Effects of Whole-Body Electromyostimulation on Metabolic Syndrome in Adults at Moderate-to-High Cardiometabolic Risk—A Systematic Review and Meta-Analysis

Abstract

In the present work, we aimed to determine the effect of whole-body electromyostimulation (WB-EMS) on metabolic syndrome (MetS) as a cluster of cardiometabolic risk factors in people at moderate-to-high cardiometabolic risk. The present meta-analysis is based on a systematic literature search of a recent evidence map, which searched five electronic databases, two registers, and Google Scholar, according to PRISMA, until 31 March 2023. Controlled trials comprising adult cohorts with central obesity that compared the effect of WB-EMS versus controls using a continuous score representing MetS were included. We applied a random-effects meta-analysis and used the inverse heterogeneity model to analyze the data of the five eligible trials identified by our search. Outcome measures were standardized mean differences (SMDs) with 95% confidence intervals (95%-CIs). The risk of bias was determined using the PEDro-Score. In summary, we identified five eligible articles containing 117 participants in the WB-EMS group and 117 participants in the control group. We observed a small effect (SMD: −0.30; 95%-CI: −0.04 to −0.56) in favor of the WB-EMS intervention. The heterogeneity between the trials was very low (I2: 0%); further evidence for risks of small study/publication bias was minimal. The methodologic quality of these studies can be classified as moderate to high. In summary, the present work provides evidence of the favorable effect of WB-EMS on cardiometabolic risk in adults at moderate–high cardiometabolic risk. Considering the time effectiveness of WB-EMS, along with its safety and attractiveness, as indicated by the five studies, WB-EMS can be regarded as a feasible training option for people at cardiometabolic risk.

Full text

Citation: Guretzki, E.; Kohl, M.; von
Stengel, S.; Uder, M.; Kemmler, W.
Effects of Whole-Body
Electromyostimulation on Metabolic
Syndrome in Adults at
Moderate-to-High Cardiometabolic
Risk—A Systematic Review and
Meta-Analysis. Sensors 2024,24, 6788.
https://doi.org/10.3390/s24216788
Academic Editor: Giovanni Saggio
Received: 6 August 2024
Revised: 2 October 2024
Accepted: 17 October 2024
Published: 22 October 2024
Copyright: © 2024 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
sensors
Systematic Review
Effects of Whole-Body Electromyostimulation on Metabolic
Syndrome in Adults at Moderate-to-High Cardiometabolic
Risk—A Systematic Review and Meta-Analysis
Ellen Guretzki 1, Matthias Kohl 2, Simon von Stengel 1, Michael Uder 1and Wolfgang Kemmler 1,3,*
1Institute of Radiology, University Hospital Erlangen, Henkestrasse 91, 91052 Erlangen, Germany;
e.guretzki@htp-tel.de (E.G.); simon.von.stengel@fau.de (S.v.S.); michael.uder@uk-erlangen.de (M.U.)
2Department of Medical and Life Sciences, University of Furtwangen, 78056 Schwenningen, Germany;
matthias.kohl@hfu.eu
3
Institute of Medical Physics, Friedrich-Alexander-University of Erlangen-Nürnberg, 91052 Erlangen, Germany
*Correspondence: wolfgang.kemmler@fau.de; Tel.: +49-09131-8523999; Fax: +49-09131-8522824
Abstract: In the present work, we aimed to determine the effect of whole-body electromyostimulation
(WB-EMS) on metabolic syndrome (MetS) as a cluster of cardiometabolic risk factors in people at
moderate-to-high cardiometabolic risk. The present meta-analysis is based on a systematic literature
search of a recent evidence map, which searched five electronic databases, two registers, and Google
Scholar, according to PRISMA, until 31 March 2023. Controlled trials comprising adult cohorts
with central obesity that compared the effect of WB-EMS versus controls using a continuous score
representing MetS were included. We applied a random-effects meta-analysis and used the inverse
heterogeneity model to analyze the data of the five eligible trials identified by our search. Outcome
measures were standardized mean differences (SMDs) with 95% confidence intervals (95%-CIs). The
risk of bias was determined using the PEDro-Score. In summary, we identified five eligible articles
containing 117 participants in the WB-EMS group and 117 participants in the control group. We
observed a small effect (SMD:
−
0.30; 95%-CI:
−
0.04 to
−
0.56) in favor of the WB-EMS intervention.
The heterogeneity between the trials was very low (I
2
: 0%); further evidence for risks of small
study/publication bias was minimal. The methodologic quality of these studies can be classified
as moderate to high. In summary, the present work provides evidence of the favorable effect of
WB-EMS on cardiometabolic risk in adults at moderate–high cardiometabolic risk. Considering the
time effectiveness of WB-EMS, along with its safety and attractiveness, as indicated by the five studies,
WB-EMS can be regarded as a feasible training option for people at cardiometabolic risk.
Keywords: whole-body electromyostimulation; electrostimulation; intervention; cardiometabolic
risk; metabolic syndrome; obesity
1. Introduction
Whole-body electrostimulation (WB-EMS) is an increasingly popular innovative train-
ing technology. With its ability to stimulate all the main muscle groups simultaneously, but
with a dedicated intensity per electrode, WB-EMS can be considered a time-effective, jointly
friendly, and safe training method [
1
,
2
]. This might qualify this novel training technology as
a promising tool to address people with poor health, limited time resources, and/or a low
affinity to conventional exercise. Because of the resistance-type character of WB-EMS [
3
],
most studies of sedentary or at least non-athletic cohorts addressed outcomes related to
musculoskeletal conditions or diseases [
4
]. However, some studies provided considerable
evidence of the positive effects of a standard WB-EMS application [
3
] on parameters related
to cardiovascular health [
5
–
8
], e.g., in people with diabetes mellitus or chronic heart failure.
Sensors 2024,24, 6788. https://doi.org/10.3390/s24216788 https://www.mdpi.com/journal/sensors

