Does motivation matter in upper-limb rehabilitation after stroke? ArmeoSenso-Reward: study protocol for a randomized controlled trial
Widmer et al. Trials
Does motivation matter in upper-limb rehabilitation after stroke? ArmeoSenso- Reward: study protocol for a randomized controlled trial
Mario Widmer 0 1 2 3
Jeremia P. Held 0 1 2
Frieder Wittmann 4
Olivier Lambercy 4
Kai Lutz 1 2
Andreas R. Luft 1 2
0 Equal contributors
1 cereneo, Center for Neurology and Rehabilitation , Vitznau , Switzerland
2 Division of Vascular Neurology and Neurorehabilitation, Department of Neurology, University Hospital of Zurich , Zurich , Switzerland
3 Neural Control of Movement Laboratory, ETH Zurich , Zurich , Switzerland
4 Rehabilitation Engineering Laboratory, ETH Zurich , Zurich , Switzerland
Background: Fifty percent of all stroke survivors remain with functional impairments of their upper limb. While there is a need to improve the effectiveness of rehabilitative training, so far no new training approach has proven to be clearly superior to conventional therapy. As training with rewarding feedback has been shown to improve motor learning in humans, it is hypothesized that rehabilitative arm training could be enhanced by rewarding feedback. In this paper, we propose a trial protocol investigating rewards in the form of performance feedback and monetary gains as ways to improve effectiveness of rehabilitative training. Methods: This multicentric, assessor-blinded, randomized controlled trial uses the ArmeoSenso virtual reality rehabilitation system to train 74 first-ever stroke patients (< 100 days post stroke) to lift their impaired upper limb against gravity and to improve the workspace of the paretic arm. Three sensors are attached to forearm, upper arm, and trunk to track arm movements in three-dimensional space while controlling for trunk compensation. Whole-arm movements serve as input for a therapy game. The reward group (n = 37) will train with performance feedback and contingent monetary reward. The control group (n = 37) uses the same system but without monetary reward and with reduced performance feedback. Primary outcome is the change in the hand workspace in the transversal plane. Standard clinical assessments are used as secondary outcome measures. Discussion: This randomized controlled trial will be the first to directly evaluate the effect of rewarding feedback, including monetary rewards, on the recovery process of the upper limb following stroke. This could pave the way for novel types of interventions with significantly improved treatment benefits, e.g., for conditions that impair reward processing (stroke, Parkinson's disease). Trial registration: ClinicalTrials.gov, ID: NCT02257125. Registered on 30 September 2014.
Rehabilitation; Virtual reality; Stroke; Upper extremity; Arm; Feedback; Reward
After stroke, 50% of survivors are left with impairments in
arm function [
], which is associated with reduced
health-related quality of life . While there is evidence
for a positive correlation between therapy dose and
functional recovery [
], a higher therapy dose is challenging
to implement, as it usually leads to an increase in costs
commonly not covered by health insurances. However,
when dose is matched, most randomized controlled trials
introducing new types of rehabilitative interventions (e.g.,
robot-assisted therapy [
]) failed to show a superior effect
compared to standard therapy. Thus, the need for
improving therapy effectiveness remains. In search for elements
of effective therapy, we hypothesize that performance
feedback and monetary rewards can improve effectiveness.
It has been shown that reward enhances procedural
] and motor-skill learning [
] and has a positive
effect on motor adaptation . Rewards mainly
improve retention of motor skills and motor adaptations
]. This effect was not explained by training
duration (dose) as rewarded and non-rewarded groups
underwent similar training schedules [
]. In a
functional magnetic resonance imaging (fMRI) study,
Widmer et al. reported that adding monetary rewards
after good performance leads to better consolidation
and higher ventral striatum activation than knowledge
of performance alone . The striatum is a key locus
of reward processing [
], and its activity was shown to
be increased by both intrinsic and extrinsic reward [
Being a brain structure that receives substantial
dopaminergic input from the midbrain, ventral striatal
activity can be seen as a surrogate marker for dopaminergic
activity in the substantia nigra/ventral tegmental area
]. In rodents, Hosp et al. found that dopaminergic
projections from the midbrain also terminate directly in
the primary motor cortex (M1) [
]. Dopamine in M1
is necessary for long-term potentiation of certain
cortico-cortical connections and successful motor-skill
]. As mechanisms of motor learning are
also thought to play a role in motor recovery [
rehabilitative interventions may benefit from
neuroplasticity enhanced by reward.
