# Feasibility and Acceptability of Remote Neuromotor Rehabilitation
Interactions Using Social Robot Augmented Telepresence: A Case Study

Michael J. Sobrepera, Member, IEEE1, Vera G. Lee2,
Suveer Garg3, and Michelle J. Johnson, Ph.D., Member, IEEE4 This work was
supported by the Department of Physical Medicine and Rehabilitation at the
University of Pennsylvania and by the Eunice Kennedy Shriver National
Institute of Child Health & Human Development of the National Institutes of
Health (NIH) under Award Number F31HD102165. The content does not necessarily
represent the views of the NIH.1Michael J. Sobrepera is with the School of
Engineering and Applied Sciences, Department of Mechanical Engineering and
Applied Mechanics, University of Pennsylvania, Philadelphia, PA, USA
<EMAIL_ADDRESS>G. Lee was with the School of Engineering and
Applied Sciences, Department of General Robotics, Automation, Sensing, &
Perception (GRASP), University of Pennsylvania, Philadelphia, PA, USA and is
now with Johnson and Johnson, Raritan, New Jersey, United States
<EMAIL_ADDRESS>Garg was with the School of Engineering and Applied
Sciences, Department of Electrical and Systems Engineering (ESE), University
of Pennsylvania, Philadelphia, PA, USA and is now with Samsung Research, New
York, NY, USA<EMAIL_ADDRESS>Michelle J. Johnson is an Associate
Professor with the Department of Physical Medicine and Rehabilitation and
BioEngineering. She directs the Rehab Robotics Lab (A GRASP Lab), University
of Pennsylvania, Philadelphia, PA, USA<EMAIL_ADDRESS>
###### Abstract

There is a growing need to deliver rehabilitation care to patients remotely.
Long term demographic changes, geographic shortages of care providers, and now
a global pandemic contribute to this need. Telepresence provides an option for
delivering this care. However, telepresence using video and audio alone does
not provide an interaction of the same quality as in-person. To bridge this
gap, we propose the use of social robot augmented telepresence (SRAT). We have
constructed a demonstration SRAT system for upper extremity rehab, in which a
humanoid, with a head, body, face, and arms, is attached to a mobile
telepresence system, to collaborate with the patient and clinicians as an
independent social entity. The humanoid can play games with the patient and
demonstrate activities. These activities could be used both to perform
assessments in support of self-directed rehab and to perform exercises.

In this paper, we present a case series with six subjects who completed
interactions with the robot, three subjects who have previously suffered a
stroke and three pediatric subjects who are typically developing. Subjects
performed a Simon Says activity and a target touch activity in person, using
classical telepresence (CT), and using SRAT. Subjects were able to effectively
work with the social robot guiding interactions and 5 of 6 rated SRAT better
than CT. This study demonstrates the feasibility of SRAT and some of its
benefits.

##  I INTRODUCTION

Growing shortages of neuromotor rehabilitation clinicians [1, 2] and changing
demographics present a challenge to delivering effective rehab care. Frequent
rehabilitation care is critical for convalescence from conditions such as
stroke and cerebral palsy (CP), which can limit a person’s ability to fully
interact with the world around them. One option for overcoming these
challenges is to provide rehab care using telepresence, i.e. telerehab, a
subcategory of telehealth, the remote delivery of health care using
telecommunications [3]. Telehealth has recently seen a large increase in use
as a result of the COVID-19 pandemic and related regulatory adjustments [4].
However, telehealth with video or audio alone does not provide as rich of an
interaction as in-person. Adding a social robot to interact with patients
during telehealth interactions may be able to improve those interactions.
Previous work has shown therapists believe adding a social robot to augment
telehealth would significantly improve communication with patients, patient
motivation, and patient compliance during telerehab interactions, compared to
traditional telepresence [5]. Such a system could be deployed at primary care
clinics, schools, or other locations in the community to provide access to
rehabilitation care for patients who can not otherwise access it locally. This
would enable patients to receive more frequent care without the cost and
difficulty of traveling to a distant center of rehab care excellence.

Figure 1: Flo: Social robot augmenting telepresence for remote rehabilitation.

Understanding how patients react to such systems will allow further
development and possibly lead to better care for patients. In this paper, we
present a case series evaluating the feasibility and acceptability of social
robot augmented telepresence (SRAT) for rehabilitation relevant activities,
using the social robot, Flo, a small humanoid, with a torso, head, arms, and
face. The humanoid rides on a mobile platform with a screen, cameras, and
microphones (fig. 1).