Sensors 2024,24, 6788 2 of 13
Metabolic syndrome (MetS) is a cluster of conditions that increase the risk of heart
disease, stroke, type 2 diabetes, and other serious health problems [
9
]. The components
of MetS include (central) obesity, high blood pressure, high levels of triglycerides, low
levels of HDL-C, and insulin resistance [
9
]. Of note, MetS is necessarily dichotomous for
clinical purposes, wherein if at least three of five MetS criteria apply, MetS is present
[9–11]
.
However, to reliably determine the overall effect of an intervention, a continuous MetS-
(Z)-Score is more accurate and appropriate for scientific research [
12
]. Among others,
Johnson et al. [
12
] suggest calculating a Z-score using individual subject data, MetS cut-off
criteria, and standard deviations (denominators of each factor in the formula) of the given
(here, female) cohort at baseline (e.g., ([50
−
HDL-C]/SD
−
HDL-C) + ([Triglycerides
−
150]/SD
−
TGs) + ([fasting glucose
−
100]/SD
−
FPG) + ([waist circumference
−
88]/SD
−
WC) + ([mean arterial blood pressure
−
100]/SD
−
MAP)). Johnson et al. [
12
] applied the
National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation,
And Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). The cut-
offs are waist circumference: 102 cm (men) or 88 cm (women), HDL-C: 40 mg/dL (men)
or 50 mg/dL (women), triglycerides: 150 mg/dL, fasting glucose: 100 mg/dL, and mean
arterial blood pressure (MAP): 100 mmHg.
In the present mini-review and meta-analysis, we aimed to determine the effects
of WB-EMS on the MetS-Score. We hypothesized that WB-EMS interventions generated
significant effects on the MetS-Score compared with controls in adults at increased car-
diometabolic risk.
2. Methods
2.1. Information Sources and Search Strategy
A literature review was performed to identify the most relevant quantitative and
qualitative studies following the Preferred Reporting Items for Systematic Reviews and
Meta-Analyses (PRISMA) guidelines.
The present meta-analysis is based on the large systematic literature search and evi-
dence map provided by Beier et al. [
1
], which was slightly adapted for the present topic.
Briefly, publications in five electronic databases (Medline [PubMed], the Cochrane Central
Register of Controlled Trials [CENTRAL], the Cumulative Index to Nursing and Allied
Health [CINAHL via Ebsco Host], SPORTDiscus (via Ebsco Host), and the Physiotherapy
Evidence Database [PEDro]) and two study registers (Clinical trial.gov and the WHO’s
International Clinical Trials Registry Platform [ICTRP]) from their initiation to 6 March 2023
were searched without language restrictions. Further, we hand-searched Google Scholar
to 6 March 2023. For more detailed information, the reader is referred to the systematic
literature search and evidence map created by Beier et al. [
1
]. In order to ensure that
all eligible studies were identified and included in the present analysis, we updated our
search (28 September 2024); however, we restricted our search to the electronic databases
listed above.
2.2. Selection Process
Titles, abstracts, and full texts were independently screened by three reviewers (MB,
EG, WK) according to the pre-specified eligibility criteria listed below.
2.3. Eligibility Criteria
The eligibility criteria applied to the present systematic review were categorized
according to the PICOS scheme.
Population: Non-athletic adult cohorts with central (abdominal) obesity according to
the cut-off values (men: 94 cm, female: 80 cm) suggested by the International Diabetes
Federation (IDF) for the definition of MetS were included.
Intervention: We only considered studies that applied whole-body electromyostimula-
tion (WB-EMS) according to the current definition [2].

