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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
https://doi.org/10.1186/s12984-021-00889-1
REVIEW
Serious games forupper limb rehabilitation
afterstroke: ameta-analysis
Ioannis Doumas1,2,3, Gauthier Everard1,3, Stéphanie Dehem1,2,3 and Thierry Lejeune1,2,3*
Abstract
Background: Approximately two thirds of stroke survivors maintain upper limb (UL) impairments and few among
them attain complete UL recovery 6 months after stroke. Technological progress and gamification of interventions
aim for better outcomes and constitute opportunities in self- and tele-rehabilitation.
Objectives: Our objective was to assess the efficacy of serious games, implemented on diverse technological
systems, targeting UL recovery after stroke. In addition, we investigated whether adherence to neurorehabilitation
principles influenced efficacy of games specifically designed for rehabilitation, regardless of the device used.
Method: This systematic review was conducted according to PRISMA guidelines (PROSPERO registration number:
156589). Two independent reviewers searched PubMed, EMBASE, SCOPUS and Cochrane Central Register of Con-
trolled Trials for eligible randomized controlled trials (PEDro score ≥ 5). Meta-analysis, using a random effects model,
was performed to compare effects of interventions using serious games, to conventional treatment, for UL rehabilita-
tion in adult stroke patients. In addition, we conducted subgroup analysis, according to adherence of included studies
to a consolidated set of 11 neurorehabilitation principles.
Results: Meta-analysis of 42 trials, including 1760 participants, showed better improvements in favor of interventions
using serious games when compared to conventional therapies, regarding UL function (SMD = 0.47; 95% CI = 0.24 to
0.70; P < 0.0001), activity (SMD = 0.25; 95% CI = 0.05 to 0.46; P = 0.02) and participation (SMD = 0.66; 95% CI = 0.29 to
1.03; P = 0.0005). Additionally, long term effect retention was observed for UL function (SMD = 0.42; 95% CI = 0.05 to
0.79; P = 0.03). Interventions using serious games that complied with at least 8 neurorehabilitation principles showed
better overall effects. Although heterogeneity levels remained moderate, results were little affected by changes in
methods or outliers indicating robustness.
Conclusion: This meta-analysis showed that rehabilitation through serious games, targeting UL recovery after stroke,
leads to better improvements, compared to conventional treatment, in three ICF-WHO components. Irrespective of
the technological device used, higher adherence to a consolidated set of neurorehabilitation principles enhances
efficacy of serious games. Future development of stroke-specific rehabilitation interventions should further take into
consideration the consolidated set of neurorehabilitation principles.
Keywords: Stroke, Upper extremity, Serious games, Virtual reality, Robotics
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Background
Each year more than 1 million Europeans suffer from
stroke and approximately two-thirds of survivors main-
tain upper limb (UL) paresis [1]. is number is expected
to rise by 35% in upcoming years [2] leading to addi-
tional rehabilitation needs. To this date, few people attain
Open Access
*Correspondence: thierry.lejeune@uclouvain.be
1 Institut de Recherche Expérimentale et Clinique, Neuro Musculo Skeletal
Lab (NMSK), Secteur des Sciences de la Santé, Université Catholique de
Louvain, Avenue Mounier 53, 1200 Brussels, Belgium
Full list of author information is available at the end of the article
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Page 2 of 16
Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
complete UL recovery 6 months after stroke [3]. New
interventions targeting the UL aim for better outcomes
in activities of daily living (ADL), functional independ-
ence and quality of life. Alongside conventional thera-
pies, recent developments offer possibilities in self- and
tele-rehabilitation [4] which could help manage, cost-effi-
ciently [5], increasing rehabilitation demands.
Technological improvements in robot assisted therapy
(RAT) and virtual reality (VR) systems (VRS) enhance
patient care and facilitate therapist assistance during UL
rehabilitation [6, 7]. First, RAT promotes the use of the
affected limb, intensifies rehabilitation through task rep-
etition and offers task-specific practice [7]. Effectiveness
of RAT is established for UL rehabilitation after stroke [8,
9]. Secondly, VRS provide augmented feedback, preserve
motivation and are becoming cost-efficient [5]. Recent
meta-analyses suggest a superior effect of VR-based
interventions compared to conventional treatment on UL
function and activity after stroke, especially if developed
for this specific purpose [10–12]. Authors attributed
these findings to the fact that VRS specifically developed
for rehabilitation, as opposed to commercial video-games
(CVG), fulfil numerous neurorehabilitation principles.
Typically, a common denominator of VRS and RAT is
playful interventions by means of serious games [13, 14].
A serious game is defined as a game that has education
or rehabilitation as primary goal. ese games combine
entertainment, attentional engagement and problem
solving to challenge function and performance [15, 16].
Moreover, they comply with several motor relearning
principles that constitute the basis of effective interven-
tions in neurorehabilitation [11, 16]. For example, some
devices adapt game difficulty to stimulate recovery and
maintain motivation [15]. Others incorporate functional
tasks mimicking ADL in virtual environments and pro-
vide performance feedback during and/or after task
completion [17]. Characteristics of serious games differ
depending on targeted rehabilitation purposes and tech-
nical specificities of the system they are implemented on.
