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Assessment and Treatment of the Upper Limb by Means of Virtual Reality in Post-Stroke Patients

Authors:

Abstract

The disability deriving from stroke impacts heavily on the economic and social aspects of western countries because stroke survivors commonly experience various degrees of autonomy reduction in the activities of daily living. Recent developments in neuroscience, neurophysiology and computational science have led to innovative theories about the brain mechanisms of the motor system. Thereafter, innovative, scientifically based therapeutic strategies have initially arisen in the rehabilitation field. Promising results from the application of a virtual reality based technique for arm rehabilitation are reported.
Assessment and Treatment of the Upper
Limb by Means of Virtual Reality in Post-
Stroke Patients
Lamberto PIRON
a
, Andrea TUROLLA
a
, Michela AGOSTINI
a
, Carla ZUCCONI
a
,
Paolo TONIN
a
, Francesco PICCIONE
a
and Mauro DAM
b
a
I.R.C.C.S. San Camillo Hospital, Venice, Italy
b
Department of Neuroscience, University of Padua, Padua, Italy
Abstract. The disability deriving from stroke impacts heavily on the economic
and social aspects of western countries because stroke survivors commonly
experience various degrees of autonomy reduction in the activities of daily living.
Recent developments in neuroscience, neurophysiology and computational science
have led to innovative theories about the brain mechanisms of the motor system.
Thereafter, innovative, scientifically based therapeutic strategies have initially
arisen in the rehabilitation field. Promising results from the application of a virtual
reality based technique for arm rehabilitation are reported.
Keywords. Stroke, Rehabilitation, Motor Learning and Control, Augmented
Feedback, Virtual Reality
Introduction
Stroke is a leading cause of death and disability for men and women of all ages, classes,
and ethnic origins worldwide. Several epidemiological surveys were conducted on
cerebro-vascular disease, especially in the United States, where 500,000 new strokes
occur each year causing 100,000 deaths and leaving residual disability for 300,000
survivors. Moreover, approximately 3 million Americans have survived a stroke with
some degree of residual disability [1, 3].
Within 2 weeks after stroke, hemiparesis is present in 70-85% of patients and a
percentage, between 40 to 75%, is completely dependent in their activities of daily
living [4]. There is a lack of epidemiological data for European countries, although in
the United Kingdom the Oxfordshire Community Stroke Project (1983) reported an
annual incidence of 500 new cases in a 250,000 people community, with a peak in
people older than 75 years [5]. In a recent study conducted in Norway, a total annual
incidence of 2.21 strokes per 1000 people was reported. This rate is congruent with
other European countries showing that there are no regional variations within Western
Europe [6].
The estimates of the total cost of stroke are very variable in relation to the
difficulty of calculating the indirect cost resulting from disability and mortality. A 1993
estimate placed the total annual cost of stroke at $30 billion in the United States, of
which $17 billion are direct costs (hospital, physician, rehabilitation, equipment) and
$13 billion are indirect costs (lost productivity) [7].
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The main cost of stroke survivors is related to their residual motor disabilities that
interfere with personal, social and/or productive activities. Surprisingly, there are few
therapeutic approaches to restore lost functions. Nowadays the available rehabilitative
therapies are currently working to develop treatments that are closely related to motor
learning principles.
Recently the development of tools for quantitative analysis of motor deficits gave
the opportunity to increment the amount of data in clinical practice to better study
human motor behavior with consequent important practical implications. First of all, it
will be possible to infer the anatomical structures that modulate the different elements
of motor control. Furthermore, it may help to better characterize motor deficits and, as
a consequence, to plan individually modified therapeutic approaches. Finally, the
quantitative analysis of movement may allow to monitor pharmacological therapies (i.e
drugs interacting with the central neurotransmitters levels) that could modify the
human motor behavior [8, 9].
1. Rationale
1.1 Neurophysiology of motor learning
Research on the physiological underpinnings of movement dynamics has traditionally
focused most extensively on the primary motor cortex (M1) pointing out that neurons
in M1 are modulated by external dynamic perturbations. Some investigators [10]
indicate that several premotor areas feed M1 which then projects to the spinal cord.
These areas are intensely interconnected with each other, with a parallel contribution to
the control of movement [11].
Other work on primates demonstrated that several cortical cells in motor and pre-
motor areas responded selectively to kinematic variations during motor adaptation
tasks. These cells, clearly identified in the monkey SMA, are involved in the process of
kinematics-to-dynamics transformation, hence in new motor task learning [11]. Doya et
al. [11, 12] proposed other correlations between the motor learning problem and
circuitry at the cortical level, suggesting that different brain areas are involved in three
different kinds of learning mechanisms: supervised learning, reinforcement learning
and unsupervised learning.