Sensors 2024,24, 6788 3 of 13
Comparators: All types of control groups, be they physically inactive or active, were
considered. Studies with an isolated WB-EMS intervention arm without a control group
were excluded. In cases of more than one control group [
13
], the non-exercise control group
was included in the analysis. In cases of superimposed interventions [
14
], we compared
the mixed WB-EMS/exercise group with the isolated exercise group.
Outcomes: For the present review, we included eligible studies that reported data on
the metabolic syndrome score specified as a primary or secondary outcome. All kinds of
continuous scores representing MetS were accepted.
Study design: We included only randomized and non-randomized controlled trials.
Review articles, case reports, editorials, conference abstracts, letters, or theses (doctoral,
master, bachelor) were not considered.
2.4. Data Items and the Data Collection Process
A Microsoft Excel table modified for the present research topic was used to extract rel-
evant data from the included studies. Briefly, we extracted publication, study, intervention
characteristics, and outcomes. We further recorded whether the MetS-Score was defined (or
at least considered) as a primary/main or secondary/subordinate study outcome. Adverse
effects related to the WB-EMS intervention were also recorded. Adverse effects were de-
fined as any untoward medical occurrence, unintended disease, or injury or any untoward
clinical sign, including an abnormal laboratory finding related to the WB-EMS application.
2.5. Risk of Bias Assessment
Risk of bias was classified by WK and SvS using the Physiotherapy Evidence Database
(PEDro) Scale Risk of Bias Tool [
15
] specifically dedicated to physiotherapy/exercise studies
and thus appropriate for rating the methodologic quality of the WB-EMS intervention.
2.6. Data Synthesis
Missing standard deviations (SDs) were calculated using the method detailed in
the recently published comprehensive meta-analysis by Shojaa et al. [
16
]. If the studies
presented a confidence interval (CI) or standard errors (SEs), they were converted to
standard deviation (SD) with standardized formulas [
17
]. Because of the low number of
eligible studies, no subgroup analyses were conducted.
2.7. Statistical Analysis
A random-effects meta-analysis was computed using the metafor package [
18
] that is
included in the statistical software R [
19
]. The effect size was presented as standardized
mean differences (SMDs) with 95% confidence intervals (95%-CIs). We applied the het-
erogeneity (IVhet) model proposed by Doi et al. [
20
]. Heterogeneity between the studies
was checked using I
2
statistics. In addition to funnel plots, regression tests, and rank corre-
lation effect estimates and their standard errors using the t-test and Kendall’s
τ
-statistic
for possible small study/publication BIAS, we performed a trim-and-fill analysis using
the L0 estimator. In addition, we used DOI plots, the Luis Furuya–Kanamori index (LFK
index) [
21
], regression, and rank correlation tests to check for asymmetry. Sensitivity anal-
yses were applied to determine whether the overall result of the analysis was robust to
the use of the imputed correlation coefficient (minimum, mean, or maximum). Further, a
sensitivity analysis was applied to determine the potentially confounding effect of a trial
with a training control group [
22
]. SMD values of >0.2, >0.5, and >0.8 were interpreted as
small, medium, and large effects. A p-value < 0.05 was used as the significance level for
all tests.
3. Results
3.1. Study Selection
Figure 1(flowchart) illustrates the process of the systematic search conducted in this
study. After removing 577 duplicates, 637 articles were screened based on their titles

Sensors 2024,24, 6788 4 of 13
and abstracts. The full texts of 225 potentially relevant articles were screened and, finally,
a total of five eligible studies were included [
13
,
14
,
22
–
24
]. After removing duplicates
(PubMed:
n = 78,
CENTRAL: n = 50, CINAHL: n = 18, SPORTDiscus: n = 27, PEDro: n = 0)
the updated search to 28 September 2024 identified 80 articles, which were screened for
eligibility. However, no further study was included.
Sensors 2024, 24, x FOR PEER REVIEW 4 of 15
3.1. Study Selection
Figure 1 (flowchart) illustrates the process of the systematic search conducted in this
study. After removing 577 duplicates, 637 articles were screened based on their titles and
abstracts. The full texts of 225 potentially relevant articles were screened and, finally, a
total of five eligible studies were included [13,14,22–24]. After removing duplicates
(PubMed: n = 78, CENTRAL: n = 50, CINAHL: n = 18, SPORTDiscus: n = 27, PEDro: n = 0)
the updated search to 28 September 2024 identified 80 articles, which were screened for
eligibility. However, no further study was included.
Figure 1. Flowchart of the present literature search according to PRISMA [25].
3.2. Study, Participant, and Exercise Characteristics
The five studies comprised five WB-EMS groups (GC) that were compared with their
five most suitable control groups (Table 1). All the studies were randomized controlled
trials with parallel group designs that applied balanced randomization. The pooled
number of participants (baseline) was n = 117 in the WB-EMS group and n = 117 in the
control group. Two trials included only women [23,24], one study focused on men [22],
and two studies included mixed cohorts [13,14]. The mean age of the cohorts ranged
between 43 ± 6 years [22] and 77 ± 3 years [24] (Table 1). Two studies focused on people
with MetS [13,23] according to the definition of the International Diabetes Federation (IDF,
[9]). One study addressed older women with sarcopenic obesity [24], and two studies
included predominately middle-aged participants with overweight and obesity [14,22].
The studies varied considerably with respect to WB-EMS application (Table 2). Most
importantly, one study [14] applied superimposed WB-EMS by adding WB-EMS to high-
intensity (aerobic and resistance type) interval training (HIIT). All of the other studies
focused on WB-EMS with low-intensity voluntary exercises/movements during the WB-
EMS impulse phase. Of importance, two studies implemented (conventional) exercise
control groups [14,22] (Table 1). While Amaro-Gahete et al. [14] compared WB-EMS and
HIIT versus HIIT only, Kemmler et al. [22] compared WB-EMS versus single-set high-
intensity resistance exercise (HIT-RT) (Table 1). The length of the interventions varied
between 12 and 26 weeks [24], and the average WB-EMS volume ranged between 20 min
[24] and 52.5 min/week [14]. Impulse intensity as prescribed by the rate of perceived exertion
(RPE) varied from 6 (hard to hard+) [24] to 9 (very, very hard) [14] on the Borg CR10 scale
[26].
Figure 1. Flowchart of the present literature search according to PRISMA [25].
3.2. Study, Participant, and Exercise Characteristics
The five studies comprised five WB-EMS groups (GC) that were compared with their
five most suitable control groups (Table 1). All the studies were randomized controlled
trials with parallel group designs that applied balanced randomization. The pooled number
of participants (baseline) was n = 117 in the WB-EMS group and n = 117 in the control
group. Two trials included only women [
23
,
24
], one study focused on men [
22
], and
two studies included mixed cohorts [
13
,
14
]. The mean age of the cohorts ranged between
43
±
6 years [
22
] and 77
±
3 years [
24
] (Table 1). Two studies focused on people with
MetS [
13
,
23
] according to the definition of the International Diabetes Federation (IDF [
9
]).
One study addressed older women with sarcopenic obesity [
24
], and two studies included
predominately middle-aged participants with overweight and obesity [14,22].
The studies varied considerably with respect to WB-EMS application (Table 2). Most
importantly, one study [
14
] applied superimposed WB-EMS by adding WB-EMS to high-
intensity (aerobic and resistance type) interval training (HIIT). All of the other studies fo-
cused on WB-EMS with low-intensity voluntary exercises/movements during the WB-EMS
impulse phase. Of importance, two studies implemented (conventional) exercise control
groups [
14
,
22
] (Table 1). While Amaro-Gahete et al. [
14
] compared WB-EMS and HIIT
versus HIIT only, Kemmler et al. [
22
] compared WB-EMS versus single-set high-intensity
resistance exercise (HIT-RT) (Table 1). The length of the interventions varied between 12
and 26 weeks [
24
], and the average WB-EMS volume ranged between 20 min [
24
] and
52.5 min/week [
14
]. Impulse intensity as prescribed by the rate of perceived exertion (RPE)
varied from 6 (hard to hard+) [24] to 9 (very, very hard) [14] on the Borg CR10 scale [26].