Previous work on the efficacy of VR-based interven-
tions indicated that serious games may enhance UL
recovery after stroke [11, 12, 18]. However, why such
interventions, specifically developed for rehabilitation
purposes and implemented on various types of devices
(such as robots, smartphones, tablets, motion capture
systems, etc.), may constitute effective therapies for UL
rehabilitation after stroke needs to be further investi-
gated. Recent theoretical research proposed consolida-
tion of commonly acknowledged neurorehabilitation
principles [16]. Usually, serious games comply with sev-
eral of these principles which creates an opportunity to
evaluate clinical applicability of the consolidated set of
principles. To this day, it remains unclear whether higher
adherence to this consolidated set of neurorehabilitation
principles enhances efficacy of interventions. In addition,
it is not well known whether adherence to specific prin-
ciples influences efficacy. Finally, rehabilitation effects on
participation outcomes remain relatively unexplored. In
this context, efficacy of interventions should be addressed
in terms of all components of the World Health Organi-
zation’s International Classification of Function, Disabil-
ity, and Health (ICF-WHO) model [19].
e main objective of this systematic review and
meta-analysis was to address the following question in
PICOS form: in adults after stroke (P), do serious games,
implemented on various technological systems (I), show
better efficacy than conventional treatment (C), to reha-
bilitate UL function and activity, and patient’s participa-
tion (O)? A secondary objective was to assess whether
higher adherence to a consolidated set of neurorehabili-
tation principles enhances efficacy of games specifically
designed for rehabilitation, irrespective of the technolog-
ical device used.
Methods
Design
is systematic review followed the Preferred Report-
ing Items for Systematic Reviews and Meta-Analysis
(PRISMA) guidelines [20]. e protocol was registered in
International Prospective Register of Systematic Reviews
(PROSPERO 2020, registration number: 156589).
Identication andstudy selection
A search strategy looking for relevant literature was
developed for PubMed and adapted for the other data-
bases, namely Scopus, Embase and Cochrane Library
(Additional file1). Authors received help from a profes-
sional librarian to set up the search strategy. Two inves-
tigators (GE and ID) independently retrieved studies. All
references were stored in reference management software
EndNote X9. After removal of duplicates, remaining ref-
erences were first screened based on titles and abstracts.
Study eligibility was assessed according to the following
criteria: (a) design of randomized controlled trials (RCT)
(b) participants were adults undergoing stroke rehabili-
tation (c) the intervention consisted of games developed
for neurorehabilitation purposes and implemented in the
following technological devices: robotic systems, VRS,
tablets, smartphones and motion capture systems (d) rel-
evant outcomes were employed to assess UL function,
UL activity and participation (e) studies were published
in French or English before May 5th, 2020. All studies
using additional therapeutic modalities such as brain
stimulation, electrical stimulation or invasive treatments
were excluded.
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
Systematic reviews assessing effectiveness of VR-based
rehabilitation and RAT in stroke recovery were also
hand-searched looking for relevant references. Finally, a
selection based on full-text was conducted by the same
two reviewers. Disagreements were resolved through
discussion.
Quality andrisk ofbias assessment
e PEDro checklist was used for methodological qual-
ity assessment of trials [21]. In addition, the Cochrane
Collaboration’s Risk of Bias (RoB) tool was employed to
conduct a critical appraisal of each trial’s internal validity
[22].
Data extraction
e following data concerning patients, interventions,
control groups and outcomes were extracted from each
study: number of patients enrolled in each group, mean
time since stroke, corresponding stroke stage classifica-
tion (subacute: 7days to 6months after stroke, chronic:
more than 6months after stroke) [23], dosage and dura-
tion of the intervention, technological device used, type
and duration of treatment for the control group, presence
of a follow-up assessment and outcomes assessed in each
timepoint evaluation.
Studies were also assessed in terms of the number of
neurorehabilitation principles their intervention fulfilled
as described in the review of Maier et al. [11]. ese
authors described a total of 11 principles presented in
Table1. e two reviewers, independently, investigated
whether interventions of included studies fulfilled each
one of the neurorehabilitation principles. For each clearly
identified principle, one point was attributed to the study.
In case available information was vague, missing or did
not match the neurorehabilitation principle descriptive’
(as mentioned in Table1), no point was accorded. en,
we calculated a total score out of 11 for each included
study.
Outcome measurements
Outcome measures were selected in accordance to the
ICF-WHO model [19]. In each category, assessment
scales were chosen based on recent literature recom-
mendations [24, 25]. e Fugl-Meyer Assessment (FMA)
[26] was used for the body function domain. e Action
Research Arm Test (ARAT) [27], the Box and Block Test
(BBT) [28] and the Wolf Motor Function Test (WMFT)
[29] were used for the activity domain. e social partici-
pation subscale of the Stroke Impact Scale (SIS) [30] was
used for the participation domain.
When available, mean improvements in terms of
change-from-baseline and their standard deviation
(SD) were extracted for each time point. If not avail-
able, authors were contacted via email. In case of non-
response, the mean improvement was calculated through
subtraction between post-intervention mean score and
pre-intervention mean score. en, the SD was estimated
by using a formula according to the Cochrane Handbook
for Systematic Reviews of Interventions [31]. e value
of the correlation coefficient was imputed by using data
from other studies [17, 32, 33] included in the meta-
analysis. Lastly, when only median and quartiles were
Table 1 List of neurorehabilitation principles with description established by Maier et al. [11, 16]
All studies, 42 included in meta-analysis
+ , studies with SMD in favour of the experimental group for main outcomes regarding upper limb function
= , studies with SMD in favour of the control group for main outcomes regarding upper limb function
*Statistically signicant dierence (p < 0.05) in Fischer’s exact test
Neurorehabilitation principle Description Fullled in studies (%)
All studies + =
Massed practice Tasks aiming to increase the number of repetitions performed 81 79 85
Dosage Intensive training: more than a daily session of 60 min on every weekday 52 59 38
Structured practice Training that includes periods of rest 26 31 15
Task-specific practice Functional training relevant to ADL 100 100 100
Variable practice Training that includes different types of tasks 98 97 100
Multisensory stimulation Training that provides more than two types of sensory feedback 83 90 69
Increasing difficulty Complexity of tasks changes depending on participants’ ability, performance or time 76 76 80
Explicit feedback Training that provides information about the patient’s performance at the end of the task 79 93 46*
Implicit feedback Training that delivers information about the performance in real time such as visualization
of movement or other kinematic properties 74 83 54
Avatar representation Embodied training by representation of a human or body part 38 41 31
Use of the paretic limb Promoting the use of the paretic limb 76 76 80
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
available, the mean and SD were approximated using the
method proposed by Wan etal. [34]. For studies using
follow-up evaluations at least one month after the inter-
vention, mean improvements in terms of change-from-
baseline were calculated in order to assess long-term
effect retention.
