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Original Paper
Haptic Nudges Increase Affected Upper Limb Movement During
Inpatient Stroke Rehabilitation:Multiple-Period Randomized
Crossover Study
Nada Elizabeth June Signal1, BHSc, MHSc, PhD; Ruth McLaren1, BHSc, MHPrac; Usman Rashid1, BEng, MSc,
PhD; Alain Vandal2, MA, PhD; Marcus King3, BE; Faisal Almesfer4, BE, ME; Jeanette Henderson5, BHSc; Denise
Taylor1, BPhys, MSc, PhD
1Health and Rehabilitation Research Institute, Auckland University of Technology, Auckland, New Zealand
2Department of Statistics, University of Auckland, Auckland, New Zealand
3Callaghan Innovation, Christchurch, New Zealand
4Exsurgo Rehabilitation, Auckland, New Zealand
5Assessment, Treatment and Rehabilitation Department, Waitakere Hospital, Waitemata District Health Board, Auckland, New Zealand
Corresponding Author:
Nada Elizabeth June Signal, BHSc, MHSc, PhD
Health and Rehabilitation Research Institute
Auckland University of Technology
90 Akoranga Drive
Northcote
Auckland, 0627
New Zealand
Phone: 64 21929144
Email: nada.signal@aut.ac.nz
Abstract
Background: As many as 80% of stroke survivors experience upper limb (UL) disability. The strong relationships between
disability, lost productivity, and ongoing health care costs mean reducing disability after stroke is critical at both individual and
society levels. Unfortunately, the amount of UL-focused rehabilitation received by people with stroke is extremely low. Activity
monitoring and promotion using wearable devices offer a potential technology-based solution to address this gap. Commonly,
wearable devices are used to deliver a haptic nudge to the wearer with the aim of promoting a particular behavior. However, little
is known about the effectiveness of haptic nudging in promoting behaviors in patient populations.
Objective: This study aimed to estimate the effect of haptic nudging delivered via a wrist-worn wearable device on UL movement
in people with UL disability following stroke undertaking inpatient rehabilitation.
Methods: A multiple-period randomized crossover design was used to measure the association of UL movement with the
occurrence of haptic nudge reminders to move the affected UL in 20 people with stroke undertaking inpatient rehabilitation. UL
movement was observed and classified using movement taxonomy across 72 one-minute observation periods from 7:00 AM to
7:00 PM on a single weekday. On 36 occasions, a haptic nudge to move the affected UL was provided just before the observation
period. On the other 36 occasions, no haptic nudge was given. The timing of the haptic nudge was randomized across the
observation period for each participant. Statistical analysis was performed using mixed logistic regression. The effect of a haptic
nudge was evaluated from the intention-to-treat dataset as the ratio of the odds of affected UL movement during the observation
period following a “Planned Nudge” to the odds of affected limb movement during the observation period following “No Nudge.”
Results: The primary intention-to-treat analysis showed the odds ratio (OR) of affected UL movement following a haptic nudge
was 1.44 (95% CI 1.28-1.63, P<.001). The secondary analysis revealed an increased odds of affected UL movement following
a Planned Nudge was predominantly due to increased odds of spontaneous affected UL movement (OR 2.03, 95% CI 1.65-2.51,
P<.001) rather than affected UL movement in conjunction with unaffected UL movement (OR 1.13, 95% CI 0.99-1.29, P=.07).
Conclusions: Haptic nudging delivered via a wrist-worn wearable device increases affected UL movement in people with UL
disability following stroke undertaking inpatient rehabilitation. The promoted movement appears to be specific to the instructions
given.
JMIR Mhealth Uhealth 2020 | vol. 8 | iss. 7 | e17036 | p. 1https://mhealth.jmir.org/2020/7/e17036 (page number not for citation purposes)
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Trial Registration: Australia New Zealand Clinical Trials Registry 12616000654459;
https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370687&isReview=true
(JMIR Mhealth Uhealth 2020;8(7):e17036) doi: 10.2196/17036
KEYWORDS
stroke; rehabilitation; physical activity; movement; disability; technology; upper limb; wearable; haptic; nudge
Introduction
Although the incidence of stroke has reduced, its burden
continues to grow as more people are surviving after stroke and
living with disability [1]. Direct and indirect health care costs
following stroke are strongly correlated with stroke disability,
with greater disability associated with greater costs [2,3].