Sensors 2024,24, 6788 5 of 13
Table 1. Study, participant, and diet characteristics of the five trials included in the present systematic review and meta-analysis.
First Author, Year Study
Design
Sample
Size/Group [n]
Gender
(Men/Women) Age [Years]
Body Mass
Index
[kg/m2]
Waist Circum-
Ference (cm)
Dietary
Intervention/Energy
Restriction
Cardio- Vascular
Health
Status
1Amaro-Gahete
et al. 2019 [14]RCT WB-EMS: 19
CG: 18
WB-EMS:10/9
CG: 9/9
WB-EMS: 53.5 ±5.3
CG: 53.1 ±5.6
28.6 ±4.6
26.4 ±3.2
99.3 ±13.7
97.5 ±10.9 no MR
MR
2Kemmler et al.
2016 [22]RCT WB-EMS: 23
CG: 23 Only men WB-EMS: 43.7 ±6.1
CG: 41.9 ±6.4
28.5 ±4.1
26.9 ±3.3
102.6 ±9.4
100.5 ±9.6 no MR
3Reljic et al.
2020 [23]RCT WB-EMS: 15
CG: 14 Only women 56.0 ±10.9
Details n.g.
36.1 ±4.5
37.4 ±4.8
107.2 ±7.3
109.6 ±8.6
−500 kcal/d + Protein
≥1 g/d
−500 kcal/d+ Protein
≥1 g/d
HR
4Reljic et al.
2022 [13]RCT WB-EMS: 26
CG: 26
WB-EMS: 8/18
CG: 8/18
WB-EMS: 52.7 ±12.5
CG: 49.0 ±15.1
37.2 ±4.0
38.0 ±6.3
114 ±10
109 ±11
−500 kcal/d/
−500 kcal/d HR
5Wittmann et al.
2016 [24]RCT WB-EMS: 25
CG: 25 Only women WB-EMS: 77.3 ±4.9
CG: 77.4 ±4.9
24.2 ±2.0
23.9 ±1.4
93.5 ±4.8
91.4 ±6.4 no MR
AE: aerobic training; MR: moderate cardiovascular risk (e.g., central obesity); HR: high cardiovascular risk (e.g., prevalent MetS), m: men; n.g. not given; RT: resistance training;
w: women.

Sensors 2024,24, 6788 6 of 13
Table 2. Exercise characteristics of the five trials included in the present systematic review and meta-analysis.
First Author, Year
Superimposed WB-EMS
Intervention Length [Weeks]
Sessions/Week [n]
Length of Session [min]
Impulse Frequency [Hz]
Impulse Intensity
Duty Cycle [%]
Impulse-
Rest Phase
Control Physical Intervention
Loss to Follow-Up [%]
Attendance [%]
Adverse Effects
1 Amaro-Gahete et al. 2019 [14]HIIT AE + RT
and WB-EMS 12 2 20, 33 10–20,
35–75 moderate–high AE: 99
RT: 50–63
HIIT
AE + RT
HIIT + WB-EMS: 17
HIIT: 30
HIIT+WB-EMS: 99
HIIT: 99 no
2 Kemmler et al. 2016 [22] no 16 1.5 20 85 high 60
6–4 s HIT-RT WB-EMS: 9
HIT-RT: 13
WB-EMS: 90 ±11
HIT-RT: 93 ±7no
3 Reljic et al. 2020 [23] no 12 2 20 85 moderate 60
6–4 s none 25 93 ±8 no
4 Reljic et al. 2022 [13] no 12 2 20 85 moderate 60
6–4 s none 23 93 ±8 no
5 Wittmann et al. [24] no 26 1 20 85 low–moderate 50
4–4 s none 4 89 ±6 no
AE: aerobic training; HIT-RT: single-set, high-intensity resistance exercise training, HIIT: high-intensity interval training, MR: moderate cardiovascular risk (e.g., central obesity); HR:
high cardiovascular risk (e.g., prevalent MetS), m: men; RT: resistance training; w: women.