Data andstatistical analysis
Articles scoring below 5/10 on the PEDro scale were
excluded due to overall poor methodological quality
[35]. In addition, only trials that described conventional
therapy used in the comparison group as including occu-
pational, physical or self-therapy were considered for
statistical analysis. Statistical analyses were performed
using the RevMan 5.3 software [36]. Since different rating
scales were used for studied outcomes and results were
reported in various ways, standardized mean difference
(SMD) and 95% confidence interval (CI) were calculated.
is method allowed standardization of results across
studies. A random effects meta-analysis model was used
for all analyses and statistical significance level was set at
P < 0.05 [37]. Heterogeneity across trials was estimated
using the I2 test. Heterogeneity was not considered to be
significative for a I2 < 30% [30].
Subgroup analysis was conducted for RCT whose
intervention met at least 8/11 neurorehabilitation princi-
ples compared to RCT whose intervention fulfilled less.
Another subgroup analysis was performed according to
stroke stage, comparing effects of interventions using
serious games on subacute and chronic stroke patients.
Subgroup analysis were only considered when at least
two trials in each subgroup reported a given domain.
Furthermore, long-term effect retention for trials that
measured outcomes at follow-up was evaluated.
Publication bias was evaluated visually through fun-
nel plot graphic representation. Sensitivity analyses was
conducted to verify results robustness in case of funnel
plot asymmetry, heterogeneity or presence of outliers.
Additional sensitivity analyses were conducted using two
different values for correlation coefficient [30]. GRADE-
pro program was used to assess the strength of the body
evidence [38].
Finally, a Fischer’s exact test was used to compare dif-
ferences in proportions among studies, depending on
their results, regarding adherence to each neurorehabili-
tation principle.
Results
Study selection
A total of 8141 trials were identified through search
across all databases and 165 additional records through
other sources. After removal of duplicates, 5131 arti-
cles were screened based on titles and abstracts. Among
these, 5049 were excluded and 82 full-text articles were
assessed for eligibility. 51 RCT were included in the
qualitative synthesis. Finally, after quality assessment
was performed, 42 RCT were considered for quantita-
tive synthesis. Further details are illustrated in the study
PRISMA flow chart (Fig.1).
Study characteristics
A total of 2083 participants with a mean age ranging from
49.3 to 76.0years were included in the qualitative synthe-
sis. For each included study, we identified the mean age
of the participants, the stroke stage classification and the
type of device used for intervention (Table2). Approxi-
mately one third (31%) of studies included stroke patients
at subacute stage and two-thirds (69%) at chronic stage.
Across trials, serious games were implemented on dif-
ferent types of devices: 26 (51%) used a motion capture
system among which many low-cost systems (such as
Microsoft Kinect for example), 10 (19%) used an end-
effector type robot, 5 (9%) used motion capture gloves,
3 (7%) a robotic exoskeleton, 3 (6%) an immersive-VR
system, 2 (4%) a smartphone or tablet, 1 (2%) a sur-
face EMG-controlled sensor and 1 (2%) an arm support
system.
For each trial, total treatment duration in terms of min-
utes per session, number of sessions per week and total
number of weeks was identified. In addition, whether
intervention and control groups were time-matched
regarding these characteristics was verified (Table 3).
Total number of weeks of treatment varied from 2 to
12 weeks with a mean of 5 weeks among trials. Daily
duration of therapy varied widely among studies ranging
from 30 to 225min. In most trials (85%), total treatment
duration was matched between the intervention and con-
trol groups (Table3).
e number of neurorehabilitation principles fulfilled
by serious games were identified through content analy-
sis. is number varied from 4 to 11 (Table3). For a total
of 11 neurorehabilitation principles, 32 (63%) interven-
tions met 8 or more, 17 (33%) met between 5 and 7 and 2
(4%) interventions met less than 5. Table1 illustrates the
percentage of studies included in meta-analysis that com-
plied with each neurorehabilitation principle. In addition,
Table 1 displays differences in adherence to each neu-
rorehabilitation principle between studies with overall
positive or negative results (based on each study SMD in
quantitative synthesis results). Statistically significant dif-
ferences were observed regarding the principle of explicit
feedback. Indeed, the group of studies with overall posi-
tive results adheres more to this principle than the other
group.
Regarding main outcomes, 44 trials (87%) assessed
UL motor function, 30 (59%) assessed UL activity and
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
9 (17%) assessed participation (Table 3). Most tri-
als (60%) reported significantly superior results in at
least one ICF-WHO component in favour of interven-
tions using serious games compared to conventional
treatment.
Methodological quality andrisk ofbias assessment
PEDro scores of 51 included studies ranged from 5 to
8 with a mean (SD) of 6.33 (1.15) indicating an over-
all moderate to high methodological quality (Table2).