Here, we describe a trial protocol to test the effect of
enhanced feedback and reward on arm rehabilitation
after stroke at matched training dose (time and
intensity). We use the ArmeoSenso, a standardized virtual
reality (VR)-based training system [
] that is delivered
in two versions for two different study groups, one
version with and one without reward and enhanced
Ethics and reporting
The study protocol follows the Consolidated Standards
of Reporting Trials (CONSORT) Statement on
randomized trials of non-pharmacological treatment [
Standard Protocol Items: Recommendations for
Interventional Trials (SPIRIT; see Fig. 5 for the SPIRIT Figure
and the SPIRIT Checklist in Additional file 1) guidance
for protocol reporting [
]. The study is recruiting
patients at three different rehabilitation clinics. The
procedures and the protocol (version 4.1 of 18 August 2016)
have been approved by the responsible Ethics
Committees “Ethikkommission Nordwest- und Zentralschweiz,”
the “Kantonale Ethikkommission Zürich” (LU2013-079
and PB_2016-01804) and the Swiss Agency for
Therapeutic Products (Swissmedic: 2014-MD-0033) and
conform to the guidelines of Good Clinical Practice E6 (R1).
All subjects have to give written informed consent in
accordance with the Declaration of Helsinki. A quality
assurance audit/inspection of this study may be
conducted by the competent authority or Ethical Committees,
respectively. The quality assurance auditor/inspector will
have access to all medical records, the investigator’s
studyrelated files and correspondence, and the informed
consent documentation that is relevant to this clinical study.
This multicentric trial is randomized, controlled and
assessor-blinded (Fig. 1). Patients are unaware of the
training characteristics of the other study group.
This study includes stroke patients (maximum 100 days
after stroke) who meet the following criteria: minimum
age of 18 years, hemiparesis of the arm due to
cerebrovascular ischemia, the ability to lift the paretic arm
against gravity, a minimal arm workspace of 20 cm ×
20 cm in the horizontal plane, ability and willingness to
participate, as well as the absence of severe aphasia (i.e.,
patients who are not able to follow two-stage
commands), depression, dementia and hemianopia.
The randomization procedure was planned and set up
by an independent contract research organization
(Appletree CI Group, Winterthur, Switzerland). A
nonconsecutively increasing, pseudo-randomly generated list
of subject identification numbers (IDs) was created. IDs
are chronologically assigned to each new study
participant, stratified by the study center. Allocation to one of
the two study groups is balanced in blocks of 4. The
randomization list containing the subject ID, the
corresponding group allocation and a randomly generated
password was sent to an independent (unblinded) study
staff member (“admin”) who has set up respective
patient-user computer accounts used for accessing the
therapy game. The group-specific version of the game,
i.e., either with or without reward, is defined by the
account. The admin keeps the assignment list and is not
involved in data collection.
Immediately before the first training session, each
study participant has to confirm by signature to have
received a sealed envelope containing a butterfly etiquette
with ID and password to access the account. The patient
keeps this etiquette for the entire study duration.