Sensors 2024,24, 6788 7 of 13
Loss to follow-up in the WB-EMS groups ranged between 4% for 26 weeks [
24
] and
25% for 12 weeks of intervention [
13
]. The withdrawal rate, defined as voluntary drop-out
due to personal reasons (e.g., loss of interest, lack of time, aversion to or discomfort with
the intervention) and considered an indicator of attractiveness, averaged between 4% and
13%. The attendance rate to the training sessions in the WB-EMS and active control groups
averaged
≥
90%. None of the studies reported any adverse effects related to the WB-EMS
or exercise interventions.
Energy-restrictive diets were applied in two of the five studies [
13
,
23
]. Reljic et al.
reported a net energy reduction of
−
502 (WB-EMS) vs.
−
439 kcal/d (CG) [
13
] and
−
336
(WB-EMS) versus
−
588 kcal (CG) [
23
], in their groups. However, the authors did not list
significant group effects. Three studies monitored dietary habits in their WB-EMS and
CG-groups [
14
,
22
,
24
,
27
]. While Amaro-Gahete et al. [
14
] listed marginal changes in energy
intake in HIIT and HIIT + WB-EMS (36 vs. 11 kcal/d), Kemmler et al. [
22
] observed a
significant difference (2.9
±
9.9% vs. 7.8
±
10.6%, p= 0.010) between the groups with higher
intake in the WB-EMS-group. Lastly, Wittmann et al. [
24
] reported significant reductions
(
−
139 kcal/d, p= 0.019) only for the WB-EMS group, whilst significant differences to the
CG were not reported.
3.3. Methodologic Quality of the Trials
Following PEDro and applying the classification of Ribeiro de Avila et al. [
28
], the
methodologic quality of the studies can be classified as moderate (PEDro: 5–7) to high
(PEDro:
≥
8) (Table 3). In particular, aspects related to allocation concealment or blinding
prevented better ratings.
Table 3. Assessment of risk of bias for the included studies.
First Author, Year
Eligibility Criteria
Random Allocation
Allocation Concealment
Inter Group Homogeneity
Blinding Subjects
Blinding Personnel
Blinding Assessors
Participation ≥85% Allocation
Intention to Treat Analysis a
Between Group Comparison
Measure of Variability
Total Score
Amaro-Gahete et al. 2019 [14]Y11100001116
Kemmler et al. 2016 [22] Y10100111117
Reljic et al. 2020 [23] Y11100100116
Reljic et al. 2022 [13] Y11100100116
Wittmann et al. 2016 [24] Y11100111118
a
A point is awarded not only for the intention to treat analysis but also when “all subjects for whom outcome
measures were available received the treatment or control condition as allocated”. Bold: Total PEDro-score.
3.4. Study Outcomes
All trials [
13
,
14
,
22
–
24
] treated the MetS-Z-score (
. . .
or the “cardiometabolic risk pro-
file”) as the primary or main study outcome. However, two [
13
,
23
] studies applied the MetS-
Syndrome definition specified by the National Cholesterol Education Program (NCEP)
Adult Treatment Panel III [
10
], and three other studies applied the IDF criteria and cut-off
values for the metabolic syndrome [
14
,
22
,
24
]. Briefly, both definitions used the same cut-off
values for HDL-C (men: 40 mg/dL, women: 50 mg/dL), triglycerides (150 mg/dL), and
fasting glucose (100 mg/dL); however, different values for blood pressure (IDF: diastolic
85 mmHg, systolic: 135 mmHg versus NCEP-ATP III: mean arterial blood pressure (MAP):