Detailed PEDro scale scoring for each trial is illus-
trated in Additional file1: TableS1. In addition, the
detailed analysis using the Cochrane Collaboration
RoB tool is presented in Additional file1: Fig.S1.
Eect ofrehabilitation throughserious games onUL motor
function
In total, rehabilitation using serious games led to signifi-
cantly better improvements, of moderate effect size, in
UL motor function compared to conventional treatment
(SMD = 0.47; 95% CI = 0.24 to 0.70; P < 0.0001) (Fig. 2).
Subgroup analysis highlighted differences between
results of trials using serious games fulfilling 8 or more
neurorehabilitation principles and those that did not
(P = 0.003). Indeed, only interventions that met 8 or
more principles showed significant impact of moderate
effect size on upper limb motor function (SMD = 0.62;
95% CI = 0.33 to 0.92; P = 0.0001). Although total results
indicated considerable heterogeneity between studies
(I2 = 76%), analysis using the GRADE approach led to a
Fig. 1 Flow chart (PRISMA) of the selection process
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
Table 2 Characteristics of included studies
Author ParticipantsaAgebStroke stage Type of device PEDro score
Adomaviciene [51] 42 64.6 Subacute Motion capture system, LCD monitor 5
Ang [52] 21 54.2 Chronic Haptic Knob robotic system, LCD monitor 6
Aprile [53] 224 69.5 Subacute 4 different robotic devices 6
Askin [54] 38 55.0 Chronic Motion capture system, LCD monitor 6
Brunner [40] 120 62.0 Subacute Motion capture gloves, LCD monitor 7
Cameirao [55] 19 61.0 Subacute Motion capture system, data gloves, LCD monitor 5
Cameirao [56] 44 62.0 Chronic Motion capture system, data gloves, LCD monitor 6
Cho [57] 38 60.0 Chronic End-effector robot, LCD monitor 8
Choi [58] 24 61.0 Subacute Smartphone and tablet computer 6
Crosbie [59] 18 60.0 Chronic Immersive VR motion tracking system 8
Dehem [14] 45 67.3 Subacute End-effector robot, LCD monitor 7
Duff [60] 21 68.5 Chronic Motion capture system, LCD monitor 5
Henrique [61] 31 76.0 Chronic Immersive VR motion tracking system 5
Housman [62] 28 55.0 Chronic Robotic exoskeleton, LCD monitor 5
Hung [13] 33 58.5 Chronic Motion capture system, LCD monitor 7
Jang [63] 10 57.1 Chronic Motion capture system, LCD monitor 5
Jo [64] 29 64.0 Chronic Motion capture system, LCD monitor 5
Kim [65] 23 53.5 Subacute Motion capture system, LCD monitor 8
Kiper [66] 80 64.0 Subacute Motion capture system, LCD monitor 5
Kiper [67] 44 64.3 Subacute Motion capture system, LCD monitor 5
Kiper [46] 136 63.9 Subacute Motion capture system, LCD monitor 6
Klamroth-Marganska [68] 73 56.5 Chronic Robotic exoskeleton, LCD monitor 8
Kottink [32] 18 61.5 Chronic Motion capture system, LCD monitor 6
Kwon [69] 26 57.5 Subacute Motion capture system, LCD monitor 5
Laffont [44] 51 58.0 Subacute Touchscreen interface, computer monitor 8
Lee [70] 26 67.5 Chronic Motion capture system, LCD monitor 8
Lee [71] 18 71.1 Chronic Motion capture system, LCD monitor 6
Lee [72] 30 51.0 Chronic End-effector robot, LCD monitor 6
Levin [73] 12 58.5 Chronic Motion capture system, LCD monitor 6
Liao [74] 20 54.5 Chronic End-effector robot, LCD monitor 7
Mugler [75] 32 58.0 Chronic Surface EMG-controlled sensor, computer monitor 6
Nijenhuis [76] 19 60.0 Chronic Arm suppor t system 6
Norouzi-Gheidari [39] 18 49.9 Chronic Motion capture system, LCD monitor 7
Ogun [77] 65 60.6 Chronic Immersive VR motion tracking system 6
Oh [17] 31 55.0 Chronic 3-D manipulator, computer monitor 7
Park [33] 25 52.5 Chronic 2-D planar motion handlebar, LCD monitor 7
Piron [78] 36 65.2 Chronic Motion capture camera, computer monitor 7
Piron [47] 47 60.5 Chronic Motion capture system, LCD monitor 8
Prange [79] 68 59.1 Subacute Arm support system, computer monitor 7
Rogers [80] 21 64.4 Subacute Touchscreen mega-tablet 6
Schuster-Amft [81] 54 61.3 Chronic Motion capture gloves, LCD monitor 8
Shin [82] 16 49.3 Subacute Motion capture system, LCD monitor 5
Shin [83] 32 54.0 Chronic Motion capture system, LCD monitor 6
Shin [84] 46 58.5 Chronic Motion capture gloves, LCD monitor 7
Subramanian [85] 32 61.0 Chronic Motion capture system, LCD monitor 7
Thielbar [86] 14 56.5 Chronic Pneumatically actuated motion capture gloves 6
Thielbar [87] 20 59.7 Chronic Motion capture system, LCD monitor 5
Tomic [88] 26 57.4 Subacute End-effector robot, LCD monitor 7
Wolf [89] 99 56.9 Chronic End-effector robot, computer touch screen 7
Yin [90] 23 58.3 Subacute Motion capture system, computer monitor 6
Zondervan [91] 17 59.5 Chronic Motion capture gloves, computer monitor 6
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
moderate certainty of evidence (Additional file1: Fig.S2
illustrates detailed summary of findings).