###  I-A Related Works

This work examines the combination of telerehabilitation and socially
assistive robots. Both have rich literature showing the promise of each for
delivering rehabilitation care.

####  I-A1 Social Robots for Upper Extremity Rehab

Social robots for rehabilitation are not new. They fall within the broader
category of socially assistive robots [6] which combine both assistive robots,
which support users with disabilities, and social robots, which are designed
to interact and communicate with humans. Several systems have been developed
for upper extremity rehabilitation, ex: The NT project uses a Nao robot to
interact with patients, and a Microsoft Kinect sensor to track patients,
allowing the robot to autonomously demonstrate and correct poses in a pose
mirroring game and in a pose sequence recall game. In a longitudinal study of
the system, with 13 subjects participating in on average 11.6 sessions, each
approximately 24 minutes long, clinicians, parents, and children, found the
system useful and wanted to continue to use it [7]. RAC CP Fun is another Nao
based robotic platform designed to engage with preschool students who have CP
by playing games and motivating physical activity. The robot interacts by
singing songs, changing its position relative to patients, and providing
feedback. Fridin et al. found that children with CP exhibited a higher level
of interaction with the robot than their typically developing peers, as
measured by eye contact as well as various facial, body, and vocal expressions
of emotion [8, 9]. The Bandit robot is a social robot which is targeted
towards older adults and is designed to monitor, instruct, evaluate, and
encourage patients while they do their rehab. In a multi-session study with 33
subjects, the robot was found to be effective at motivating physical exercise
[10].

####  I-A2 The importance of presence in interactions

Robots provide challenges in cost and complexity when being added to a
telepresence system. Why then are they worth pursuing?

Considerable evidence suggests that physical presence is important for
motivation, compliance, understanding, and enjoyment in both rehab and non-
rehab interactions. Fridin et al. demonstrated with RAC CP Fun that, comparing
an in-person robot and robot projected onto a screen, pediatric subjects
interacted significantly more with the in-person robot [11]. The Bandit robot
was also tested with subjects in physically present, virtually present, and
simulated presence conditions. The physically present condition was preferred
[10]. Bainbridge et al. showed that physical presence is important for trust
and motivation, especially for uncomfortable tasks [12], and Kiesler et al.
showed that subjects co-located with a physical robot were more engaged with
it and better followed diet advice when compared to a virtual agent [13].
Vasco et al. similarly found that stroke patients prefer using SARs for
rehabilitation therapy over virtual agents shown on a screen, reporting higher
engagement levels and exercise performance with the physical robot [14] Mann
et al. demonstrated that subjects were more likely to trust, be engaged with,
and follow instructions from a robot giving instructions and asking questions,
compared to the same interface on a tablet [15]. And Céspedes et al. showed
that simply adding a SAR onto a pre-existing neurorehabilitation device as a
third agent for motivation and engagement purposes has the potential to
increase performance [16].

####  I-A3 Telerehabilitation

Telepresence systems can be as simple as using a screen, camera, and Internet
connection via a cellphone, tablet, or computer, equipment which patients and
providers often already possess. Some systems include a mobile robotic base
which can be remotely controlled, such as the commercialized systems from
Double Robotics and VGo Communications. Others have robotic appendages to
communicate the operator’s intent [17] or screens which can actuate to face
the direction the operator is looking [18, 17].

There have been reported successes in telerehabilitation. For example,
Dodakian et al. presented a tabletop game system attached to a computer for
rehabilitation of stroke patients. By prompting the patient to play physical
games while monitoring movements over telepresence, patient compliance and
motivation was increased [19]. Abel et al. found that patients’ range of
motion can be effectively assessed over telepresence, and some patients may
prefer telehealth appointments for certain rehabilitation tasks, such as range
of motion assessments and wound tracking [20]. Preference is driven largely by
convenience. Bettger et al. compared a tele-physical therapy program for
therapy post total knee arthroplasty (n=143) with a traditional in-person
therapy program (n=144) for 12 weeks. The telerehab program had lower costs,
lower rates of rehospitalization, and was non-inferior in measures of rehab
outcomes when compared to the traditional program [21].

However, limitations associated with this technology, including field of view
of the operator (clinician), network latency, screen resolution, and
projection of three-dimensional interactions into two dimensions, lessen the
perception of the presence of the remote operator and reduce spatial reasoning
for both users (clinician and patient) [22, 18]. The resulting lack of
physical presence, coupled with unclear instructions for movements over
telepresence, may decrease patients’ compliance and motivation to perform
required motor assessment tasks and, as a result, limit the clinician’s
ability to assess the patient’s current function and progress and motivate
home therapy adherence. This highlights a need to develop platforms that have
a physical presence and can perform both assistive and social functions. With
the current pandemic, the need and call for telerehab systems has grown [23],
a need which will continue to grow with shifting demographics and future
unforeseen care challenges.