Around 80% of stroke survivors experience upper limb (UL)
disability, with only 5%-20% achieving full recovery of UL
function [4-6]. UL disability has subsequent impacts on
independence in activities of daily living, discharge destination,
return to work, quality of life, and mood [7-10].
Effective rehabilitation involves high-dose, intensive,
task-specific activity [11]. Meta-analyses of randomized
controlled trials suggest there is a dose-response relationship,
with higher doses of rehabilitation resulting in better outcomes
[12-14]. However, studies describing usual stroke care illustrate
that the dose of UL rehabilitation received by people with stroke
is extremely low, with as little as 4-6 minutes in physiotherapy
sessions and 11-17 minutes in occupational therapy sessions
[15]. Movement of the affected UL outside formal therapy
sessions during inpatient rehabilitation is also low [16].
Consequently, affected UL movement dose, both within formal
therapy sessions and across the rehabilitation day, is currently
insufficient to reduce UL disability following stroke.
Rehabilitation technologies have been proposed as potential
solutions to the limited dose of rehabilitation this population
receives [17]. A number of technological solutions have been
developed for use in UL stroke rehabilitation, including virtual
reality, gaming, and robotics [17-19]. Despite indications of
effectiveness [20,21], the use of rehabilitation technologies is
not yet pervasive in stroke care [18]. Therapists have identified
several barriers to adopting rehabilitation technologies, including
concerns about patient safety, whether the technology effectively
addresses a clinical need, and the feasibility of technologies
from time, space, and cost perspectives [22,23]. The poor uptake
of rehabilitation technologies is inconsistent with research
involving people with stroke that indicates rehabilitation
technologies can support engagement and interest in performing
repetitive rehabilitation activities and offer a means of social
support [19,24,25]. Activity monitoring and promotion using
wearable devices is a potential low-cost and feasible
rehabilitation technology. Research investigating the effect of
wearable devices on outcomes following stroke is in its infancy.
Preliminary indications suggest that wearable devices may
increase the amount and intensity of physical activity undertaken
during rehabilitation [26-28] and potentially contribute to
improved functional outcomes [29]. However, the effect of
wearable devices on UL rehabilitation and outcomes has been
less well studied [30,31], with much of the research to date
focusing on the accuracy and validity of accelerometry
measurement of real-world UL movement [32-34].
Wearable devices that deliver haptic nudges have been used to
promote physical activity in both healthy and patient populations
[35-39]. Commonly, a haptic nudge reminder is delivered via
a small motor embedded inside a wearable device. Wearers are
encouraged to respond to a haptic reminder by performing a
particular behavior. For example, a haptic nudge might be used
to remind the wearer to stand up and move after an extended
period of sitting or to undertake rehabilitation exercises.
However, despite the pervasiveness of haptic nudging in
consumer wearable devices, there remains much to learn about
the effectiveness of haptic nudging in promoting behaviors in
patient populations. Haptic nudges have been used to effectively
promote behaviors in people with autism spectrum disorder [40]
and traumatic brain injury engaged in a rehabilitation task [41].
Research also suggests that wearable devices are feasible and
well tolerated in people with stroke [30,42,43], with preliminary
data indicating haptic nudging via wearable devices may
promote affected UL movement [31]. The aim of this study was
to estimate the effect of haptic nudging delivered via a
wrist-worn wearable device on UL movement in people with
UL disability following stroke undertaking inpatient
rehabilitation.
Methods
Study Design
A multiple-period randomized crossover design was used to
measure the association of UL movement with the occurrence
of haptic nudge reminders to move the affected UL in 20 people
with stroke undertaking inpatient rehabilitation. UL movement
was observed and classified using movement taxonomy across
72 one-minute observation periods from 7:00 am to 7:00 pm
on a single weekday. On 36 occasions, a haptic nudge (Nudge)
to move the affected UL was provided just before the
observation period, and on the other 36 occasions, no haptic
nudge was given (No Nudge). The timing of the haptic nudge
was randomized. Approval for this study was obtained from the
New Zealand Health and Disability Ethics Committee
(16/NTA/74).