ArmeoSenso training system
The arm rehabilitation system combines motion
capturing via wearable inertial measurement units (IMUs) in
combination with a therapy game, running on a touch
screen computer (Inspiron 2330, Dell Inc., Round Rock,
TX, USA) (Fig. 2a). Three wireless IMUs (MotionPod 3,
Movea SA, Grenoble, France) are fixed to the
functionally impaired lower and upper arm as well as
the trunk [
In contrast to robot-based VR therapy systems, this
sensor-based approach does not offer any weight
support for the impaired arm. The ArmeoSenso system
specifically requires the patient to lift the arm against
gravity and to increase hand workspace in
threedimensional (3D) space. The system was validated in a
home feasibility trial with stroke patients [
]. For the
present study, the ArmeoSenso system includes two
automated functional assessments, one consisting of a
pointing task with nine targets arranged in two
semicircles in the transversal plane. The second assessment
measures the hand workspace of the trained limb (see
the “Primary outcome” section). While identical
assessments are performed in both training groups, the system
includes a specific version of a therapy game for each of
the two training groups: (A) a rewarding version
including monetary rewards, knowledge of performance
feedback and graphical special effects (Fig. 3a) and (B) a
non-rewarding version lacking these motivators (Fig. 3b).
A more detailed description follows.
In addition to standard therapy, both groups train for
1 h per day, 5 days a week for 3 weeks while inpatients
in a participating rehabilitation hospital. Note that for
study participants, standard therapy excludes additional
proximal-arm training. All other therapies, however, are
not affected by the study.
ArmeoSenso training is supervised by a therapist.
Since 1 h of consecutive upper-limb training per day
without weight support can be too demanding for some
patients, deviations from this protocol are allowed to a
minimum cumulative training time of 720 min.
A typical ArmeoSenso training session is described in
Wittmann et al. [
]. For the present study, patients log
in to their user account with their random ID and the
password printed on their butterfly etiquette. The IMUs
are fixed to the affected lower and upper arm and to the
trunk using custom-made Velcro straps (Balgrist Tec
AG, Zurich, Switzerland). The supervising therapist may
help if necessary. The ArmeoSenso system then guides
the patient through three calibration poses and two
automated assessments (see the “Outcome measures”
section) before training starts (beginning of the targeted
60-min session duration). In order to prevent physical
exhaustion, the patient is visually instructed to rest for
at least 4 s every 40 s. Moreover, patients are allowed to
interrupt the training session if an additional break is
needed. The duration of the additional breaks is added
at the end of the training session. After 60 min of net
training time, the automated assessments will be repeated
and the patient will be asked to fill in a short motivation
questionnaire (see the “Secondary outcome” section).
Both groups train with modified versions of the
ArmeoSenso “METEORS” game (see [
]). Although the two
versions differ markedly in terms of their appearance, they
share the underlying game mechanics. That is, in both a
virtual “hand” which matches the movement of the
subject’s real hand is used to catch objects that drop
downwards from the top of the screen. The targets are placed
within, or at the border of, the patient's virtual 3D
workspace, which is continuously estimated and updated using
a voxel-based model . The time to complete a round
in the METEORS game is T_max = 150 s (excluding rest).
If, during these 150 s, less than five targets were missed,
the round is won and the difficulty increases by up to
three levels, depending on the number of targets that hit
the ground. Difficulty is adapted dynamically by changing
(1) the average target speed of falling, (2) the target spawn
interval and (3) the number of simultaneously spawned
targets (one to a maximum of seven). It increases in this
order (i, ii, iii, i, …). Conversely, difficulty decreases in
reverse order if more than four targets were missed and
the round is lost after a certain time (T_loss). In that
case, the difficulty decrease is calculated by rounding
Tmax to the closest integer, but with a maximum of four
The reward group will train for 15 h with a version of
the METEORS game that is very similar to the one used
in previous studies [
]. Briefly, the hand is used to
catch the targets that are depicted as meteors. The
movement of the patient’s whole arm is displayed with
low latency on the computer screen as a moving virtual
arm; a feature implemented to increase the feeling for
embodiment and thus improve the motivation to move
the arm . Subjects are instructed to use the hand to
catch the falling meteors in order to protect their planet
from being destroyed (Fig. 3a). This game theme is easily
understood and emotionally involving [
Whenever a meteor is touched by the virtual hand, it
explodes, giving the patient immediate knowledge of the
result. Furthermore, a score appears with each exploding
meteor that depends on the falling speed and diminishes
with the time the meteor was visible on the screen
before being caught. Scores are summed up over a round
and reset when the next round starts. However, there is
also an all-time high score always visible on the upper
left (Fig. 3a). If a meteor is missed, it crashes on the
planet and damages it. Should the patient miss more
than four meteors within T_loss < 150 s, the round is
lost, which results in visual effects showing the planet
being destroyed and the camera shaking, followed by a
message encouraging the patient to try again.