The cerebellum is supposed to be involved in real-time fine tuning of movement
by means of its feed-forward structure based on massive synaptic convergence of
granule cell axons (parallel fibers) onto Purkinje cells, which send inhibitory
connections to deep cerebellar nuclei and to inferior olive. The circuit of the cerebellum
is capable of implementing the supervised learning paradigm which consists of error
driven learning behaviors. Reinforcement learning is based on the multiple inhibitory
pathways of the basal ganglia that permit the reward predicting activity of dopamine
neurons and change of behavior in the course of goal directed task learning. The
extremely complex anatomical features of the cortex suggest that information coding is
established by an unsupervised learning paradigm in which the activity is determined
by the Hebbian-rule of synaptic updating. In this paradigm the environment provides
input but gives neither desired targets nor any measure of reward or punishment [11,
12]. Recent neurophysiologic studies demonstrated that some natural complex systems
have discrete combinatory architecture that utilizes finite numbers of primary elements
to create larger structures, such as motor primitives in spinal cord [13]. Poggio and
Bizzi [14] hypothesized a hierarchical architecture where the motor cortex is endowed
with functional modular structures that change their directional tuning during
adaptation, visuo-motor learning, exposure to mechanical load and reorganization after
lesions, i.e. the circuit of interneurons as central pattern generators, unit burst
generators, and spinal motor primitives contributing to motor learning. In the latter case
the force fields stored as synaptic weights in spinal cord may be viewed as representing
motor field primitives from which, through linear superimposition, a vast number of
movements can be fashioned by impulses conveyed by supraspinal and reflex pathways
[14]. Computational analysis [15] verifies that this proposed mechanism is capable of
learning and controlling a wide repertoire of motor behaviors. This hypothesis suggests
that the cortical lesion induced by a stroke could modify the hierarchical architecture
with negative influences on learning and controlling new motor behaviors.
1.2 Neurophysiopathology of stroke lesion
From the physiopathologic perspective, much evidence demonstrated that the location
of the stroke lesion is related to upper limb motor deficit severity. Specifically it is
argued that patients with cortical stroke have a better motor outcome than patients with
subcortical stroke. Furthermore, patients with mixed cortical plus subcortical stroke
tended to improve more than patients with pure subcortical stroke despite the expected
larger size of mixed lesions. Although subcortical strokes are normally smaller than
cortical strokes, they are more likely to involve primary (from M1) and secondary
motor pathways (from SMA and premotor area, PMA). The descending fibers from
primary and secondary motor areas converge in the internal capsule maintaining their
somatotopic distribution. Consequently, even small subcortical lesions produce
devastating motor effects. The probability of upper limb motor recovery after stroke is
hence linked strictly with the anatomical lesion: 75% for patients with lesions restricted
to the cortex (MI, PMA, SMA); 38.5% for those with subcortical or mixed cortical plus
subcortical lesions not affecting the posterior limb of the internal capsule (PLIC); and
3.6% for those with involvement of the PLIC plus adjacent corona radiata, basal
ganglia or thalamus [16].
1.3 Computational approach to the upper limb rehabilitation.
The computational approach to the motor system is a powerful analysis, in the field of
neuroscience, which offers the opportunity to unify the experimental data in a
theoretical framework. In the computational perspective, the motor behavior is intended
as the manifestation of an engineering system, whose basic task is to manage the
relationships between motor commands and sensory feedback. This management is
necessary for two reasons:
1. it ensures that our movements achieve their goals;
2. it enables us to learn by experience to make more accurate and effective
movements.
Recently, Han et al. developed a computational model for bilateral hand use in arm
reaching movements to study the interactions between adaptive decision making and
motor learning after motor cortex lesion [17]. This model combines a biologically
plausible neural model of the motor cortex with a non-neural model of reward-based
decision making and physical therapy intervention. The model demonstrated that in the
damaged cortex, during therapy, the supervised learning rules ensured that
underrepresented directions of movement were “repopulated”, thereby decreasing
average reaching errors.
The authors suggested that after stroke, if no therapy is given, plasticity due to
unsupervised learning may become maladaptive, thereby augmenting the stroke’s
negative effect. They also indicated that there is a threshold for the amount of therapy
based on three types of learning mechanisms (unsupervised, supervised and
reinforcement) required for the recovery process; below this threshold motor retraining
is “in vain”. In other words, there is an absent or exiguous use of the arm exhibiting the
“learned non-use” phenomenon. In the absence of supervised or reinforcement learning,
subsequent motor performance worsens with any amount of rehabilitation trials. On the
contrary, if unsupervised learning is not present, motor performance improves with any
amount of rehabilitation trials in the late period.