Participants
All people with stroke admitted to the rehabilitation service
from July 2018 through December 2018 were considered for
inclusion in this study. Participants were included if they had
a confirmed diagnosis of stroke based on the Oxford
classification system [44], presented with UL deficit as a result
of stroke as determined by their rehabilitation therapist, were
deemed medically stable and fit for rehabilitation by their
medical consultant, and provided written informed consent.
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Participants were excluded if they had cognitive, behavioral, or
communication impairments that, in the opinion of the research
team (RM, DT, NS), would limit their ability to participate in
the research (for example, if the person was unable to follow a
2-step verbal command or recall the details of the research
study); were within 3 days of planned discharge from inpatient
rehabilitation; or reported shoulder pain.
Procedure
Potential participants were identified and referred to the research
team by their rehabilitation therapist. They were then informed
about the study and screened against the inclusion and exclusion
criteria by a trained research assistant. Eligible participants
provided written informed consent and identified a mutually
agreeable day for data collection. Demographic, clinical, and
medical information was gathered from the medical record of
consenting participants by the rehabilitation therapist. Collected
data included age, sex, ethnicity, date of stroke, type of stroke,
side of body most affected, dominant hand prior to stroke, date
of admission to the rehabilitation ward, estimated date of
discharge, comorbidities, and medications.
On the day of data collection, the participant was fitted with a
BuzzNudge wearable device on the wrist of the affected UL.
The BuzzNudge is a Bluetooth-enabled wearable device with
a 2.3 V coin vibration motor (Precision Microdrives Ltd, Model
310-103), which provided 3 consecutive vibratory stimuli of
0.3 seconds duration at 150 Hz within 1.5 seconds, representing
a similar magnitude of stimulus to the vibration of a phone. The
researcher explained the value of moving the affected UL after
stroke and instructed the participant to “move, try and move,
or visualize moving their (affected) arm” following a nudge.
The researcher emphasized that the participant should do
whatever movement they felt they could manage. If sensation
was impaired in the affected UL such that the participant could
not feel the haptic nudge, the device was worn on the less
affected UL, but the participant was still instructed to use the
haptic nudge as a reminder to move the affected UL.
During data collection, participants were followed discreetly
out of their field of view around the rehabilitation ward, therapy
areas, and hospital facilities by a trained researcher (where
feasible). The researcher manually recorded UL movement for
1 minute every 10 minutes [45]. Each minute of observation
was broken into 6 epochs of 10 seconds using a silent interval
timer. UL movement was classified according to a previously
defined taxonomy: (1) unilateral affected UL movement; (2)
unilateral unaffected UL movement; (3) bimanual movement,
where movement of both ULs was observed to achieve a
common task or purpose; (4) bilateral limb movement, where
movement of both ULs was observed to achieve independent
or unrelated tasks; and (5) no movement [16]. When patients
were not able to be directly observed (ie, because curtains were
drawn or when in showers or toilets), activity was recorded after
conferring with the participant, staff, or family members, as
appropriate. In circumstances where the activity could not be
estimated (eg, during 4 randomly scheduled observer breaks),
activity was coded as unobserved [16,46].
Haptic nudge reminders were triggered by the researcher via
Bluetooth immediately before movement observation according
to a planned randomization schedule. For half of the observation
periods, a haptic nudge was to be provided, and for half, a haptic
nudge was not to be provided. Further details regarding the
randomization schedule are presented in Multimedia Appendix
1. Haptic nudges were not triggered if the participant was not
visible, the participant was asleep, or a nudge was considered
inappropriate (eg, if the participant was drinking a hot beverage
or undertaking an assessment procedure). Any scheduled nudge
that was not given was recorded as a “Missed Nudge.”
Statistical Analysis
Coded data were entered into a Microsoft Excel spreadsheet.