Sensors 2024,24, 6788 8 of 13
100 mmHg) and, in particular, waist circumference (IDF: men 94 cm, women: 80 cm versus
NCEP-ATP III: men: 102 cm, women: 88 cm) were used.
As stated, all the studies summarized the five MetS components as a continuous score.
Apart from one study [
14
] that did not provide sufficient information, all the trials calculated
MetS-Z-scores according to the approach suggested by Johnson et al. [
12
]. Applying the
NCEP ATP III cut-off values for a female cohort, the MetS-Z-score was calculated as
follows: MetS-Z-score: ([50
−
HDL-C]/SD
−
HDL-C) + ([Triglycerides
−
150]/SD
−
TGs)
+ ([fasting glucose
−
100]/SD
−
FPG) + ([waist circumference
−
88]/SD
−
WC) + ([mean
arterial blood pressure
−
100]/SD
−
MAP). Amaro-Gahete et al. [
14
] applied quite a similar
approach. Briefly, the authors divided the sum of the five (waist circumference + MAP
+ glucose + triglycerides + HDL-C) standardized scores (value–mean/SD) to calculate a
continuous score.
Relevant for the interpretation of the results, decreases in the MetS-Score(s) always
indicate favorable changes.
3.5. Meta-Analysis Results
Figure 2displays the results of WB-EMS versus control on the MetS-Score. In summary,
we observed a low (SMD:
−
0.33; 95%-CI:
−
0.07 to
−
0.59) but significant (p= 0.013) effect in
favor of the WB-EMS intervention. Heterogeneity between the trials was very low (I
2
: 0%,
Figure 2). In the sensitivity analysis with respect to the imputation of the mean correlation
(see Figure 2), the minimum or maximum correlation revealed roughly comparable effects.
Of note, the two studies that compared WB-EMS with an exercise control group did not
negatively impact the result of the meta-analysis (Figure 2).
Sensors 2024, 24, x FOR PEER REVIEW 8 of 15
mg/dL), and fasting glucose (100 mg/dL); however, different values for blood pressure
(IDF: diastolic 85 mmHg, systolic: 135 mmHg versus NCEP-ATP III: mean arterial blood
pressure (MAP): 100 mmHg) and, in particular, waist circumference (IDF: men 94 cm,
women: 80 cm versus NCEP-ATP III: men: 102 cm, women: 88 cm) were used.
As stated, all the studies summarized the five MetS components as a continuous
score. Apart from one study [14] that did not provide sufficient information, all the trials
calculated MetS-Z-scores according to the approach suggested by Johnson et al. [12]. Ap-
plying the NCEP ATP III cut-off values for a female cohort, the MetS-Z-score was calcu-
lated as follows: MetS-Z-score: ([50 − HDL-C]/SD − HDL-C) + ([Triglycerides − 150]/SD −
TGs) + ([fasting glucose − 100]/SD − FPG) + ([waist circumference − 88]/SD − WC) + ([mean
arterial blood pressure − 100]/SD − MAP). Amaro-Gahete et al. [14] applied quite a similar
approach. Briefly, the authors divided the sum of the five (waist circumference + MAP +
glucose + triglycerides + HDL-C) standardized scores (value–mean/SD) to calculate a con-
tinuous score.
Relevant for the interpretation of the results, decreases in the MetS-Score(s) always
indicate favorable changes.
3.5. Meta-Analysis Results
Figure 2 displays the results of WB-EMS versus control on the MetS-Score. In sum-
mary, we observed a low (SMD: −0.33; 95%-CI: −0.07 to −0.59) but significant (p = 0.013)
effect in favor of the WB-EMS intervention. Heterogeneity between the trials was very low
(I2: 0%, Figure 2). In the sensitivity analysis with respect to the imputation of the mean
correlation (see Figure 2), the minimum or maximum correlation revealed roughly com-
parable effects. Of note, the two studies that compared WB-EMS with an exercise control
group did not negatively impact the result of the meta-analysis (Figure 2).
Figure 2. Forest plot showing the meta-analysis results of all the included trials [13,14,22–24] for
WB-EMS effects on the metabolic syndrome score. Data are shown as pooled standard mean differ-
ences (SMDs) with 95%-CIs for changes after WB-EMS (EG) versus control (CG).
Excluding the trial by Kemmler et al. [22], which compared WB-EMS with HIT-RT,
slightly reduced the effect of WB-EMS on the MetS-Z-score (SMD: 0.29, 95%-CI: −0.00 to
−0.58), but it was still significant (p = 0.049).
The IV-Het funnel plot with the trim-and-fill analysis (Figure 3) imputed one study
at the lower right side, thus indicating a publication/small study bias. The LFK Index (1.61)
indicated minimal asymmetry; in parallel, the regression (p = 0.526) and rank correlation
test (p = 0.817) did not indicate significant asymmetry.
Figure 2. Forest plot showing the meta-analysis results of all the included trials [
13
,
14
,
22
–
24
] for WB-
EMS effects on the metabolic syndrome score. Data are shown as pooled standard mean differences
(SMDs) with 95%-CIs for changes after WB-EMS (EG) versus control (CG).
Excluding the trial by Kemmler et al. [
22
], which compared WB-EMS with HIT-RT,
slightly reduced the effect of WB-EMS on the MetS-Z-score (SMD: 0.29, 95%-CI:
−
0.00 to
−0.58), but it was still significant (p= 0.049).
The IV-Het funnel plot with the trim-and-fill analysis (Figure 3) imputed one study at
the lower right side, thus indicating a publication/small study bias. The LFK Index (1.61)
indicated minimal asymmetry; in parallel, the regression (p= 0.526) and rank correlation
test (p= 0.817) did not indicate significant asymmetry.

Sensors 2024,24, 6788 9 of 13
Sensors 2024, 24, x FOR PEER REVIEW 9 of 15
Figure 3. IV-Het funnel plot with trim-and-fill for WB-EMS effects on the metabolic syndrome score.
Table 4 lists changes in the components of the MetS-Z-score in detail. In summary,
only MAP revealed consistently more favorable results in the WB-EMS group compared
with the control group, although only one study stated significant differences [24]. How-
ever, only three of the five studies applied statistical tests to address this issue.
Figure 3. IV-Het funnel plot with trim-and-fill for WB-EMS effects on the metabolic syndrome score.
Table 4lists changes in the components of the MetS-Z-score in detail. In summary, only
MAP revealed consistently more favorable results in the WB-EMS group compared with
the control group, although only one study stated significant differences [
24
]. However,
only three of the five studies applied statistical tests to address this issue.
Table 4. Changes in MetS-Score components in the WB-EMS and control groups of the five studies.
Amaro-Gahete et al.
2019 [14]1
Kemmler et al.
2016 [22]
Reljic et al.
2020 [23]2
Reljic et al.
2022 [13]1,2
Wittmann et al.
2016 [24]
∆Waist circumference
WB-EMS (cm) −4.0 ±2.4 −3.4 ±4.5 −2.3 −3.0 −1.4 ±2.1
∆Waist circumference
Control (cm) −4.5 ±2.5 −2.1 ±4.1 −1.0 −2.0 −0.0 ±2.3
∆MAP WB-EMS (mmHg) −5.4 ±3.1 −4.9 ±7.3 −7.0 2.0 −8.8 ±11.0
∆MAP Control (mmHg) −1.6 ±1.8 −3.6 ±5.6 1.0 −1.0 −2.2 ±9.5
∆Triglycerides WB-EMS
(mg/dL) −30 ±41 9.5 ±55.5 −6.0 −15.0 2.8 ±28.5
∆Triglycerides Control
(mg/dL) −15 ±60 −10.1 ±47.9 −30.0 −18.0 9.8 ±39.2
∆HDL-C WB-EMS (mg/dL) 5.1 ±12.9 n.g. 3−1.0 −1.0 −1.3 ±6.35
∆HDL-C Control (mg/dL) 2.2 ±12.8 n.g. 0 −2.0 −4.6 ±6.6
∆Fasting Glucose WB-EMS
(mg/dL) 0.6 ±5.9 −4.3 ±9.0 −2.0 −2.0 −3.0 ±10.3
∆Fasting Glucose Control
(mg/dL) −4.1 ±6.1 1.7 ±8.5 −5.0 −3.0 −3.6 ±7.9
Bold values: significant effects in favor of WB-EM; bold and italic: significant effects in favor of the control group;
1
significant differences between WB-EMS and CG were not calculated;
2
differences between pre- and post-
intervention were not given and therefore calculated;
3
however, a significant effect for the total cholesterol/HDL-C
ratio in favor of the WB-EMS group was not given.
4. Discussion
The present systematic review and meta-analysis, including five randomized con-
trolled trials that considered the MetS-Score as the main outcome, shows a low positive