1.4 Virtual reality as an emerging therapy
Virtual Reality (VR) is an innovative technology consisting of a computer based
environment that represents a 3-D artificial world. VR has been already applied in
many fields of human activity. New computer platforms permit human-machine
interactions in real time, therefore the possibility of using VR in medicine has arisen.
The present level of technical advances in the computer interface allows the
development of VR systems as therapeutic tools in some neurological and psychiatric
pathology. For example, stroke survivors may undergo rehabilitative therapeutic
procedures with different VR systems [18, 19]. The use of a VR-based system coupled
to a motion tracking tool allows us to study the kinematics of arm movement in the
restorative process after stroke. Furthermore, the possibility of modifying the artificial
environment, where the patients could interact, may exploit some of the mechanisms of
motor learning.
We know from physiological studies that humans perform a large variety of
constrained and unconstrained movement in a smooth and graceful way because the
CNS enables us to rapidly solve complex computational problems. One hypothesis is
that the CNS needs little information in order to adapt movements to the changing of
the external requirements, providing that it already contains preprogrammed algorithms
for function [20]. These algorithms produce regularities in biological movements that
are not in any way implied by the motor task. Accordingly with this view, a given
movement can be characterized by variant and invariant elements. For instance, the
variant part of a reaching movement is the distance of the targets (corresponding to the
amplitude of the movement). The invariant part consists of straight paths with a bell-
shaped speed profile in all movements [21, 22].
In our laboratory, we experimented with a VR based setting for the assessment and
treatment of arm motor deficit in patients after stroke. We compared a VR based
(reinforced feedback in virtual environment, RFVE) and traditional physical therapy
technique (conventional therapy, CT) in the treatment of arm motor impairments in
post-stroke patients. The studied population met the following inclusion criteria: a
single ischemic stroke in the region of the middle cerebral artery at least six months
before the study (proven by means of CT scan or MRI); conventional physical therapy
treatment received in the early period after stroke; mild to intermediate motor
impairments of the arm assessed as a Fugl-Meyer Upper Extremity score (F-M UE)
between 20 and 60, at baseline [23]. Clinical history or evidence of memory
impairments, neglect, and apraxia or aphasia interfering with verbal comprehension
were all considered exclusion criteria.
The experimental intervention was the RFVE treatment and the control procedure
consisted of conventional physical therapy treatment. Both therapies were oriented
towards upper extremity motor rehabilitation. In the first one, the subject was requested
to perform different kinds of motor tasks while the movement of the entire
biomechanical arm system’s end-effector was simultaneously represented in a virtual
scenario by means of motion-tracking equipment. The equipment included a computer
workstation connected to a 3D motion-tracking system (Polhemus 3Space FasTrak,
Vermont, U.S.A) and a high-resolution LCD projector which displayed the virtual
scenarios on a large wall screen. The electromagnetic 3D motion-tracking sensor was
positioned on a manipulable object (rubber ball, polystyrene cube etc.) held by the
subject, or, alternatively, was attached to a glove worn by the patient in cases of severe
grasping deficits. The physical therapist could create numerous virtual motor tasks for
the arm through the use of flexible software, developed at the Massachusetts Institute
of Technology (Cambridge, MA, U.S.), which processes the motion data coming from
the end-effector receiver. The therapist selected the characteristics and the complexity
of the motor tasks in order to suit each patient’s arm deficit. In the virtual scenario, the
therapist determined the starting position and the characteristics of the target, such as
target orientation, for each task or the addition of other virtual objects to increase the
task’s complexity. A simple reaching movement could accomplish some tasks, while
others required more complicated movements, such as putting the envelope in the
mailbox, hitting the nail, or pouring the glass in the carafe. The subject moves the real
envelope, hammer, or glass and sees on the screen the trajectory of the corresponding
virtual object toward the virtual mailbox, nail, or carafe.
During the RFVE therapy, patients were asked to perform motor tasks according to
constraints specified beforehand by the therapist. Subjects were given information
about their arm movements during the performance of motor skills (knowledge of
performance, KP) by the movement of the end-effector’s virtual representation. The
therapist’s movement and trajectory could also be displayed in the background of the
virtual scene in order to facilitate the subject’s perception and adjustment to motion
errors (learning by imitation) [24]. Moreover, knowledge of the results (KR) regarding
motor task correctness was supplied to patients in the form of standardized scores and
by displaying arm trajectory morphology on the screen. Initially, the above mentioned
KP and KR were provided at a frequency of more than 90% and were gradually
decreased as performance improved.