Descriptive analysis was used to examine the amount and type
of UL movement. If a participant withdrew from the study, their
movement observations were coded as missing values, and their
scheduled nudges were coded as Missed Nudges. Statistical
analysis was performed using mixed logistic regression. Total
affected UL movement was collated based on all observations
in which the affected UL was moved: total affected UL
movement = unilateral affected UL movement + bilateral limb
movement + bimanual movement.
In the primary analysis using the intention-to-treat dataset,
nudges were represented as a fixed effect factor with two levels:
Planned Nudge (ie, Nudge + Missed Nudge) and No Nudge,
meaning the analysis considered whether a nudge was planned
or not, rather than delivered. The effect of Planned Nudges was
evaluated as the ratio of the odds of affected UL movement
during the observation period following a Planned Nudge to
the odds of affected UL movement during the observation period
following No Nudge. More formally, the primary null hypothesis
tested with the model was: H0: ORPlanned Nudge/No Nudge = 1.
The sensitivity of the effect of the Planned Nudge to missing
values was tested with the pooled effect of 10 worst-case random
imputations at the level of the participant with the worst
outcomes.
In the secondary analysis using the intention-to-treat dataset,
two additional models were used to evaluate the effect of a
Planned Nudge on unilateral affected UL movement and the
sum of bilateral limb movement + bimanual movement,
respectively. A post-hoc exploratory analysis with an
instrumental variable approach was used to evaluate the local
average treatment effect (also known as complier average causal
effect) of the haptic nudge reminder. This analysis considered
the effect of the haptic nudge when delivered (Nudged)
compared with no haptic nudge (Not Nudged) irrespective of
the schedule on total affected UL movement. To explain the
variation in UL movement across the day, all models fitted the
data with smooth natural splines that had 1 degree of freedom
per hour. To account for correlated repeated measures, the
models included hierarchical random effects per participant and
per hour within participant. Statistical analyses were performed
using R version 3.5.1 (R Foundation for Statistical Computing,
Vienna, Austria) with lme4 version 1.1-21 [47], splines version
3.5.1 [48], and emmeans version 1.3.4 [39]. The threshold of
statistical significance was set at .05. A detailed statistical
analysis report containing code snippets and additional graphical
representations of data is available in Multimedia Appendix 1.
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Results
Participant Characteristics
In total, 20 people consented to participate in this study (Table
1). Participants’ median age was 76 years (IQR 68-83 years),
and the median time since stroke was 23.5 days (IQR 8.25-38.25
years); 9 participants had left hemiparesis, 10 had right
hemiparesis, and 1 participant had bilateral symptoms with the
left UL more affected than the right. Five participants had total
anterior circulation syndrome, 10 had partial anterior circulation
syndrome, 4 had lacunar circulation syndrome, and 1 had
posterior circulation syndrome. Of the participating patients, 4
had hemorrhagic stroke, and 16 had ischemic stroke. Participant
2 was withdrawn from the study when 6 nudges in a row were
unable to be delivered due to a technical error. Participant 6
asked to withdraw 20 minutes into data collection due to
experiencing anxiety associated with wearing the device.
Table 1. Participant demographics.
Device worn on AULAUL = dominant ULb
AULa
Days since strokeStroke classificationGenderAge range (years)Participant
YesNoLeft9LACS-Ic
Male70-791
YesNoLeft39TACS-Ie
Female80-892d
YesNoLeft59TACS-IFemale70-793
YesYesRight8LACS-Hf
Female40-494
YesYesRight5PACS-Ig
Female60-695
YesNoLeft34PACS-IMale80-896d
YesYesRight27TACS-IMale70-797
YesNoLeft7PACS-IFemale80-898
YesYesRight67TACS-IMale80-899
YesYesRight36PACS-IMale60-6910
YesYesLeft25TACS-IFemale50-5911
NoNoLeft33LACS-HMale70-7912
YesNoLeft12PACS-IMale80-8913
NoYesRight3LACS-IMale60-6914
YesYesRight40PACS-Hh
Male70-7915
YesYesRight22PACS-IFemale80-8916
YesNoLeft6PACS-IFemale60-6917
YesYes
Bilater-
al10POCS-Ii
Male60-6918
YesYesRight9PACS-IMale80-8919
YesYesRight160PACS-HMale80-8920
aAUL: affected upper limb.