Additional subgroup analysis was conducted based on
the stroke stage of included participants across studies
(Fig.3). Results suggest that interventions using serious
games were effective in improving UL motor function
in both subacute (SMD = 0.35; 95% CI = 0.10 to 0.59;
P = 0.006) and chronic stage after stroke (SMD = 0.57;
95% CI = 0.19 to 0.95; P = 0.003). Differences among sub-
groups did not reach statistical significance (P = 0.33).
Finally, in order to address heterogeneity, sensitivity
analyses were performed in two ways. A first analysis was
conducted by excluding outliers identified through fun-
nel plot graphic representation (Additional file1: Fig.S3).
en, a second analysis was carried out by using a dif-
ferent correlation coefficient value. In both cases, results
indicate no significant differences in total estimates when
compared to initial findings (Additional file1: Figs. S4
and S5).
Eect ofrehabilitation throughserious games onUL
activity
In total, rehabilitation using serious games led to sig-
nificantly better improvements, of low effect size, in
upper limb activity compared to conventional treatment
(SMD = 0.25; 95% CI = 0.05 to 0.46; P = 0.02) (Fig. 4). In
a similar way to results regarding UL function, subgroup
analysis showed significantly better improvements, of
moderate effect size, only for interventions that fulfilled
8 or more neurorehabilitation principles (SMD = 0.42;
95% CI = 0.12 to 0.72; P = 0.006). Differences among
subgroups were statistically significant (P = 0.01). Total
results indicated moderate heterogeneity between studies
(I2 = 56%). Additional subgroup analysis based on stroke
stage did not reach statistical significance for neither
subacute or chronic stage after stroke (Additional file1:
Fig.S6).
Eect ofrehabilitation throughserious games
onparticipation
In total, rehabilitation using serious games led to signifi-
cantly better improvements, of large effect size, in partici-
pation compared to conventional treatment (SMD = 0.66;
95% CI = 0.29 to 1.03; P = 0.0005) (Fig.5). No significant
heterogeneity was present (I2 = 0%). All trials included in
this analysis used a serious game that complied with 8 or
more neurorehabilitation principles.
Analysis offollow‑up data
Separate analyses were conducted regarding follow-up
data for each ICF-WHO component. Only half of the
studies included in the quantitative synthesis (50%) per-
formed follow-up evaluations. Among them, length of
follow-up period ranged from 1 to 6months with a mean
(SD) of 2.3months (1.86). An overall tendency towards
improvement for interventions using serious games
regarding all ICF-WHO components was observed
(Additional file1: Figs. S7, S8 and S9). Total estimates
concerning UL function indicate effect retention to fol-
low-up in favour of the experimental group of moderate
effect size (SMD = 0.42; 95% CI = 0.05 to 0.79; P = 0.03).
Results did not reach statistical significance regarding UL
activity and participation.
Discussion
Main results
is systematic review and meta-analysis showed results
in favour of rehabilitation using, purpose-built, serious
games on UL motor function, UL activity and participa-
tion after stroke compared to conventional treatment.
Moreover, long term effect retention was significantly
maintained regarding UL function. Irrespective of the
technological device used, serious games that complied
with more than 8 out of 11 neurorehabilitation principles
showed better overall effects.
Previous studies oneectiveness ofVRS/CVG forUL
rehabilitation afterstroke
Previous work on the use of VRS and CVG for UL reha-
bilitation after stroke demonstrated similar results [11,
17]. Yet, to date, usage and efficacy of game-based inter-
ventions for UL rehabilitation after stroke remain con-
troversial [38–40]. Initially, a meta-analysis by Saposnik
et al., combining observational studies and RCT, sug-
gested improvements in UL strength and motor function
after stroke [41]. However, this review focused on vari-
ous VRS, including CVG designed by the entertainment
industry, not specifically developed for rehabilitation.
In addition, no statistically significant differences were
observed concerning UL activity outcomes and no anal-
ysis was conducted regarding ICF-WHO participation
component due to limited available data.