###  I-B Social Robot Augmented Telepresence

Recognizing the broad potential impact from telerehab and that some of the
challenges with telepresence could be overcome by using a socially assistive
robot, we propose to augment telerehab interactions with social robots. In a
previous study of 351 therapists in the United States, therapists reported
they believe social robot augmented telepresence (SRAT) would significantly
improve communication, motivation, and compliance during telerehab
interactions, compared to classical telepresence. To explore this new
direction in healthcare robotics, we have developed Flo, an example SRAT.

The system is comprised of a Kobuki drive base, two RealSense D415 cameras, a
screen, speakers, and a fisheye camera (fig. 1). A humanoid with a body, head,
arms, and a face can be placed onto the system and easily removed. This allows
the system to be used in both classical telepresence (CT) and SRAT
configurations. The system is controlled through a server via a remote web
interface by a plays and script methodology with wizard of oz control. The
humanoid can synthesize arbitrary speech using AWS Polly, and the face of the
humanoid can be dynamically changed [24]. More design details can be found in
[25].

Here we explore the feasibility of social robot augmented telepresence for
engaging in upper extremity rehabilitation activities, using the Flo platform
to compare SRAT to CT.

##  II PROCEDURE

The study was approved by the University of Pennsylvania Institutional Review
Board. In addition to consenting to participate in the study, all subjects
also provided an optional media release, allowing publication of their images.

###  II-A Demographics and Baselines

After consenting, subjects were assessed using the box and block test [26] to
measure unilateral gross manual dexterity, children’s color trails test for
pediatric subjects [27] and color trails test for adult subjects [28] to
measure visual attention, graphomotor sequencing, psychomotor speed, and
cognitive flexibility, as a proxy for executive cognitive function more
generally, and grip strength test [29] to measure hand and forearm strength as
a proxy for upper limb strength (fig. 2).

Figure 2: Subjects performing the clinical assessments at the beginning of the
trial. From left to right: the box and block test, color trails test, and grip
strength test.

Subjects, aided by a caretaker/parent if present, answered a survey asking:
basic demographics, history of cognitive and motor impairment, technology
usage, level of education, and current therapy practice and compliance, how
they are feeling today, and how they feel about robots. Surveys were
administered by a study team member, enabling data to be collected from
subjects of all ages and cognitive levels as well as allowing follow-up
questions to be asked.

###  II-B Conditions and Ordering

Subjects were randomly assigned to an ordering group. With FTF signifying
face-to-face (fig. 3), SRAT (fig. 4), and CT (fig. 5), the groups are: FTF-
SRAT-CT and FTF-CT-SRAT. Once the intake surveys were complete, the subject
was seated in a room. For the FTF condition, the operator entered the room and
sat on a chair, next to the telepresence system, which was not connected, but
used to gather video data, in front of the subject. For the SRAT/CT
conditions, the robot entered the room under remote control by the same
operator. This ordering sequence was used to give each subject a baseline
face-to-face experience to begin, as would likely happen in the real world,
before moving on to the telepresence modalities. Previous results have
suggested that when initial interactions are remote, results are poor [11].

Figure 3: Subject interacting in person with the operator (Condition FTF). On
the left, playing a Simon Says game. On the right, performing the target touch
activity.

Figure 4: Subject interacting with the operator via telepresence with a social
robot augmenting the interaction (Condition SRAT).

Figure 5: Subject interacting with the operator via classic telepresence
(Condition CT).

###  II-C Interaction

To begin each interaction, the operator introduced themselves and, in the SRAT
condition, the robot. The operator asked the subject if they wanted to play a
game. When the subject said yes: in the SRAT condition the robot said “great,
let’s play Simon Says” and explained how to play a game of Simon says, in the
CT/FTF conditions, the operator said “great, let’s play Simon Says” and
explained how to play a game of Simon Says. The game was played with the
subject moving through 20 motions with an additional 6 repeated motions where
there was no Simon Says command, with all instructions given by the robot in
the SRAT condition. The motions were identical in all conditions, composed of
bimanual activities: clapping, reaching overhead with hands apart, reaching
out forward with arms, covering both eyes and unimanual activities: reaching
across the body to touch the shoulder, touching the mouth, touching the top of
the head, reaching out to the side, etc. For the first four subjects, the
unimanual activities were done individually for each arm, randomly ordered. As
the study evolved, for the final two subjects, activities were made more
difficult and engaging using bilateral non-symmetrical motions constructed
randomly (ex: “wave with your right arm and touch your shoulder with your left
hand”). This game pushed the subjects to the ends of their range of motion,
using motions which are relevant for activities of daily living (ADLs).