bUL: upper limb.
cLACS-I: lacunar circulation syndrome ischemic.
dParticipant withdrawn.
eTACS-I: total anterior circulation syndrome ischemic.
fLACS-H: lacunar circulation syndrome hemorrhagic.
gPACS-I: partial anterior circulation syndrome ischemic.
hPACS-H: partial anterior circulation syndrome hemorrhagic.
iPOCS-I: posterior circulation syndrome ischemic.
Data Completeness
In total, 7517 of a possible 8640 observations of movement in
10-second time intervals were recorded across the 20
participants (median 414 observations/participant, IQR 402-420
observations/participant, range 12-432 observations/participant),
representing data completeness of 87.0%. Data loss was due to
the 2 participants who withdrew (769/8640 observations, 8.9%)
and the remaining participants being away from the service for
appointments or involved in private personal hygiene activities
(354/8640 observations, 4.1%).
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Of the 720 Planned Nudges, 32.6% (235 Nudges) were not
delivered (Missed Nudge), with 8.7% (63/720 Nudges) ascribed
to the 2 participants that withdrew. For the remaining Missed
Nudges, participants were sleeping for 12.6% (90/720) of the
Planned Nudges; Nudges could not be directly observed for
6.7% (48/720) of the Planned Nudges; a nudge was deemed
inappropriate for 2.8% (20/720) of the Planned Nudges; a
technical error prevented nudging for 1.4% (10/720) of the
Planned Nudges; and the reason was not stated for 0.4% (3/720)
of the Planned Nudges.
UL Movement
During observations without a nudge scheduled (No Nudge),
the affected UL moved 19.2% of the time; 15.6% of movement
occurred in conjunction with the unaffected UL, and only 3.6%
of the time the movement was of the affected UL by itself. The
unaffected UL moved 39.2% of the time, with half of this
movement (23.6%) being movement of the unaffected UL by
itself. Participants used one or both ULs for 42.8% of the
observation time.
Haptic Nudge Effect
The results of the statistical analyses are presented in Table 2.
The treatment effect of the intervention is represented by the
odds ratio (OR) for Planned Nudge versus No Nudge. This OR
indicated that the odds of moving the affected UL either
independently (unilateral affected UL movement) or in concert
with the unaffected limb (bimanual movement or bilateral limb
movement) was 1.44 times greater following a Planned Nudge
than following No Nudge. The proportions estimated by the
model for the affected UL movement (unilateral affected UL
movement + bilateral limb movement + bimanual movement)
recorded during the observation periods following a Planned
Nudge and No Nudge were 26.7% (95% CI 15.4%-42.2%) and
20.2% (95% CI 11.2%-33.6%), respectively. Therefore, the
average absolute increase in the proportion of affected UL
movement with the intervention was 6.5% (95% CI 4.2%-8.6%),
representing an increase of 32.2% in average activity. The
sensitivity analysis showed that the effect of the Planned Nudge
on unilateral affected UL movement + bilateral limb movement
+ bimanual movement was robust to missing values (P<.001).
The proportion of observation periods with affected UL
movement following Planned Nudges and No Nudges by
participants is represented in Table 3.
The secondary analysis revealed that the odds of moving the
affected UL independently (unilateral affected UL movement)
was 2.03 times greater following a Planned Nudge than
following No Nudge. However, the OR for either bilateral or
bimanual movement (bilateral limb movement + bimanual
movement) was only 1.13 times greater. The exploratory
analysis revealed that the OR for the effect of the haptic nudge
when delivered (Nudged) compared with no haptic nudge (Not
Nudged) irrespective of the schedule was 1.64.
Table 2. Odds of an affected upper limb (UL) movement recorded during the observation periods.