Sensors 2024,24, 6788 10 of 13
effect (SMD:
−
0.30; 95%-CI:
−
0.04 to
−
0.56) of WB-EMS application on this cardiometabolic
risk cluster in middle-aged to older women and men with increased cardiometabolic risk.
This significant finding is quite impressive since two trials [
14
,
22
] implemented active con-
trol groups with exercise protocols (HIIT and HIT-RT), with high evidence of positive effects
on cardiometabolic risk factors related to MetS [
29
–
31
]. Amaro-Gahete et al. [
14
] compared
combined WB-EMS/HIIT versus isolated HIIT and reported significant positive changes
for the combined group only without any change in HIIT. Of note, the non-training control
group in their study deteriorated significantly; thus, significant effects (compared with the
CG) were reported for HIIT and WB-EMS/HIIT. In parallel, (significantly) unfavorable
changes in the CG with significant effects were also reported for the homeostasis model
assessment index (HOMA) and the quantitative insulin sensitivity check index (QUICKI).
Nevertheless, this significant deterioration in important cardiometabolic biomarkers within
12 weeks in the CG that received no intervention within that period is surprising, particu-
larly since no confounding effects were reported.
Kemmler et al. [
22
] compared MetS-Z-score changes after 16 weeks of WB-EMS versus
a comparable time-effective HIT-RT (i.e., single-set RT with high exercise intensity). The
protocol reported non-significantly (p= 0.096) more favorable results for WB-EMS. In
contrast, after 12 weeks of intervention, Reljic et al. [
13
] reported the opposite effects
after comparing their single-set RT group (not included in the analysis) with WB-EMS.
The longer intervention period and higher exercise intensity in the study by Kemmler
et al. [
22
] may well contribute to this finding. In addition, Reljic et al. [
13
] also reported
significantly more favorable effects after HIIT and multiple-set RT (not included in the
analysis) compared with WB-EMS. However, given the proof-of-principle approach of the
present study, we decided not to compare conventional exercise versus WB-EMS at least
when non-training control groups were available. Since only one study was included, by
directly comparing the effects of WB-EMS versus HIT-RT [
22
,
27
], we are unable to reliably
decide whether DRT or WB-EMS is superior for favorably affecting the MetS-Z-score in
people with moderate to high cardiometabolic risk. However, from a pragmatic point of
view, the issue of superiority might be less relevant since WB-EMS should be considered a
training option predominately suitable for people with limited time resources, low affinity,
or little motivation to exercise conventionally.
In reviewing the physiological mechanisms of MetS changes, the present work was un-
able to clarify which of the underlying parameters of MetS was most sensitive to WB-EMS.
The results of MetS components of the individual trials (Table 4) indicate that only MAP
shows consistently more favorable effects in the WB-EMS group compared with the CG,
while all the other parameters (i.e., waist circumference, resting glucose, triglycerides, HDL-
C) revealed inconsistent effects partially in favor of WB-EMS and partially in favor of the
control. However, apart from the low number of studies, we abstained from sub-analyses
of the five parameters constituting MetS according to IDF [
9
] or NCEP ATP III [
10
] because
of the finding that particular laboratory biomarkers (i.e., FPG, HDL-C, TG) of most studies
were in a normal range. Correspondingly, the clinical relevance of presumably low to mod-
erate positive or negative changes will be difficult to estimate. Nevertheless, in reviewing
the five studies, it was found that waist circumference decreased in all trials. Although the
effects were not significant in each case, the clinical relevance of this aspect is important.
In parallel, MAP significantly decreased in four of the five studies
[13,14,22,24]
, while
all trials reported at least suboptimum average baseline MAP (
102–110 mmHg
). Fasting
glucose declined in all WB-EMS groups; however, because of the widely normal average
baseline values (90 to 104 mg/dL) or/and minor changes, the results on fasting glucose
should be considered clinically less relevant. The same is true for HDL-C with its either
minor positive or minor negative changes (
±
2 mg/dL), a finding consistently observed
by the five studies. In parallel, no study reported significant declines in triglyceride levels
after WB-EMS.
Apart from the limited number of eligible studies and their low to moderate sample
sizes, some other limitations and study particularities should be considered to interpret