The operator then said that they want the subject to play another game. In the
CT/FTF conditions, the operator explained the game and in the SRAT condition,
the robot explained it: “In the target touch activity I will tell you to touch
the dots on my [hands/board] … Let’s start in a ready position, return to this
position after every touch”. In the CT condition, the telepresence system had
colored dots mounted on a board hanging on the robot. In the FTF condition,
the same board was mounted on the platform next to the operator. In the SRAT
condition, the robot had the same dots on its hands and moved its hands to the
same points as those on the board. The first four subjects were instructed to
touch each of three dots with each hand ten times, for a total of sixty point-
to-point motions. The final two subjects were instructed to complete a series
of 1 to 4 dot/hand sequences with two dots available, randomly selected. This
activity tests the attention and motivation of the subjects by instructing
them to do repetitive motions. In the modification made for the final two
subjects, difficulty was increased, and more sustained attention was required
rather than simple touching.

###  II-D Mid-Interaction Survey and Rest

On completion of each condition, the robot/operator exited the room. Subjects
were then given a survey asking questions from the NASA task load index (TLX)
[30], intrinsic motivation inventory (IMI) [31], how well they enjoyed the
interaction, if they would like to do the interaction again, and how safe they
felt during the interaction. Once the surveys were completed, subjects rested
until at least 15 minutes had passed since the end of the prior condition.

###  II-E Post Study Survey

At the end of the study, subjects are asked questions about the entire
experiment: which interaction modality they thought was best and several
questions adapted from Telemedicine Satisfaction and Usefulness Questionnaire
[32] on whether they thought telemedicine would change how they manage their
healthcare, communicate with their clinicians, and if telehealth visits would
be convenient to them.

##  III RESULTS

###  III-A Subjects

Eight subjects participated in the pilot trial. The surveys were dramatically
edited between the first and second subjects, so the first subject was
excluded from analysis. For one other subject, the power system on the robot
failed, preventing that subject from completing the protocol. As a result,
that subject was also excluded. Therefore 6 subjects’ results were analyzed.
Complete subject information can be seen in table I.

Table I: Subject demographics, affective state, experience/feelings regarding relevant technologies, and trial interaction preferences |  | AJ | HL | GS | VM | PD | BF
---|---|---|---|---|---|---|---
| Diagnosis | Stroke | Stroke | Stroke | None | None | None
| Age | 55 | 53 | 63 | 13 | 4 | 6
| Gender | F | M | F | M | F | F
Color Trails Test Z-score
| CTT-1 | -3.9 | -2.2 | 0.0 | -0.8 | - | -
| CTT-2 | -5.0 | -1.5 | 0.9 | 0.4 | - | -
Box and Block Test Z-score
| Dominant hand | -4.6 | -3.1 | -5.6 | -3.2 | 0.2 | -3.2
| Non-dominant hand | -2.3 | -2.3 | -5.2 | -3.5 | 0.3 | -3.1
Self-Assessment Manikin
| Valence (1: Happy, 9: Unhappy) | 1 | 1 | 1 | 3 | 1 | 1
| Arousal (1: Excited, 9: Relaxed/Sleepy) | 1 | 1 | 5 | 4 | 1 | 3
| Dominance (1: Submissive, 9: Dominant) | 4 | 7 | 9 | 7 | 9 | 9
Please rate your level of experience with (1: No experience, 5: Very high
experience):
| Computers | 4 | 2 | 3 | 4 | 2 | 2
| Tablets | 4 | 2 | 3 | 4 | 3 | 3
| Smartphones | 4 | 2 | 2 | 4 | 3 | 1
| Robots | 4 | 2 | 1 | 3 | 2 | 1
Have you ever done:
| A video call? | Yes | Yes | Yes | Yes | Yes | Yes
| A video call for healthcare? | No | No | Yes | No | No | No
How do you feel about (1: Very negative, 5: Very positive):
| Using video calls for healthcare? | 5 | 4 | 2 | 4 | 5 | 2
| Robots? | 5 | 5 | 4 | 5 | 5 | 4
Interaction Modality Preference:
| First | CT | FTF | FTF | SRAT | SRAT | SRAT
| Second | SRAT | SRAT | SRAT | FTF | CT | FTF

The subjects with stroke varied functionally – one had aphasia, another had
spasticity and loss of function in one hand, preventing independent finger and
wrist actuation. All but one subject (PD) performed 2 to 6 standard deviations
below normal on the box and block test [26, 33]. Subjects varied from severely
impaired to typically functioning on the color trails test. At intake, all
subjects reported being happy, excited to neutral, and dominant to neutral.
All subjects reported positive feelings towards robots. All subjects had
previously made video calls, only one had done so for healthcare (GS).
Subjects initially were mixed on their feelings towards using video calls for
healthcare.