PvalueZ valueStandard error95% CIOdds ratioEstimate
Planned nudge/no nudge
<.0015.860.091.28-1.631.44
Primary analysis: AUa+BiLb+BiMc
<.0014.40.081.16-1.461.30Sensitivity analysis: AU+BiL+BiM
<.0016.650.221.65-2.512.03Secondary analysis: AU
.071.800.080.99-1.291.13Secondary analysis: BiL+BiM
Nudged/not nudged
<.0016.770.121.42-1.891.64Exploratory analysis: AU+BiL+BiM
aAU: unilateral affected upper limb movement.
bBiL: bilateral limb movement.
cBiM: bimanual movement.
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Table 3. Proportion of observations with affected upper limb movment (unilateral affected upper limb movement + bilateral limb movement + bimanual
movement) following No Nudge and Planned Nudge.
Planned Nudge (%)No Nudge (%)Participant
11.117.411
0.001.85
2a
30.0926.393
13.893.244
52.3146.305
0.003.70
6a
12.9618.067
38.8935.198
5.561.399
9.2616.6710
7.875.5611
0.936.4812
37.9630.0913
42.1315.7414
39.3520.8315
43.9832.8716
37.9623.6117
24.5438.8918
43.0625.9319
16.6723.6120
aParticipant withdrawn.
Discussion
Principal Findings
This multiple-period randomized crossover study explored the
effect of haptic nudging on UL movement in people with stroke.
Haptic nudging increased the likelihood that a person with stroke
moved their affected UL by 1.44 times (P<.001) during the
subacute rehabilitation phase. Haptic nudging resulted in a
relative increase in the proportion of affected UL movement of
32.2%. The actual amount and type of UL movement observed
without nudging in our study was comparable with our
previously published research [16] and other observational
studies [33,46]. This strengthens the assertion that haptic nudges
influence the amount of affected UL movement in people with
stroke. This study is the first to specifically investigate whether
haptic nudges delivered by a wrist-worn wearable device
influence the amount of UL movement undertaken during
rehabilitation following stroke. Given the limited amount of
spontaneous UL movement following stroke [16,46,49] and the
challenges associated with increasing the dose of UL
rehabilitation [15,50], these research findings indicate that haptic
nudging represents a potentially powerful stroke rehabilitation
tool that could be easily implemented in clinical practice.
Our secondary analysis clarified the type of UL movement
promoted by haptic nudging. Participants were 2.03 times more
likely to move their affected UL in isolation (unilateral affected
UL movement) following a haptic nudge compared with moving
the affected UL in concert with the unaffected UL (bimanual
movement + bilateral limb movement), which was just 1.13
times more likely. Given that participants were instructed to
move their affected UL rather than both limbs together, the
instructions related to haptic nudging may be important in
determining exactly which movements are promoted. This
specificity in effect has been noted in other studies in which
people with stroke altered their behavior in response to feedback.
Dobkin and Plummer-D'Amato [51] gave daily feedback in
relation to gait speed to people with stroke undertaking
rehabilitation. They reported the feedback group had
significantly increased gait speed but did not change walking
endurance or independence compared with the control group
(usual care). Our study contributes to the growing body of
research suggesting that drawing attention to specific aspects
of movement and physical activity throughout the rehabilitation
day can influence patient behavior during stroke rehabilitation
[26-31].
The greater odds of moving the affected UL in the minute
following a planned nudge resulted in a 32.2% increase in the
average amount of movement. Another small-scale
proof-of-concept study involving people with stroke (n=7) [30]
indicated an increase of 19.7% in the average amount of affected
UL movement in the hour following a haptic nudge reminder
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to undertake exercises. In that study, participants were instructed
to perform up to 80 repetitions of task-specific training in
response to a haptic nudge, but only received a median of 4
nudges across the rehabilitation day. In contrast, participants in
our study received an average of 27 haptic nudges and were
instructed to move, try to move, or think about moving their
affected UL following a nudge. It is not yet known how the
frequency of nudges, burden of the required behavioral response,
and capacity to integrate that response into everyday activities
influence the magnitude and duration of the haptic nudge effect
in people with stroke.