In the CT group the subjects were asked to perform specific exercises for the upper
limb with a strategy of progressive complexity. First, the patients were requested to
control isolated motions without postural control, with physical therapist support if
necessary, then postural control was included and, finally, complex motion with
postural control was practiced. For example, patients were asked to touch different
targets arranged upon a horizontal plane in front of them; to manipulate different
objects; to follow trajectories displayed on a plane; to recognize different arm positions.
The physical therapists chose the exercises in relation to functional assessments
and patient needs.
The aim of this study was to compare the RFVE and CT approaches towards the
treatment of arm motor impairments in post-stroke patients. We hypothesized that a
rehabilitation technique based on motor learning rules, specifically the kinematic
information about arm movements in a virtual environment, could significantly
improve the motor outcome scores better than CT therapy. Before and after the
treatment, the degree of motor impairment and independence in daily living activities
were evaluated in both groups with the F-M UE score and the Functional Independence
Measure scale (FIM) [25]. At the same evaluation times, for all of the patients, we
determined the mean duration (MD) in sec, mean linear velocity (MLV) in cm/sec, and
the number of sub-movements (SM) in 36 motor trials organized into four tasks.
The patients’ starting position was the same in all of the trials. The different
orientation of the target (horizontal, vertical and diagonal on the subject’s frontal plane)
determined the complexity of the movement in terms of involving the activation of
different muscles. The patients were randomly assigned into the 2 groups and both
groups underwent the therapy for 1 hour treatment sessions daily, 5 days a week for 4
weeks.
Analyzing clinical (F-M UE and FIM) variables, we found, in both groups, a
statistical significance within the groups for the F-M UE (p-values<0.00, p-
values<0.016, respectively) and for the FIM (p-values<0.00, p-values<0.009,
respectively) scales. The robust regression analysis revealed that the F-M UE values
after the treatment were systematically higher in the RFVE patients than in the CT
subjects (β =-4.26, p-value<0.005). We observed the same result also for the FIM
values after the treatment (β =-4.59, p-value<0.02). The kinematic (MD, MLV, SM)
parameters changed significantly after the treatment only in the experimental group (p-
value = 0.01, 0.00 and 0.02 respectively), in contrast to those of the control subjects (p-
value = 0.18, 0.11 and 0.15 respectively). Finally none of patients who underwent the
RFVE therapy complained of any discomforts due to interaction with the virtual world,
such as cybersickness, altered eye-motor coordination or postural disequilibrium,
thereby demonstrating that this VR-application is safe for neurological patients.
Our results confirm that late therapy may improve motor performance as suggested
in others studies using different rehabilitation techniques [26, 27]. The kinematic
results were coherent with the RFVE rationale based on the amplification of kinematic
feedback to promote motor recovery; furthermore the improvement in motor
performance occurred concurrently with kinematic variation. In our opinion, the higher
results achieved with RFVE treatment were connected with the rationale of the VR
based technique which exploits the motor learning mechanisms.
2. Conclusion
In our VR setting, patients were given information about their arm movements during
the performance of motor skills (KP) that consisted of the representation of their end-
effector, and “virtual teacher” movement which showed the actual kinematics of the
hand path in order to practice “learning by imitation”. The teacher, as other relevant
feedback, realizes an ideal environment to implement new predictors or to modify
disrupted forward models. These mechanisms are developed by means of amplification
of the actual state. On the other side, new or better controllers can be developed by
means of different sensorimotor context presented in every scenario, as by the
utilization of graphic models that reproduce the visual objects’ appearance, giving
coherent contextual information. Furthermore, instructions imparted by the therapist
during the experimental procedure and the virtual representation of the correct
movement contributed to providing information about motor performance, thereby
exploiting so-called “supervised learning”. Moreover, the object’s trajectories
displayed on-screen allowed patients to evaluate the accuracy of their movement (KR),
thereby promoting the identification of successful motor strategies through the “trial
and error” paradigm. A second kind of KR provided to patients was a reward delivered
when the task performance score surpassed a pre-established threshold. These two
phenomena contributed to generating the basis for the “reinforcement learning”
mechanism.
In our experience, the synergistic activity of supervised, reinforcement and
learning by imitation facilitates faster development of the kinematic internal models
essential for motor learning. The opportunity for supplying patients with a
measurement of motor performance generated an auto-competitive stimulus for
progressively improving the correctness of arm trajectories session by session. The
above aspect, combined with the novelty and the originality of the VR-based therapy,
motivated the patients to enthusiastically participate in the rehabilitation sessions.
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... The rehabilitation of neurological motor impairments is based on motor learning principles within complex sensorimotor and cognitive processes [2]. Repracticing the execution of goal-directed actions requires some planning and computational steps that engage connections among various brain areas [3,4]. ...