Sensors 2024,24, 6788 11 of 13
our findings reliably. (a) First of all, one may criticize that we did not include solely WB-
EMS studies with non-training control groups. While the comparison of WB-EMS&HIIT
versus isolated HIIT (and not non-training control) in the study by Amaro-Gahete et al. [
14
]
is plausible and comprehensive, the inclusion of the study by Kemmler et al. [
22
] that
compared isolated WB-EMS vs. isolated HIT-RT is more debatable. However, we finally
decided to include the study bearing in mind that the comparison with a presumably
effective intervention might dilute the actual effect of WB-EMS in the analysis. For this
reason, we conducted a sensitivity analysis without the study by Kemmler et al. [
22
], which
only slightly reduced the (albeit low) effect of WB-EMS on the MetS-Z-score.
(b) Another minor limitation is that this study is based on the comprehensive results
of a systematic literature search (PRISMA) and evidence map of WB-EMS conducted up to
March 2023. In order to check if eligible articles have been published after this date, we
conducted an additional literature search (up to 28 September 2024) in electronic databases
only. Furthermore, because our approach used the search of a previous comprehensive
literature search, we are unable to fully apply the PRISMA criteria for the present article. In
parallel, this study was not registered. (c) In order to include clinically relevant cohorts,
we focused on cohorts with central, i.e., abdominal obesity. Actually, waist circumfer-
ence (as the indicator of central obesity in all MetS definitions) is a valid determinant
of intra-abdominal/visceral fat tissue accumulation [
32
], considered the key driver of
cardiometabolic risk [
33
]. However, it should be noted that cut-off criteria for waist circum-
ference differ considerably between the definitions decided by the IDF (
≥
80 and
≥94 cm
)
and ATP III (
≥
88 and
≥
102 cm) for women and men, respectively. (d) The studies did
not perform a homogeneous calculation of the MetS-Z-score: two studies each applied
the NCEP ATP III cut-off values [
13
,
23
], and the three others used IDM criteria [
14
,
22
,
24
].
Additionally, while four studies properly applied the approach suggested by Johnson
et al. [
12
], because of a lack of information, we cannot be sure if Amaro-Gehete et al. [
14
]
strictly followed the specifications of Johnson et al. [12].
(e) We applied a random-effects meta-analysis with the inverse heterogeneity model
(IVhet) [
20
], which is less susceptible to the underestimation of statistical error in heteroge-
neous studies. Therefore, the results are more reliable in heterogeneous studies, where the
random effects estimator may lead to coverage probabilities that are well below the desired
nominal level, which means the significance and relevance of the results may be overesti-
mated [
34
]. Considering the low heterogeneity listed in Figure 1(I
2
= 0%), one may argue
that a random effects meta-analysis is not appropriate. However, with only five eligible
trials, we were not in a suitable position to prove heterogeneity statistically. We obtained
an estimated I
2
of 0%, but the confidence interval was very wide (0% to 77%) and thus did
not even exclude “high/considerable heterogeneity”. Correspondingly, we were aware of
higher degrees of heterogeneity and therefore applied a random effects model.
(f) All studies covered cohorts with central obesity, and two studies included people
with MetS [
13
,
23
]. Thus, we think it is justified to generalize our findings to middle-aged
to older people with increased cardiometabolic risk.
Considering the low withdrawal and high attendance rates of the WB-EMS study
arms, WB-EMS can also be classified as an attractive training method. Furthermore, the
dense network of commercial WB-EMS facilities, particularly in Germany [
3
], and its
ongoing distribution worldwide indicate the feasibility and applicability of this novel
training technology.
In summary, the present study suffers from large heterogeneity between the study
protocols with respect to age, gender, training/non-training control groups, length of
the intervention, and weekly WB-EMS training frequency. With respect to the stimula-
tion protocol, all studies applied low-stimulation frequency WB-EMS with intermitted
(predominately 4–6 s of impulse/4 s of impulse break) stimuli; nevertheless, the super-
imposed approach of Amaro-Gahete et al. [
14
] complicates the proper assignment of the
effect and/or dilutes the difference in MetS-Z-score changes compared with a training
control group.

Sensors 2024,24, 6788 12 of 13
Bearing the above in mind, we would like to conclude that we provided at least
low evidence for a favorable effect of WB-EMS on the metabolic syndrome in cohorts at
increased cardiometabolic risk. Apart from its effectiveness, WB-EMS can be considered
a feasible attractive, and safe training option particularly suitable for people unable or
unmotivated to exercise conventionally.
Author Contributions: Conceptualization, W.K., M.K., S.v.S. and M.U.; methodology, W.K. and S.v.S.;
software, M.K.; validation, E.G., W.K., S.v.S. and M.U.; formal analysis, M.K. and W.K.; investigation,
E.G., M.K., S.v.S., M.U. and W.K.; resources, M.U. and W.K.; data curation, E.G., M.K. and W.K.;
writing—original draft preparation, E.G., S.v.S., M.K. and W.K.; writing, E.G., S.v.S., M.K. and W.K.;
funding acquisition, M.U. and W.K. All authors have read and agreed to the published version of
this manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: The datasets generated and/or analyzed during the current study are
available from the corresponding author upon reasonable request.
Acknowledgments: This work was performed in (partial) fulfillment of the requirements for Ellen
Guretzki to obtain the degree Dr. med. dent.
Conflicts of Interest: The authors declare that this research was conducted in the absence of any
commercial or financial relationships that could be construed as a potential conflict of interest.
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