After successful level completion, patients are shown a
feedback screen illustrating that they have successfully
saved the planet, how many meteors they managed to
catch and how many they have missed (Fig. 4a).
Monetary rewards are given for each completed level.
Patients can win up to 1 Swiss Franc (CHF; approx.
US$20), if they succeed, but 0.1 CHF is deducted for
every missed meteor. As a new level can be started
approximately every 3 min, a maximum of 20 CHF could
be won per training session in case of an uninterrupted
winning streak. This, however, is unlikely due to the
difficult adaptation described above. All of it, the money
won during the preceding round, during the ongoing
training session and the total money gathered over the
whole course of the study, is presented on the feedback
screen (Fig. 4a), which is followed by a high score list
showing the top 10 results (Fig. 4b). If the current result
was in the top 10, it is marked in the list (Fig. 4b). This
feature was also implemented to optimize patient
New planets (eight in total) and/or backgrounds (12 in
total) are unlocked during the course of the 3-week
training. These rewards do not have any influence on
the gameplay and difficulty but are intended to add
variety to the game. Once three planets have been
unlocked, the patient can choose between two randomly
selected planets at the start of every round.
The control training consists of the same sensor system
and game mechanics with all rewarding feedback
removed. In order to reduce the feeling of embodiment
], only the position of the hand is shown as a green
decagon on a plain black background. Targets are simple
pill-shaped, single-colored objects that disappear with a
delay of 1 s without producing a score or sound after
being touched; hence, there is no immediate but delayed
knowledge of performance. Complete removal of
knowledge of performance is not possible in this game
because patients then might reach for the same target
several times, which would hamper comparability to the
other study group. The feedback screen, the monetary
reward, the high score list and the unlocking of new
planets and backgrounds are also removed. Instead,
patients are looking at a blank screen to keep the training
time comparable. Most notably, the target placement
and difficult adaptation remain unaffected.
The clinical assessments are collected by assessors
blinded to treatment allocation. All assessors are trained
in performing the assessments before the start of the
trial. In addition to the outcome measures described
below, demographics, comorbidities, cognitive function
(Mini Mental State Examination) and concomitant
therapy will be recorded (Fig. 5).
The primary outcome of this trial is the workspace of
the impaired arm in the horizontal plane, measured by
using an assessment integrated into the ArmeoSenso
platform. Subjects are instructed to actively reach out as
far as possible with their impaired arm forward,
backward and sideways to explore the entire arm workspace.
The workspace is corrected for trunk movements and
computed as the number of square pixels of 10-cm side
length arranged in the transverse plane relative to the
patient’s trunk (Fig. 2b) (see Wittmann et al. [
Wittmann et al. [
] for more information). This
assessment is conducted immediately before and after every
therapy session (Fig. 5).
Arm impairment is assessed using the Fugl-Meyer
Assessment-Upper Extremity (FMA-UE), arm activity
using the Wolf Motor Function Test (WMFT), the Box
and Block Test and a pointing task (ArmeoSenso
integrated assessment) (Fig. 5). For the pointing task, nine
targets arranged in two semicircles appear one after
another in the transversal plane in front of the subject. The
goal is to reach out to the target within 8 s. The number
of targets reached and the mean time to target is
reported. The Motor Activity Log 14 (MAL-14) for
selfreported movement ability, the Barthel Index (BI) as a
measure of independence in daily living, the National
Institutes of Health Stroke Scale (NIHSS) as a measure of
stroke severity are recorded and the global disability is
assessed using the modified Rankin Scale (mRS) (Fig. 5).
