscle, in addition to sweat gland metabolism.
In such a load setting, blood and sweat lactate concentrations increase in the CR condi-
tion itself, which would likely increase further when combined with EMS. In our results
for the single regression analysis, R2 was 0.2726, and in terms of correlation coefﬁcient,
r = −0.52. Therefore, our results showed a moderate association between the increase in
blood lactate at 20 min (or the end of exercise) due to the addition of EMS and the time
change to the point of sLT, and the amount of change in the blood lactate concentration
between conditions could be explained by the amount of change in the point of sLT. More
recently, there have been reports on the development of lactate biosensors that are not
affected by sweat secretion rate [39] and on the development of systems that combine
colorimetric analysis with deep learning to detect sweat lactate [40]. These techniques may
contribute to more accurate sweat lactate measurement during exercise. Moreover, the
results of this study suggest that noninvasive skeletal muscle metabolic assessment, which
previously required blood sampling, may be possible with sweat lactate.
Our results showed that there was no difference in the heart rate between the two con-
ditions. A previous study reported a difference between the conditions with and without
EMS at 80% VT loading [9], which was inconsistent with the results of this study. One pos-
sible reason for the inconsistency in the results could be the difference in the exercise load
intensity. Watanabe et al. examined the effects of different voluntary exercise intensities
(50%, 75%, 100%, and 125% of VT) on metabolic responses to exercise combined with EMS
and reported that the increment in oxygen consumption at 125% of VT was signiﬁcantly
lower than those at lower exercise intensities [11], suggesting that the additional recruit-
ments of motor units associated with EMS would be attenuated during high-intensity
voluntary exercise, especially over the AT. Contrarily, EMS can induce a greater reliance on
anaerobic glycolysis for energy production, along with phosphocreatine degradation and
lactate formation [41–44]. In this study, the blood lactate concentration was also increased
during exercise combined with EMS. Therefore, the constant load exercise combined with
EMS at 125% of VT may have further increased the glycolytic metabolism, through large
and fatigable fast-twitch motor units with glycolytic ﬁbers. Although future investigations
should be conducted to include exercise intensities of 80% VT and 100% VT, as in previous
studies, there may be a limited increase in heart rate with the addition of EMS under
exercise intensities above AT, in which lactic can accumulate.
This study has several limitations. First, all 22 study participants were university
students and male, suggesting a population bias. Therefore, future evaluations including
participants with different characteristics, such as age, sex, and exercise capacity, would
allow for a wider interpretation and application of the results. Second, it was difﬁcult to
measure the heart rate using an electrocardiogram at the chest due to wearing a pair of
upper and lower full-body suits. Therefore, measurements were taken from the peripheral
wrist with a Fitbit instead. Thus, it may be necessary to consider the inﬂuence of mea-
surement uncertainty [45,46] as a reason why there was no difference between the two
conditions with respect to the heart rate. Third, the EMS load intensity was set based on the
subjectivity of everyone; thus, the stimulus intensity differed among participants. Fourth,
we cannot eliminate the possibility that the participants were not given any control, such as
fasting or prohibiting exercise on the previous day, which may have affected the pattern of
blood lactate level changes. Therefore, it is considered that such controls are also necessary
to conduct more precise experiments.
5. Conclusions
Constant load pedaling exercise combined with EMS resulted in an early increase
in sweat lactate levels, which could explain, to some extent, the increase in blood lactate
concentrations. Since sweat lactate measurement is noninvasive, continuous, and easy to
perform, it may be expected to be used as an alternative to blood lactate measurement
Sensors 2022, 22, 9585
9 of 11
for monitoring metabolism during exercise combined with EMS and for determining its
effectiveness in the future.
Author Contributions: T.S., H.O., D.N. and Y.K. conceived and designed the research; T.S., H.O.,
K.I., J.N., H.F., S.H. and Y.M. conducted the experiments and analyzed the data; T.S. drafted the
manuscript and prepared the tables/ﬁgures; all the authors edited and revised the manuscript; M.N.
contributed to the supervision of the research project; D.N. and T.N. fulﬁlled the role of project
administration and funding acquisition. All authors have read and agreed to the published version
of the manuscript.
Funding: This research was funded by KGRI/loT Healthcare Research Consortium (Grant number
02-066-0008).
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki and ethical guidelines for medical and health research involving human participants and
was approved by the Institutional Review Board of our institution (approval no. 20190357).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the
study. Written informed consent has been obtained from the subjects to publish this paper.
Data Availability Statement: The data that support the ﬁndings of this study are available from the
corresponding author upon reasonable request.
Acknowledgments: We thank Yoshikazu Kikuchi for his assistance with data collection.
Conﬂicts of Interest: Daisuke Nakashima is the president of Grace Imaging Inc. and holds shares in
this company. This company has no involvement in this research. The other authors declare that they
have no known competing ﬁnancial interests or personal relationships that could have appeared to
inﬂuence the work reported in this paper.
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Constant Load Pedaling Exercise Combined with Electrical Muscle Stimulation Leads to an Early Increase in Sweat Lactate Levels.
Sawada, Tomonori,Okawara, Hiroki,Nakashima, Daisuke,Ikeda, Kaito,Nagahara, Joji,Fujitsuka, Haruki,Hoshino, Sosuke,Maeda, Yuta,Katsumata, Yoshinori,Nakamura, Masaya,Nagura, Takeo