Results for individual participants illustrated that there was
considerable variability in response to haptic nudging. For
example, 13 participants increased the amount of movement of
their affected UL in response to nudging, with 8 exhibiting large
relative increases. In contrast, 5 participants had a reduction in
the amount of affected UL movement in response to haptic
nudging. There appeared to be no relationship between
individual response and participant age, stroke severity,
hemiplegic side, or whether the hemiplegic side was the
dominant hand. Although the researchers checked that the
participant understood the instruction to move the affected UL
in response to haptic nudging at the beginning of data collection,
it remains unclear whether cognitive, communication,
perceptual, or sensory deficits influenced participants’ ability
to attend and respond to the nudge. Other nudging modalities
(eg, auditory tones, lights, and text messaging) may be effective
and more appropriate than haptic vibration for some people
with stroke [52]. In addition, we relied on observation of
movement, and it was not possible to determine whether
participants who were more severely affected were attempting
to or thinking about moving their affected UL. This could be
addressed in future research by using alternative data collection
methods such as ecological momentary assessment [53] or
electroencephalography to determine movement intention [54].
One participant who had moved less in response to haptic
nudging had a cerebellar stroke that influenced UL movement
bilaterally; advocating increased movement of the more affected
limb might have been inappropriate in that case. The relationship
between haptic nudge efficacy and clinical and demographic
factors requires further investigation to ensure that this type of
technology is used appropriately.
The magnitude of effect in response to haptic nudging might
have been underestimated in our study given that we included
observations in which planned nudges were not delivered
(Missed Nudges), for example, when a participant was asleep
or not visible to the researcher. This assertion was supported
by the exploratory analysis that revealed the OR for the effect
of the scheduled nudge when actually delivered compared with
no haptic nudge was 1.64. It is also noteworthy that our
participants were advised of the value of moving the affected
UL after stroke on a single occasion. The effect of haptic
nudging may be enhanced by providing regular positively
framed information on the consequences of nudged behavior
(eg, “more movement promotes recovery”), encouraging explicit
action planning (eg, “I will move my affected arm by…when I
feel the nudge”), repeated practice of the desired behavioral
response to the haptic nudge, and tracking and reporting the
desired behavior [35,55,56]. In commercial wearable devices,
haptic nudging is commonly coupled with other behavior change
and persuasive strategies including education, gamification,
social support via social network services, and reward systems
[56,57]. It is likely that the magnitude of effect of a
comprehensive rehabilitation wearable technology that
incorporates haptic nudging with other behavioral change and
persuasive strategies would have a larger effect than the effect
of haptic nudging alone, as estimated in this study [35,58,59].
This study sought to investigate the effect of haptic nudging on
UL movement across an inpatient rehabilitation day; we did not
explore the effect on UL movement over a longer timeframe or
in a community setting. It is possible that people with stroke
habituate or become less responsive to haptic nudging with
everyday use. Conversely, they may learn to respond to haptic
nudging more effectively over time. Understanding the effect
over time is important, as increasing the dose of upper limb
movement to a therapeutic level through continued engagement
over a matter of weeks to months is likely required to promote
functional gains. In the subacute phase following stroke,
adherence to wearable devices has been reported as high [31,42],
although use appears to dwindle over time [42]. This is
consistent with studies in healthy community-dwelling people,
where half to two-thirds of purchasers continued to use wearable
devices 6 months after purchase [35,36]. In healthy populations,
uptake and ongoing use of such devices are influenced by
personal characteristics, including age, computer self-efficacy,
ease of use, usual levels of physical activity, internalization of
intention to change, and personality [36,60]. Although wearable
devices have been found to be acceptable to people with stroke
[61], one of our participants withdrew at the beginning of data
collection because wearing the device made him feel anxious.
Previous research indicates that the use of wearable technologies
may increase anxiety in clinical populations [62,63]. When
developing wearable devices to promote physical activity and
movement in people with stroke it may be important to consider
the personal and clinical characteristics of the intended users,
when and where in the continuum of care the device will be
used and for how long, and how users’ engagement and
adherence can be supported.