... Recent innovative approaches for motor rehabilitation with technology-based (hereafter, TB) techniques aim to resemble the ecological environments, where behavior is demanding and cognitive abilities may be involved [2,14]. TB methods are based on interactive action-feedback simulation software, which engages patients into real-world-like scenarios [2,15,16] and supports motor recovery, as demonstrated for upper limb rehabilitation [17][18][19][20]. ...
... Recent innovative approaches for motor rehabilitation with technology-based (hereafter, TB) techniques aim to resemble the ecological environments, where behavior is demanding and cognitive abilities may be involved [2,14]. TB methods are based on interactive action-feedback simulation software, which engages patients into real-world-like scenarios [2,15,16] and supports motor recovery, as demonstrated for upper limb rehabilitation [17][18][19][20]. Nevertheless, a recent Cochrane review noted that most studies of TB rehabilitation (i.e., using virtual reality) usually exclude patients with severe cognitive deficits, thereby prompting for further investigations on cognitive abilities as covariate in motor training outcome [21]. ...
Article
Full-text available
The rehabilitation of motor deficits following stroke relies on both sensorimotor and cognitive abilities, thereby involving large-scale brain networks. However, few studies have investigated the integration between motor and cognitive domains, as well as its neuroanatomical basis. In this retrospective study, upper limb motor responsiveness to technology-based rehabilitation was examined in a sample of 29 stroke patients (18 with right and 11 with left brain damage). Pretreatment sensorimotor and attentional abilities were found to influence motor recovery. Training responsiveness increased as a function of the severity of motor deficits, whereas spared attentional abilities, especially visuospatial attention, supported motor improvements. Neuroanatomical analysis of structural lesions and white matter disconnections showed that the poststroke motor performance was associated with putamen, insula, corticospinal tract, and frontoparietal connectivity. Motor rehabilitation outcome was mainly associated with the superior longitudinal fasciculus and partial involvement of the corpus callosum. The latter findings support the hypothesis that motor recovery engages large-scale brain networks that involve cognitive abilities and provides insight into stroke rehabilitation strategies.
... However, this recovery process is typically slow and labour-intensive, usually involving extensive interaction between one or more therapists and one patient [19]. Motor disability does not only cause limitations in functional motor control, muscle strength, and range of motion (ROM) but can limit the ability to perform daily tasks, that could cause isolation, and reduce participation in community activities [27] and [36]. Participating in repetitive exercises can help these people to overcome the limitations they experience, but lack of action and isolation stops them to perform recommended practices thus, become weaker, and cause obesity-related chronic health conditions and so on. ...
... A lack of motivation is another impediment that stops them to participate in physiotherapy sessions regularly. Studies in computational neuroscience have shown that virtual reality (VR) rehabilitation techniques could create an environment that recovers health conditions as well as community integration [50] and [36]. A study by [50] among post-stroke patients was conducted to investigate the effects of the two treatment methods: (I) combined VR and conventional therapy and (II) standard therapy alone. ...
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This paper proposes the use of a non-immersive virtual reality rehabilitation system ReHabgame developed using Microsoft Kinect and the Thalmic Labs Myo gesture control armband. The ReHabgame was developed based on two third-person video games that provide a feasible possibility of assessing postural control and functional reach tests. It accurately quantifies specific postural control mechanisms including timed standing balance, functional reach tests using real-time anatomical landmark orientation, joint velocity, and acceleration while end trajectories were calculated using an inverse kinematics algorithm. The game was designed to help patients with neurological impairment to be subjected to physiotherapy activity and practice postures of daily activities. The subjective experience of the ReHabgame was studied through the development of an Engagement Questionnaire (EQ) for qualitative, quantitative and Rasch model. The Monte-Carlo Tree Search (MCTS) and Random object (ROG) generator algorithms were used to adapt the physical and gameplay intensity in the ReHabgame based on the Motor Assessment Scale (MAS) and Hierarchical Scoring System (HSS). Rasch analysis was conducted to assess the psychometric characteristics of the ReHabgame and to identify if these are any misfitting items in the game. Rasch rating scale model (RSM) was used to assess the engagement of players in the ReHabgame and evaluate the effectiveness and attractiveness of the game. The results showed that the scales assessing the rehabilitation process met Rasch expectations of reliability, and unidimensionality. Infit and outfit mean squares values are in the range of (0.68 1.52) for all considered 16 items. The Root Mean Square Residual (RMSR) and the person separation reliability were acceptable. The item/person map showed that the persons and items were clustered symmetrically.
... VRRS features a wide range of innovative non-immersive virtual reality medical devices, incorporating a multi-domain technology developed by Khymeia (an Italian Small-Medium Enterprise, SME) and tested for rehabilitation both in clinical settings and telerehabilitation. Utilizing biofeedback and augmented feedback mechanisms, VRRS enhances user engagement and compliance [45,46]. Initially designed for the adult population, recent applications with children and adolescents have shown promising preliminary outcomes [32,34,47,48]. ...