Two other groups conducted systematic reviews on a
similar topic [42, 43]. However, both reviews included
studies concerning not only UL rehabilitation but also
Table 2 (continued)
LCD monitor, liquid–crystal display monitor; 3-D, 3-Dimensional; 2-D, 2-Dimensional
a Participants: number of total participants in study
b Age: mean age in years estimated for total number of participants included in each study
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
Table 3 Duration, matched groups, outcome measurements, overall findings, number of included neurorehabilitation principles
Authors and publication year DurationaMatched
groupsbUL function UL activity Participation Overall
ndingscPrinciplesd
Adomaviciene, 2019 [51] 2 ✓FMA-UE BBT + 4
Ang, 2014 [52] 6 ✓FMA-UE = 5
Aprile [53] 6 ✓FMA-UEsARAT
s = 10
Askin, 2018 [54] 4 X FMA-UEm, s BBTm, s + 6
Brunner, 2017 [40] 4 ✓ARAT
s, BBT = 4
Cameirao, 2011 [55] 12 ✓FMA-UE + 6
Cameirao, 2012 [56] 4 ✓FMA-UE BBT + 6
Cho, 2019 [57] 6 ✓FMA-UE ARAT, BBT + 6
Choi, 2016 [58] 2 ✓FMA-UE s + 8
Crosbie, 2012 [59] 3 ✓ARAT s = 6
Dehem, 2019 [14] 9 ✓FMA-UE BBT SIS + 9
Duff, 2013 [60] 4 ✓FMA-UEm, s WMFTm, s SIS = 9
Henrique, 2019 [61] 12 ✓FMA-UE + 9
Housman, 2009 [62] 9 ✓FMA-UE + 5
Hung, 2019 [13] 12 ✓FMA-UEm, s WMFTm, s = 8
Jang, 2005 [63] 4 ✓FMAsBBTs + 10
Jo, 2012 [64] 4 X WMFT + 9
Kim, 2018 [65] 2 ✓FMA-UEsBBTs = 7
Kiper, 2011 [66] 4 ✓FMA-UEs + 9
Kiper, 2014 [67] 4 ✓FMA-UEs + 9
Kiper, 2018 [46] 4 ✓FMA-UEs + 8
Klamroth-Marganska, 2014 [68] 8 ✓FMA-UE SIS + 7
Kottink, 2014 [32] 6 ✓FMA-UE ARAT = 6
Kwon, 2012 [69] 4 X FMA-UEs = 5
Laffont [44] 6 ✓FMA-UE BBT, WMFT = 8
Lee, 2016a [70] 8 ✓FMA-UEsBBTs + 8
Lee, 2016b [71] 6 ✓BBT + 9
Lee, 2018 [72] 8 ✓FMA-UEs + 8
Levin, 2012 [73] 3 ✓FMA-UEsBBTs, WMFT + 9
Liao, 2012 [74] 4 ✓FMA-UEs + 7
Mugler, 2019 [75] 3 X FMA-UE = 8
Nijenhuis, 2017 [76] 6 ✓FMA-UEm, s ARAT
m, s, BBT SIS = 5
Norouzi-Gheidari, 2019 [39] 4 X FMA-UEsBBTsSISs + 8
Ogun, 2019 [77] 6 ✓FMA-UEsARAT
s + 8
Oh, 2019 [17] 6 ✓FMA-UE BBT + 9
Park, 2019 [33] 4 ✓FMA-UE WMFT SIS = 9
Piron, 2009 [78] 4 ✓FMA-UEs + 8
Piron (2010) [47] 4 ✓FMA-UEs + 10
Prange, 2015, [79] 6 ✓BBT + 9
Rogers2019 [80] 4 X FMA-UEs = 5
Schuster-Amft, 2018 [81] 4 ✓BBTm, s SIS = 7
Shin, 2014 [82] 2 X FMA-UEs = 8
Shin, 2015 [83] 4 ✓FMA-UEm, s = 9
Shin, 2016 [84] 4 ✓FMA-UEsSISs + 10
Subramanian, 2012 [85] 4 ✓FMA-UE + 8
Thielbar, 2014 [86] 6 ✓FMA-UEsARAT
s + 10
Thielbar, 2020 [87] 4 ✓FMA-UE + 8
Tomic, 2017 [88] 3 ✓FMA-UE WMFT + 8
Wolf, 2015 [89] 8 ✓FMA-UEsARAT
s, WMFT = 6
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Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
gait and balance, making it difficult to draw conclusions
regarding the UL. Palma etal., solely relying on qualita-
tive synthesis, supported positive findings on function
[42]. Results were inconclusive regarding activity and
participation components and further interpretation
was limited due to lack of quantitative synthesis. en, a
meta-analysis by Lohse etal. showed positive effects in
favour of VR-based interventions regarding three ICF-
WHO components [43]. However, analysis was restricted
to therapies that did not include robotic assistance. Fur-
thermore, analyses through meta-regressions did not
point out significant differences in outcomes between
commercially available and custom-built systems.
Two updated Cochrane reviews covered broader
aspects of VR and robotics in UL rehabilitation after
stroke [8, 10]. In the review by Mehrholz etal., high qual-
ity evidence supports better improvements in ADL, arm
function and arm strength in favour of RAT [8]. None-
theless, effects of robotic training performed in form of
a serious game were not studied. en, a review by Laver
etal. on VR-based interventions, demonstrated equiva-
lent improvements in UL function and activity when
comparing time-matched interventions [10]. Notably, UL
function and activity outcomes were pooled in one com-
mon analysis instead of distinguishing effects in terms
of the two ICF-WHO components. Further analyses in
subgroups suggested better results when specific systems
designed for rehabilitation were employed compared to
off-the-shelf CVG, although differences did not reach
statistical significance.
Finally, two recent reviews showed improvements on
both UL function and activity in groups receiving VR/
gaming-based training after stroke [11, 18]. However,
both reviews studied broader aspects of VR-based inter-
ventions and their scope was not delimited to specific
use of serious games. Karamians et al. suggested that
interventions with gaming components further promote
recovery compared to those providing visual feedback
only [18]. en, Maier etal. distinguished VRS specifi-
cally built for rehabilitation purposes from others des-
tined to generic use [11]. Results illustrated that, when
compared to conventional therapy, interventions spe-
cifically designed based on elements enhancing neural
plasticity led to significantly better results [11]. Addition-
ally, it was suggested that custom-made interventions, in
comparison to non-specific interventions, comply better
with a series of neurorehabilitation principles.
Adherence toneurorehabilitation principles
ofinterventions using serious games forUL rehabilitation
afterstroke
To this date, UL stroke recovery through games devel-
oped specifically for rehabilitation and implemented
on diverse systems, has not been explicitly reviewed.