###  III-B Randomization

AJ, BF completed the study in the FTF-CT-SRAT order. HL, GS, VM, PD completed
it in the FTF-SRAT-CT order.

###  III-C Ability to Participate

All subjects were able to fully participate with the robot. No subjects
reported difficulty understanding the instructions given by the humanoid. AJ
reported difficulty in the CT condition with seeing the operator due to the
small screen size. The last two subjects to participate (PD and BF), who were
the youngest and experienced more challenging activities, appeared to have
more difficulty with the Simon Says activity and had significant difficulty
with the target touch activity across conditions. PD was not comfortable with
left and right hands and had difficulty with more than two step instructions.

###  III-D Quality of Interactions

Using the IMI (1 low to 7 high), enjoyment for each condition averaged between
5.1 and 5.8, competence averaged between 6.5 and 6.7, effort averaged between
3.8 and 4.4, and pressure averaged between 2.1 and 2.4.

###  III-E Modality Preference

All three pediatric subjects rated SRAT as the best modality. The three adult
subjects rated SRAT as the second-best modality. Complete ratings are shown in
table I.

###  III-F Observations

Throughout the interactions, the subjects had opportunities to provide
feedback and the study staff recorded notes. GS reported not liking
telepresence, but liked working with the social robot, and stated that they
felt less pressure as the robot could adjust its pacing to their needs
(compared to a human who may be in a rush). AJ said that they thought the
social robot would be useful for home practice. VM reported that the SRAT
interaction was the best due to it being the funniest. BF was more energetic
filling out surveys after the SRAT interaction than the other interactions.
PD, the youngest subject, was very excited to interact with the social robot.
After completing the experiment and surveys, they asked if they could play
with the robot more. We drove it into the room and had the robot say hello,
wave, and talk with them. They interacted with it and ended up petting it on
its head as if it were a pet or a doll.

##  IV DISCUSSION

This case series covers users of a wide variety of ages and motor and
cognitive function. All subjects were able to fully participate in three
conditions: face to face, classical telepresence, and social robot augmented
telepresence. Enjoyment was high for all conditions. All conditions required
moderate effort, but subjects reported high competence and felt low pressure.
With this size of a case series, comparisons between measures after conditions
are not warranted. The high level of enjoyment and the ability of all subjects
to interact with the social robot while it augmented the telepresence
interaction demonstrates acceptability of the system by patients.

The social robot augmented telepresence system was rated higher than
traditional telepresence by five of the six subjects (all but AJ). This is an
early indicator of the benefit that the social robot can add. The pediatric
subjects all rated the social robot augmented condition as best. This may be
partly a novelty effect, which is well documented in the literature. But
previous systems, such as the NT, have demonstrated the use of social robots
for rehab longitudinally with good results [7]. Even if there is a large
amount of novelty driven interest, by using evolving games and activities
coupled with dynamic robot expressions, high engagement should be maintained
over time. Seeing the youngest subject’s (PD) high enthusiasm for the social
robot was exciting to the study team. That subject clearly assigned a
personality to the robot.

One of the adult subjects commented on the social robot being well suited for
subjects who move slower, because it can adapt to their pace, reducing the
pressure during visits while encouraging improved performance. This
highlighted a point of utility that we had not anticipated and adds more
rationale for developing social robots for rehabilitation and remembering to
design with elders, not just children, in mind.

###  IV-A Limitations

All subjects had positive views towards robotics at the start of the trial and
had previous experience making video calls, although only one for health care
purposes, which may bias the respondents towards accepting the social robot.

##  V CONCLUSIONS

We completed a case series with 6 subjects interacting with the Flo robotic
system, an example of social robot augmented telepresence. By multiple
metrics, the system performed well, was accepted by subjects, and appeared
feasible to use for upper extremity motor rehabilitation activities and
assessments.

## ACKNOWLEDGMENT

We thank the subjects who participated in this work.

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