... VRRS features a wide range of innovative non-immersive virtual reality medical devices, incorporating a multi-domain technology developed by Khymeia (an Italian Small-Medium Enterprise, SME) and tested for rehabilitation both in clinical settings and tele-rehabilitation. Utilizing biofeedback and augmented feedback mechanisms, VRRS enhances user engagement and compliance [45,46]. Initially designed for the adult population, recent applications with children and adolescents have shown promising preliminary outcomes [32,34,47,48]. ...
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Background/Objectives: In recent years, the advent of new technologies has fostered their application in neuro-psychomotor and language rehabilitation, particularly since the COVID-19 pandemic. Tele-rehabilitation has emerged as an innovative and timely solution, enabling personalized interventions monitored by clinicians. TABLET TOSCANA project aims to develop innovative tele-rehabilitation organizational models in children, adolescents and young adults with congenital and acquired developmental disabilities, using the Virtual Reality Rehabilitation System (VRRS) Home Kit and the MedicoAmico APP. Methods: The trial is designed according to the CONSORT statement guidelines. The project encompasses three phases: adapting the technologies for pediatric use, validating them through a wait-list study, and analyzing feasibility and effectiveness data to define new organizational models. A randomized wait-list-control study with 100 subjects aged 6 to 30 years will compare tele-rehabilitation versus prosecution of standard care. Discussion: Although literature highlights tele-rehabilitation benefits such as improved access, cost savings, and enhanced treatment adherence, practical implementation remains limited (i.e., the definition of standardized procedures). TABLET TOSCANA project seeks to address these gaps by focusing on multi-domain treatments for neurodevelopmental disabilities and emphasizing the integration of tele-rehabilitation into local health services. Conclusion: The project aims to improve the continuity and intensity of care through innovative models that integrate tele-rehabilitation into local health services. The results could inform healthcare policies and promote the development of innovative and collaborative models of care, paving the way for more effective and widespread tele-rehabilitation solutions and fostering collaborative networks among professionals.
... It integrates multi-domain technology designed for rehabilitation in both clinical and home-based settings. Utilizing biofeedback and augmented feedback, the system is designed to be user-friendly and engaging [36,37]. Initially developed for adult patients, VRRS has recently been adapted for children and adolescents, with recent studies showing promising results [38][39][40][41]. ...
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Background/Objectives: New advances in technologies are opening the possibility to support functional evaluation and rehabilitation in the field of speech therapy. Among available systems, a virtual reality rehabilitation system (VRRS, Khymeia) is a multi-domain ecosystem. Despite it being used in a limited number of studies, its use in speech-therapy has shown potential for promoting linguistic and literacy skills. Methods: This pilot study aims to assess the feasibility of single-session speech assessment with the VRRS in twenty-eight children with cerebral palsy (CP) by means of ad hoc questionnaires. Moreover, we evaluated the feasibility and the effects of an intensive tele-rehabilitation treatment with the VRRS in a subgroup of three children with unilateral CP. Results: Feasibility was generally good when using the VRRS for assessments. Both clinicians and children found it to have good usability, although acceptability scores were higher for children than clinicians. For tele-rehabilitation, overall improvements were observed in both linguistic and learning (reading and writing) skills. Conclusions: This study paves the way for VRRS use in speech-therapy tele-rehabilitation for children with CP and language and learning difficulties.
... 14 Within the review, three randomised controlled trials (RCTs) were pooled to compare in-person care to computer software, to rehabilitate upper limb function (170 participants in total). One study compared the same intervention delivered in-person versus virtually, 15 one compared virtual reality telerehabilitation to conventional in-person therapy, 16 and one investigated comparable doses and modes of therapy delivered either in-clinic or through telerehabilitation. 17 Within the review, a further three RCTs compared telerehabilitation to usual care to rehabilitate upper limb function, one using written and video instructions, 18 one using phone and messaging systems, 19 and one using a computer-based system. ...