In addition, most recent reviews delimit their scope in
technological terms by considering interventions based
on the devices being used [11, 12, 18]. Some authors
characterise comparison between studies using differ-
ent devices as difficult [44]. However, a holistic over-
view of serious games, regardless of the technology
used, is important in order to better understand their
added value in UL rehabilitation after stroke. Com-
parison between studies using systems with different
technical specificities, mainly in hardware, is challeng-
ing. Nonetheless, interventions through serious games
implemented on different devices may share similari-
ties. Indeed, all studies included in our review perform
non-invasive treatments. en, gamification and adapt-
ability of interventions, to the patients’ impairments
and performance, aim to maintain motivation through-
out therapy sessions [45]. Additionally, all these sys-
tems have the potential to give access to kinematic data
allowing objective assessment, evaluating real-time
performance and tracking UL recovery [46–48]. Finally,
Table 3 (continued)
Authors and publication year DurationaMatched
groupsbUL function UL activity Participation Overall
ndingscPrinciplesd
Yin, 2014 [90] 2 ✓FMA-UEm, s ARAT
m, s = 11
Zondervan, 2016 [91] 3 ✓ARAT, BBT = 7
UL upper limb, FMA-UE Fugl-Meyer Assessment Upper Extremity subscale, ARAT action research arm test, BBT box and block test, WMFT Wolf-motor function test,
SIS stroke impact scale, ✓, matched time between interventions; X, time between interventions not matched; + , statistically signicant improvement in favour of
experimental group for main outcomes; = , no statistically signicant dierences reported between experimental and control group
a Duration: total number of treatment weeks
b Matched groups: matched time in terms of daily session time, sessions per week and total number of weeks between experimental and control group
c Overall ndings: reported ndings concerning primary outcome measures
d Principles: total number of neuro-rehabilitation principles fullled by the serious game used in the intervention. A total of 11 principles were examined for each trial
m Studies that reported only median and quartiles
s Studies for which the standard deviation had to be estimated
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Page 10 of 16
Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
all interventions stimulate recovery through adher-
ence to common neurorehabilitation principles. In fact,
comparison across different types of technologies and
treatment modalities leads to identification of common
‘active ingredients’ in terms of effective rehabilitation
[11]. In accordance with recent literature, this review
contributes to identifying a rationale regarding efficacy
of interventions in UL rehabilitation after stroke. Our
results point out that even in a group of interventions
specifically developed for rehabilitation purposes, dif-
ferences in outcomes may be explained depending on
higher adherence to neurorehabilitation principles.
Furthermore, even though most interventions seem
to fulfil certain principles (task-specific practice, vari-
able practice, massed practice), it seems that clusters
of principles met among serious games may lead to
differences in efficacy. For instance, our findings sug-
gest that providing feedback during therapy appears
to be an important characteristic that interventions
using serious games should satisfy. Further, to what
degree each individual principle contributes in efficacy
is difficult to study. However, it appears that the more
Fig. 2 Forest plot of upper limb motor function as measured by the FMA-UE: studies using a serious game fulfilling ≥ 8 Npr versus studies using a
serious game fulfilling < 8 Npr. FMA-UE upper extremity subscale of the Fugl-Meyer Assessment, Npr neurorehabilitation principles
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 11 of 16
Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
an intervention adheres to principles, the better the
expected outcomes can be regarding motor recovery.
To the best of our knowledge, this systematic review is
the first to address, in a non-fragmented way, efficacy of
specifically designed gaming interventions in UL reha-
bilitation after stroke. Our results confirm current trends
favouring custom-made rehabilitation systems and gami-
fication of interventions. Positive findings concerning
function and activity have already been reported in pre-
vious reviews [11, 18]. It is worth noting that this review
shows encouraging results in participation outcomes
indicating, therefore, improvements in three ICF-WHO
components.
Strengths andlimitations
In a rapidly emerging field, 40% of studies included
in our review were published within the last 3 years.
Quantitative synthesis was performed by only using
RCT of moderate to high methodological quality.
However, this was not feasible for two studies due to
unavailable data. Additionally, even though our work
was conducted according to PRISMA guidelines for
Fig. 3 Forest plot of upper limb motor function as measured by the FMA-UE: studies in the subacute phase after stroke versus studies in the
chronic phase after stroke. FMA-UE, upper extremity subscale of the Fugl-Meyer Assessment
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 12 of 16
Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
systematic reviews, no methods were used to detect
unpublished trials. Also, publication bias was only
assessed through funnel plot graphic representation
which nonetheless did not indicate asymmetry. Het-
erogeneity across studies was moderate to high regard-
ing UL function and activity outcomes. is may be
partially due to variation of elements such as patient
characteristics, duration of interventions and evalua-
tion timepoints. Heterogeneity was addressed by using
a random effects model for meta-analyses and by con-
ducting additional analyses. Even though heterogene-
ity levels remained moderate, our results were little
affected by changes in methods or outliers, indicating
robustness.
Fig. 4 Forest plot of upper limb activity as measured by the ARAT, BBT, WMFT: studies using a serious game fulfilling ≥ 8 Npr versus studies using
a serious game fulfilling < 8 Npr. ARAT action research arm test, BBT box and block test, WMFT Wolf motor function test, Npr neurorehabilitation
principles
Fig. 5 Forest plot of participation as measured by the social participation subscale of the SIS. SIS stroke impact scale
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Page 13 of 16
Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
Perspectives
Our work offers some suggestions regarding clini-
cal practice and future research. Interventions using
serious games may be encouraged and integrated in
upper limb rehabilitation programs during subacute
and chronic stage after stroke. Specifications regarding
dosage, duration and selection of patients that could
benefit most from these treatments need further inves-
tigation. In addition, serious games should be explored
in terms of ways to provide self- or tele-rehabilitation.