Finally, patients fill in a short questionnaire after each
training session. Ten questions (five positively and five
negatively formulated), given in randomized order,
evaluate the subjective appraisal of the training on a
five-point Likert scale (Fig. 5).
Assessments of safety
Adverse events (AEs) expected to occur are skeletal or
muscular pain and fatigue indicating a syndrome of
overuse. The quality management system of the Clinical
Trial Center Zurich will be followed according to
national and international guidelines [
]. Adverse events
(AEs) will be documented and related serious adverse
events (SAEs) will be reported to the Ethical Committee,
the competent authority (Swissmedic) and local principle
investigators (PIs). All SAEs will be included in an
annual report to authorities and PIs. AEs will be recorded
from baseline assessment to the end of the trial (Fig. 5).
The sample size is estimated to detect a between-group
difference of 4.8 voxels in the workspace difference from
beginning to end of training, based on the improvement
in arm workspace from pilot results (unpublished) and
an estimated group difference of 20%. This assumes a
two-sided alpha level at .05 and a power of 80%. For an
effect with a standard deviation of seven voxels, 35
subjects per group yields 80% power to detect the true
alternative. We will randomize 37 subjects in each group,
based on our observed attrition rate of 5% in a previous
interventional trial [
]. This calculation was performed
using G*Power 3.1 [
Our primary analysis is an intention-to-treat analysis
comparing the two groups. In addition, as this is an
explanatory trial, a per-protocol analysis will be used to
analyze the effect of feedback under ideal conditions
]. Therapy will take place in 15 sessions over
3 weeks, and there is the possibility that some subjects
will not complete the full treatment regimen due to
scheduling issues or other time constraints. If they still
perform at least 12 h of therapy the data will be analyzed.
All other patients will be considered “non-compliant” in
the sense that they do not receive the full treatment dose.
According to the per-protocol principle, their outcomes
will not be analyzed.
A two-sample t test comparing the mean change in
voxel workspace assessment between the two groups will
be used; in case of non-normality, a Mann-Whitney test
will be computed instead. Moreover, repeated measures
analysis of variance (ANOVAs), in case of normally
distributed data, or non-parametric Friedman tests will be
used to assess the development of the different outcome
measures over time. Statistical significance will be based
on a p value threshold of 0.05. Data will be analyzed
using MATLAB R2013b (or newer) (MathWorks Inc.,
Natick, MA, USA) and SPSS (version 23 (or newer),
IBM Corp., Armonk, NY, USA).
This is the first randomized clinical trial to evaluate the
effect of enhanced feedback and reward on arm
rehabilitative training following stroke. Intrinsic (score,
knowledge of performance) and extrinsic rewards (money)
hypothetically improve motor cortex plasticity and
overall motivation to train. Because motivation affects
training time and time is a crucial determinant of effect [
this trial controls for time by using a control
intervention that is matched in time and dose of training.
In a motor learning study with healthy young subjects,
we have shown that the consolidation/retention of a
skilled motor task is more effective if the task was
trained in the presence of reward [
]. In a rat model,
projections from midbrain dopaminergic regions to M1
are required for successful motor learning and functional
plasticity at cortical (layer II/III) synapses [
mechanisms that presumably support recovery after
stroke . Whether the dopaminergic system can be
stimulated to improve recovery remains to be shown.
Likewise, whether reward is an appropriate stimulus is
Previous studies have assessed the patient’s motivation
for a specific training (e.g., Wittmann et al. [
Nijenhuis et al. [
]), but none of them compared the
outcome to an appropriate control condition for the
evaluation of the effectiveness of rewarding therapy.
Although functional improvement itself might be
motivating enough for some patients to train, here we are in
search of a clinical effect of reward on a reduction in
impairment (shoulder/elbow range of motion (ROM))
mediated by active and repetitive proximal-arm training.