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Introduction Stroke is a leading cause of disability throughout the world. Unilateral upper limb impairment is common in people who have had a stroke. As a result of impaired upper limb function, people who have had a stroke often employ abnormal ‘compensatory’ movements. In the short term, these compensatory movements allow the individual to complete tasks, though long-term movement in this manner can lead to limitations. Telerehabilitation offers the provision of rehabilitation services to patients at a remote location using information and communication technologies. ‘EvolvRehab’ is one such telerehabilitation system, which uses activities to assess and correct compensatory upper body movements, although the feasibility of its use is yet to be determined in National Health Service services. Using EvolvRehab, we aim to assess the feasibility of 6 weeks telerehabilitation in people after a stroke. Methods and analysis A multisite feasibility study with embedded design phase. Normally distributed data will be analysed using paired samples t-tests; non-normally distributed data will be analysed using related samples Wilcoxon signed rank tests. Thematic content analysis of interview transcripts will be used to investigate the usability and perceived usefulness of the EvolvRehab kit. Ethics and dissemination This study has received ethical approval from Solihull Research Ethics Committee (REC reference: 23/WM/0054). Dissemination will be carried out according to the dissemination plan co-written with stroke survivors, including academic publications and presentations; written reports; articles in publications of stakeholder organisations; presentations to and publications for potential customers. Trial registration number NCT05875792 .
... It is a fully functional architecture that allows for neurological, cognitive, postural, speech and orthopedic rehabilitation activities in VR environments using different peripherals, including a stabilometric balance. VRRS is conceived to treat the subject by generating augmented feedback toward his central nervous system through targeted rehabilitation programs which are performed in a virtual environment that helps the subjects develop knowledge of the results of the movements [43,44]. There are several packages for rehabilitation and others for assessments. ...
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Considering the variability and heterogeneity of motor impairment in children with Movement Disorders (MDs), the assessment of postural control becomes essential. For its assessment, only a few tools objectively quantify and recognize the difference among children with MDs. In this study, we use the Virtual Reality Rehabilitation System (VRRS) for assessing the postural control in children with MD. Furthermore, 16 children (mean age 10.68 ± 3.62 years, range 4.29–18.22 years) were tested with VRRS by using a stabilometric balance platform. Postural parameters, related to the movements of the Centre of Pressure (COP), were collected and analyzed. Three different MD groups were identified according to the prevalent MD: dystonia, chorea and chorea–dystonia. Statistical analyses tested the differences among MD groups in the VRRS-derived COP variables. The mean distance, root mean square, excursion, velocity and frequency values of the dystonia group showed significant differences (p < 0.05) between the chorea group and the chorea–dystonia group. Technology provides quantitative data to support clinical assessment: in this case, the VRRS detected differences among the MD patterns, identifying specific group features. This tool could be useful also for monitoring the longitudinal trajectories and detecting post-treatment changes.
... Upper limb hemiplegia is one of the most serious disabling consequences of stroke [1]. ere are many studies on the influence of upper limb motor function of patients. ...
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This paper mainly introduces the relevant contents of automatic assessment of upper limb mobility after stroke, including the relevant knowledge of clinical assessment of upper limb mobility, Kinect sensor to realize spatial location tracking of upper limb bone points, and GCRNN model construction process. Through the detailed analysis of all FMA evaluation items, a unique experimental data acquisition environment and evaluation tasks were set up, and the results of FMA prediction using bone point data of each evaluation task were obtained. Through different number and combination of tasks, the best coefficient of determination was achieved when task 1, task 2, and task 5 were simultaneously used as input for FMA prediction. At the same time, in order to verify the superior performance of the proposed method, a comparative experiment was set with LSTM, CNN, and other deep learning algorithms widely used. Conclusion. GCRNN was able to extract the motion features of the upper limb during the process of movement from the two dimensions of space and time and finally reached the best prediction performance with a coefficient of determination of 0.89.
... In our study, the use of a VR-based system, together with a motion capture tool, allowed us to modify the artificial environment with which the patient could interact, exploiting some mechanisms of motor learning [33,34], thus allowing greater flexibility and effective improvement in task learning. is system has been highly successful in the functional recovery of the hemiparetic upper extremity [31,[33][34][35][36], but its combined effect with TR on the LE has not yet reported conclusive data [37]. e continuous supply of feedback during voluntary movement makes it possible to continuously adjust contractile activity [38], thus mitigating increments in spasticity and cocontraction processes of the patient. ...
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Background: Ankle spasticity is a frequent phenomenon that limits functionality in poststroke patients. Objectives: Our aim was to determine if there was decreased spasticity in the ankle plantar flex (PF) muscles in the plegic lower extremity (LE) and improvement of gait function in stroke patients after traditional rehabilitation (TR) in combination with virtual reality with reinforced feedback, which is termed "reinforced feedback virtual environment" (RFVE). Methods: The evaluation, before and after treatment, of 10 hemiparetic patients was performed using the Modified Ashworth Scale (MAS), Functional Ambulatory Category (FAC), and Functional Independence Measure (FIM). The intervention consisted of 1 hour/day of TR plus 1 hour/day of RFVE (5 days/week for 3 weeks; 15 sessions in total). Results: The MAS and FAC reached statistical significance (P < 0.05). The changes in the FIM did not reach statistical significance (P=0.066). The analysis between the ischemic and haemorrhagic patients showed significant differences in favour of the haemorrhagic group in the FIM scale. A significant correlation between the FAC and the months after the stroke was established (P=-0.711). Indeed, patients who most increased their score on the FAC at the end of treatment were those who started the treatment earliest after stroke. Conclusions: The combined treatment of TR and RFVE showed encouraging results regarding the reduction of spasticity and improvement of gait function. An early commencement of the treatment seems to be ideal, and future research should increase the sample size and assessment tools.