Limitations
A key limitation of this study was that the researcher observing
and recording movement was also responsible for triggering
the nudge and therefore not blinded to the intervention. While
the randomization schedule was designed to address lag, where
the effect of a nudge influences subsequent movement
observation periods (refer to Multimedia Appendix 1), the
duration of the nudge effect was unknown and might have
influenced subsequent observations. While participants were
blinded to the study hypothesis, it is possible that the research
protocol, particularly being observed by a researcher, may have
influenced the likelihood they moved in response to the haptic
nudge. Documentation of the number of potential participants
screened and the reasons for exclusion from the study would
have helped to interpret the external validity of the study
findings. A more detailed evaluation of the included participants’
sensorimotor, perceptual, cognitive, and communication
impairments along with measurement of their UL functional
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abilities may have allowed for a more nuanced interpretation
of the effect of haptic nudging in people with different clinical
presentations of stroke.
Conclusions
Haptic nudging increased the likelihood that a person with stroke
moved their affected UL by 1.44 times. This equated to an
increase of 32% in the average amount of affected UL
movement. Participants were twice (OR 2.03) as likely to move
their affected UL in isolation (unilateral affected UL movement)
in response to haptic nudging, compared with movement in
conjunction with the unaffected UL (OR 1.13), indicating that
the effect of haptic nudging was specific to the behavioral
instructions given. Given the limited amount of spontaneous
UL movement following stroke and the challenges associated
with increasing the dose of UL rehabilitation, haptic nudging
as part of a comprehensive wearable device aimed at increasing
the dose of UL movement represents a potentially powerful
stroke rehabilitation tool.
Acknowledgments
This research was funded by a grant from the New Zealand Medical Technologies Centre of Research Excellence. The authors
are grateful to the Waitemata District Health Board and the staff of the rehabilitation service at Waitakere Hospital who supported
this research. Simon Tse, Rohil Chauhan, Shikha Chaudhary, Abdallah Abou El Ela, and Nicole Wallen contributed to data
collection.
Authors' Contributions
NS, DT, and MK conceptualized the study and acquired funding. DT, AV, RM, and NS designed the methodology, and RM, DT,
and NS performed project administration. RM and JH collected the data, and MK and FA were responsible for the technology.
Data analysis was performed by UR and AV, and UR created the visualizations. Supervision was performed by NS and DT. The
original draft was written by NS, RM, and UR, and all authors reviewed and edited the manuscript.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Statistical analysis for the haptic nudge study.
[PDF File (Adobe PDF File), 738 KB-Multimedia Appendix 1]
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Abbreviations
AU: unilateral affected upper limb movement.
AUL: affected upper limb.
BiL: bilateral limb movement.
BiM: bimanual movement.
LACS-H: lacunar circulation syndrome hemorrhagic.
LACS-I: lacunar circulation syndrome ischemic.
OR: odds ratio.
PACS-H: partial anterior circulation syndrome hemorrhagic.
PACS-I: partial anterior circulation syndrome ischemic.
POCS-I: posterior circulation syndrome ischemic.
TACS-I: total anterior circulation syndrome ischemic.
UL: upper limb.
Edited by G Eysenbach; submitted 12.11.19; peer-reviewed by M Whelan, K Ng, N Cecilia; comments to author 10.01.20; revised
version received 15.03.20; accepted 13.05.20; published 29.07.20
Please cite as:
Signal NEJ, McLaren R, Rashid U, Vandal A, King M, Almesfer F, Henderson J, Taylor D
Haptic Nudges Increase Affected Upper Limb Movement During Inpatient Stroke Rehabilitation: Multiple-Period Randomized
Crossover Study
JMIR Mhealth Uhealth 2020;8(7):e17036
URL: https://mhealth.jmir.org/2020/7/e17036
doi: 10.2196/17036
PMID:
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©Nada Elizabeth June Signal, Ruth McLaren, Usman Rashid, Alain Vandal, Marcus King, Faisal Almesfer, Jeanette Henderson,
Denise Taylor. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 29.07.2020. This is an open-access
article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/),
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