We chose this training method because (1) it can be
standardized in its conduct and has quantifiable
parameters of dose, movement success and arm workspace as
primary outcome measure, (2) it is based on a therapy
system which was already evaluated with patients and
found to be safe, (3) it is easily supported in participating
institutions without much training of therapists who
provide assistance to the patient and (4) it has shown a
moderate effect on chronically arm-impaired stroke
]. Because the ArmeoSenso training only works
on proximal-arm function, it is not expected to have a
clinically relevant effect on activities of daily living,
independence, or quality of life. We therefore chose a
primary outcome that is close to what is actually being
trained, i.e., arm workspace. Workspace assessments
have been widely used to assess the arm function of
stroke patients, thereby showing high correlation to
standard clinical scales [
]. For a discussion of
clinical relevance of functional outcomes, in the interest of
clarity and conciseness, we would like to refer to the
review by Ashford et al. . Nevertheless, potential
transfer to more clinical scores can be tracked using our
secondary outcome measures.
The study is enrolling subjects during the initial
3 months after stroke. Most recovery is occurring in this
]. Therefore, we expect an improvement in
arm function in both groups.
A positive outcome of this trial will emphasize the role
of reward in rehabilitative training. This result could
potentially be applicable to various forms of post-stroke
rehabilitative training. Social rewards (smileys, praise),
food rewards (sweets, dietary allowance), monetary reward
or token programs are options that are easy to implement
in situations where there is systematic interaction between
a patient and a human trainer or a technical training
device. Virtual-reality-based training games, therapy
elements including repetitive performance feedback and
similar approaches are examples where to integrate
reward according to suggestions to be derived from the
The trial is currently recruiting patients. At the time of
submission, 16 stroke patients have been enrolled.
Additional file 1: SPIRIT 2013 Checklist. (DOC 121 kb)
Additional file 2: Informed Consent Form (German). (PDF 331 kb)
AEs: Adverse events; BI: Barthel Index; EKNZ: Ethikkommission Nordwest- und
Zentralschweiz; FMA-UE: Fugl-Meyer Assessment of the upper extremity;
GCP: Good Clinical Practice; IDs: Identification numbers; IMU: Inertial
measurement unit; M1: Primary motor cortex; MAL14: Motor Activity Log 14;
mRS: modified Rankin Scale; NIHSS: National Institutes of Health Stroke Scale;
PIs: Principle investigators; RCT: Randomized controlled trial; ROM: Range of
motion; SAEs: Serious adverse events; VR: Virtual reality; WMFT: Wolf Motor
The authors would like to thank Mark van Raai for his help in the implementation
of the ArmeoSenso software, and Irene Christen, Jose Lopez and Belen Valladares
for their support with the study.
This work was supported by the Clinical Research Priority Program (CRPP)
NeuroRehab of the University of Zurich, the P&K Pühringer Foundation and
the ETH Foundation (ETH Research Grant ET-17 13-2).
Availability of data and materials
For Informed Consent Form (German), see Additional file 2.
MW and JPH drafted the manuscript. ARL sponsors the study. MW, JPH, KL,
ARL, OL and FW participated in the study design and definition of requirements.
MW, KL and FW implemented the therapy system. All authors read and
approved the final manuscript.
Ethics approval and consent to participate
The study will follow Good Clinical practice (GCP) guidelines and has been
approved by the responsible local Ethics Committees “Ethikkommission
Nordwest- und Zentralschweiz,” the “Kantonale Ethikkommission Zürich”
(LU2013-079 and PB_2016-01804) and the Swiss Agency for Therapeutic
Products (Swissmedic: 2014-MD-0033). All subjects have to give written
informed consent in accordance with the Declaration of Helsinki.
Consent for publication
Written informed consent was obtained from the participant (Fig. 2a) for
publication of this photograph in this manuscript. The Informed Consent
Form is held by the authors and is available for review by the Editor-in-Chief.
Andreas R. Luft is a scientific advisor to Hocoma AG (Volketswil). The remaining
authors have no conflict of interest in the submission of this manuscript.
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