... This can affect postural control and balance and cause difficulties in independent daily life [13,18,23]. Physiopathologic research has demonstrated that such difficulties include utilising hands for timed grasp, holding, buttoning, reaching, balancing or/and walking [27]. It is of vital importance to provide opportunities for patients to relearn or improve basic skills by doing exercises that help them to restore appropriate physical functionality. ...
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A cost-effective, easily-accessible rehabilitation solution is proposed for neuro-motor rehabilitation with the capability to determine the range of motion and the kinematic ability. Four-scenarios are developed, in which the players control an avatar that is mirroring the rotations of the upper-limb joints through a multi-channel-input (Kinect, Myo, FootPedal). Administered functional reach tests (FRT) determine the player to interact with the 3D-environment while standing/sitting/using the FootPedal. The walking can be simulated through the FootPedal, while body movement is measured concurrently. The FRT's complexity level is adapted using a Monte Carlo Tree Search algorithm which determines the virtual object's position based on the proved ability of the user. Twenty-six volunteers were recruited to play the games (45-minute-sessions, 10/12 weeks). The data showed that the system had positive impact on player’s performance, being more motivating than formal therapy. The visual representation of the trajectory of the objects has proven to increase the perception of the participants in voluntary/involuntary upper extremity movement. The results showed a comparable inter-session reliability (acceptable-good ICC_{2,1}>0.77) and high Pearson correlation (r>0.85) over two repeated sessions for all the games. Kinect and Myo improved the accuracy in assessing the data regarding the timing and motion of clinically relevant movements.
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Background Effective rehabilitation of the upper extremity function is vital for individuals recovering from stroke or cervical spinal cord injury, as it can enable them to regain independence in daily tasks. While robotic therapy provides precise and consistent motor training, it often lacks the integration of real-world objects that stimulate sensorimotor experiences. The Toronto Rehabilitation Institute—Hand Function Test (TRI-HFT) utilizes 19 everyday items to assess hand function. This study aims to modify the 3D-printed TRI-HFT objects to ensure their compatibility with robotic manipulation, thereby enhancing the functional relevance of robot-assisted rehabilitation, and to evaluate the usability of the new robotic system to ensure its safety and technical performance. Results We successfully redesigned the 3D-TRI-HFT objects to enable manipulation by a robotic arm equipped with a gripper. The modified 3D-printed objects closely matched the original specifications, with most weight and size deviations within acceptable limits. Performance tests demonstrated reliable robotic manipulation, achieving a 100% success rate in 50 pick-and-place trials for each object without any breakage or slippage. Usability assessments further supported the system’s performance, indicating that participants found the system engaging, useful, and comfortable. Conclusions The modified 3D-printed TRI-HFT objects allow seamless integration into robotic therapy, facilitating the use of real-world objects in rehabilitation exercises. These modifications enhance functional engagement without compromising user interaction with the objects, demonstrating the feasibility of combining traditional rehabilitation tools with robotic systems, potentially leading to improved outcomes in upper extremity rehabilitation. Future research may focus on adapting these designs for compatibility with a broader range of robotic equipment, reducing the cost of the objects as 3D printing technology advances, and evaluating the system’s performance among individuals with stroke and SCI.
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Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is "in vain": there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive train-wait-train paradigm: if spontaneous arm use has increased in the "wait" period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided.
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This article has no abstract; the first 100 words appear below. Atrial fibrillation not related to valvular heart disease (nonvalvular atrial fibrillation) is associated with nearly half the arterial emboli presumed to be of cardiac origin. It starts at a mean age of 64 years, affects 2 to 5 percent of the general population over the age of 60 (more than 1 million people), and is associated with a fivefold increase in the risk of ischemic stroke and a 5 to 7 percent yearly risk that increases with age. Cerebral infarction eventually occurs in up to 35 percent of patients with nonvalvular atrial fibrillation. The risk is even higher if "silent" . . . James H. Chesebro, M.D. Mayo Clinic and Mayo Foundation Rochester, MN 55905 Valentin Fuster, M.D. Jonathan L. Halperin, M.D. Mount Sinai Medical Center New York, NY 10029