From a research point of view, new developments
in gaming interventions can take into consideration
adherence to neurorehabilitation principles. In accord-
ance with our findings, future developments of inter-
ventions in UL stroke rehabilitation ought to comply
with as many neurorehabilitation principles as possible.
Future work should study how variations in clusters
of these principles may influence differently specific
aspects of motor or cognitive rehabilitation. Also, rich-
ness of kinematic data, accessible through technologi-
cal devices on which games are implemented, open
new perspectives in assessment and follow-up of stroke
patients. In our review, only 11% of studies used kin-
ematic data, complementary to clinical rating scales,
for UL function evaluation. Finally, few studies (11%)
included in our review reported cognitive outcomes.
Since motor performance and functional recovery can
be influenced by cognitive determinants [49, 50], com-
bined assessment of all these aspects should be further
considered in future work.
Conclusion
In conclusion, this systematic review and meta-analysis
showed that post-stroke UL rehabilitation through seri-
ous games, implemented on various types of techno-
logical devices, showed better improvements, compared
to conventional treatment, on three ICF-WHO compo-
nents. Long term effect retention was maintained for UL
function. Irrespective of the technological system used,
serious games that complied with more than 8 out of 11
neurorehabilitation principles led to better overall effects.
Our findings emphasize the importance of adherence to
neurorehabilitation principles in order to improve effi-
cacy of interventions in UL rehabilitation after stroke.
Abbreviations
UL: Upper limb; ADL: Activities of daily living; VR: Virtual reality; VRS: Virtual
reality systems; RAT : Robot-assisted therapy; CVG: Commercial video-games;
ICF-WHO: World Health Organization’s International Classification of Function,
Disability, and Health; RCT : Randomized controlled trials; FMA: Fugl-Meyer
assessment; ARAT : Action Research Arm Test; BBT: Box and block test; SIS:
Stroke impact scale; SMD: Standardized mean difference; CI: Confidence
interval.
Supplementary Information
The online version contains supplementary material available at https:// doi.
org/ 10. 1186/ s12984- 021- 00889-1.
Additional le1: TableS1. Detailed PEDro scale scoring for each study.
Figure S1. Detailed analysis using the Cochrane collaboration risk of
bias tool. Figure S2. Detailed summary of findings using the GRADEpro
approach. Figure S3. Funnel plot graphical representation. Figure S4.
Sensitivity analysis without outliers. Figure S5. Sensitivity analysis: use
of different correlation coefficient value (0.9). Forest plot of upper limb
motor function as measured by the FMA-UE: studies using a serious
game fulfilling ≥ 8 Npr versus studies using a serious game fulfilling < 8
Npr. Abbreviations; FMA-UE, upper extremity subscale of the Fugl Meyer
Assessment; Npr, Neurorehabilitation principles. Figure S6. Forest plot
of upper limb activity as measured by the ARAT, BBT, WMFT: studies in
the subacute phase after stroke versus studies in the chronic phase after
stroke. Abbreviations; ARAT, Action Research Arm Test; BBT, Box and Block
test; WMFT, Wolf Motor Function Test; Npr, Neurorehabilitation principles.
Figure S7. Follow-up evaluation. Forest plot of upper limb motor function
as measured by the FMA-UE: studies using a serious game fulfilling ≥ 8
Npr versus studies using a serious game fulfilling < 8 Npr. Abbreviations;
FMA-UE, upper extremity subscale of the Fugl Meyer Assessment; Npr,
Neurorehabilitation principles. Figure S8. Follow-up evaluation. Forest
plot of upper limb activity as measured by the ARAT, BBT, WMFT: studies
using a serious game fulfilling ≥ 8 Npr versus studies using a serious
game fulfilling < 8 Npr. Abbreviations; ARAT, Action Research Arm Test;
BBT, Box and Block test; WMFT, Wolf Motor Function Test; Npr, Neurore-
habilitation principles. Figure S9. Follow-up evaluation. Forest plot of
participation as measured by the social participation subscale of the SIS.
Abbreviations; SIS, Stroke Impact Scale.
Acknowledgements
We would like to thank the Région Wallonne, the SPW-Economie-Emploi-
Recherche and the Win 2 Wal Program (convention n°1810108) for their sup-
port. We would like to thank Christine Detrembleur, professor at UCLouvain,
for her availability and guidance regarding the data analyses aspects. Also, we
would like to thank Sophie Patris, professional librarian at UCLouvain, for her
help in the elaboration of the search strategy.
Authors’ contributions
ID and GE conducted the study selection process, retrieved data and
performed analyses. GE contributed to writing the manuscript. TL and SD
contributed to data interpretation and manuscript revisions. All authors read
and approved the final manuscript.
Funding
Région Wallonne, SPW-Economie-Emploi-Recherche, Win2Wal Program (con-
vention n°1810108).
Availability of data and materials
All data generated or analysed during this study are included in this published
article and its supplementary information files.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Institut de Recherche Expérimentale et Clinique, Neuro Musculo Skeletal Lab
(NMSK), Secteur des Sciences de la Santé, Université Catholique de Louvain,
Avenue Mounier 53, 1200 Brussels, Belgium. 2 Service de Médecine Physique
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Page 14 of 16
Doumasetal. J NeuroEngineering Rehabil (2021) 18:100
et Réadaptation, Cliniques Universitaires Saint-Luc, Avenue Hippocrate 10,
1200 Brussels, Belgium. 3 Université Catholique de Louvain, Louvain Bionics,
1348 Louvain-la-Neuve, Belgium.
Received: 14 September 2020 Accepted: 31 May 2021
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