Posts Tagged VR
RGS is a highly innovative Virtual Reality (VR) tool for the rehabilitation of deficits that occur after brain lesions and has been successfully used for the rehabilitation of the upper extremities after stroke.
The RGS is based on the neurobiological considerations that plasticity of the brain remains throughout life and therefore can be utilized to achieve functional reorganization of the brain areas affected by stroke. This can be realized by means of activation of secondary motor areas such as the so called mirror neurons system.
RGS deploys a deficit oriented training approach. Specifically, while training with RGS the patient is playing individualized games where movement execution is combined with the observation of correlated actions performed by a virtual body. The system optimizes the user’s training by analyzing the qualitative and quantitative aspects of the user’s performance. This warranties a detailed assessment of the deficits of the patient and their recovery dynamics.
also see specs.upf.edu
[Research Poster] Upper Limb Virtual Reality Training Provides Increased Activity Compared With Conventional Training for Severely Affected Subacute Patients After Stroke
To compare amount of activity of virtual reality (VR) and conventional task-oriented training (CT).
Source: Upper Limb Virtual Reality Training Provides Increased Activity Compared With Conventional Training for Severely Affected Subacute Patients After Stroke – Archives of Physical Medicine and Rehabilitation
Virtual reality (VR) started about 50 years ago in a form we would recognize today [stereo head-mounted display (HMD), head tracking, computer graphics generated images] – although the hardware was completely different. In the 1980s and 1990s, VR emerged again based on a different generation of hardware (e.g., CRT displays rather than vector refresh, electromagnetic tracking instead of mechanical). This reached the attention of the public, and VR was hailed by many engineers, scientists, celebrities, and business people as the beginning of a new era, when VR would soon change the world for the better. Then, VR disappeared from public view and was rumored to be “dead.” In the intervening 25 years a huge amount of research has nevertheless been carried out across a vast range of applications – from medicine to business, from psychotherapy to industry, from sports to travel. Scientists, engineers, and people working in industry carried on with their research and applications using and exploring different forms of VR, not knowing that actually the topic had already passed away.
The purpose of this article is to survey a range of VR applications where there is some evidence for, or at least debate about, its utility, mainly based on publications in peer-reviewed journals. Of course not every type of application has been covered, nor every scientific paper (about 186,000 papers in Google Scholar): in particular, in this review we have not covered applications in psychological or medical rehabilitation. The objective is that the reader becomes aware of what has been accomplished in VR, where the evidence is weaker or stronger, and what can be done. We start in Section 1 with an outline of what VR is and the major conceptual framework used to understand what happens when people experience it – the concept of “presence.” In Section 2, we review some areas where VR has been used in science – mostly psychology and neuroscience, the area of scientific visualization, and some remarks about its use in education and surgical training. In Section 3, we discuss how VR has been used in sports and exercise. In Section 4, we survey applications in social psychology and related areas – how VR has been used to throw light on some social phenomena, and how it can be used to tackle experimentally areas that cannot be studied experimentally in real life. We conclude with how it has been used in the preservation of and access to cultural heritage. In Section 5, we present the domain of moral behavior, including an example of how it might be used to train professionals such as medical doctors when confronting serious dilemmas with patients. In Section 6, we consider how VR has been and might be used in various aspects of travel, collaboration, and industry. In Section 7, we consider mainly the use of VR in news presentation and also discuss different types of VR. In the concluding Section 8, we briefly consider new ideas that have recently emerged – an impossible task since during the short time we have written this page even newer ideas have emerged! And, we conclude with some general considerations and speculations.
Throughout and wherever possible we have stressed novel applications and approaches and how the real power of VR is not necessarily to produce a faithful reproduction of “reality” but rather that it offers the possibility to step outside of the normal bounds of reality and realize goals in a totally new and unexpected way. We hope that our article will provoke readers to think as paradigm changers, and advance VR to realize different worlds that might have a positive impact on the lives of millions of people worldwide, and maybe even help a little in saving the planet.
[ARTICLE] Effects of Virtual Reality Exercise Program on Balance, Emotion and Quality of Life in Patients with Cognitive Decline
[ARTICLE] The effectiveness of reinforced feedback in virtual environment in the first 12 months after stroke – Full Text HTML/PDF
[ARTICLE] A Mixed Methods Small Pilot Study to Describe the Effects of Upper Limb Training Using a Virtual Reality Gaming System in People with Chronic Stroke – Full Text
Introduction. This small pilot study aimed to examine the feasibility of an upper limb rehabilitation system (the YouGrabber) in a community rehabilitation centre, qualitatively explore participant experiences, and describe changes after using it.
Methods and Material. Chronic stroke participants attending a community rehabilitation centre in the UK were randomised to either a YouGrabber or a gym group and completed 18 training sessions over 12 weeks. The motor activity log, box and block, and fatigue severity score were administered by a blinded assessor before and after the intervention. Semistructured interviews were used to ascertain participants’ views about using the YouGrabber.
Results. Twelve participants (6 females) with chronic stroke were recruited. All adhered to the intervention. There were no adverse events, dropouts, or withdrawal. There were no significant differences between the YouGrabber and gym groups although there were significant within group improvements on the motor activity log (median change: 0.59, range: 0.2–1.25; ) within the YouGrabber group. Participants reported that the YouGrabber was motivational but they expressed frustration with technical challenges.
Conclusions. The YouGrabber appeared practical and may improve upper limb activities in people several months after stroke. Future work could examine cognition, cost effectiveness, and different training intensities.
There are approximately 33 million stroke survivors worldwide . Whilst the survival rate of stroke continues to improve, it is recognised that many survivors continue to be left with functional deficits that impact upon their quality of life and limit their return to vital functions and hobbies . The ability to return to activities of daily living after stroke can be maximised by rehabilitative therapy which improves quality of life and facilitates independence . A key component of physical therapy after stroke is repetition, or practice, of challenging movements that are focused on achieving a task or function . This repeated task practice has been shown to facilitate and harness positive adaptations within the brain to aid recovery . Whilst an ideal amount of practice to improve daily functioning has not been established , animal studies suggest that in excess of 400 repetitions are needed to promote plastic changes in the brain . In clinical studies, two to three hours a day of practice for six weeks has been shown to elicit meaningful improvements in stroke survivors . Meta-analyses of clinical trials also indicate that higher doses of practice promote better outcomes in impairments and activities of daily living for people after stroke [4, 7–9].
Facilitating increased practice of task orientated movements may be particularly helpful in improving the upper limb in people after stroke. Between half and two-thirds of stroke survivors report problems with their upper limb which significantly affects their activities of daily living  and has considerable negative effects upon participation and quality of life [11, 12]. Recovery of the upper limb may be particularly difficult as an individual’s use of the affected arm has been observed to be minimal after stroke . Furthermore, restoration of the upper limb often is not the primary aim of initial rehabilitation for both the patient and therapist, who are likely to be more focused on regaining the ability to walk . Consequently it is unsurprising that less than 10 minutes of a typical therapy session are focused upon activities for the upper limb [13, 15].
There is good quality evidence for the use of interventions which require repetitive, task orientated, and task specific activities to improve the recovery of the upper limb after stroke [16, 17]. These interventions include constraint induced movement therapy (CIMT), virtual reality, and interactive video games . Interactive video gaming using forms of virtual reality (VR) have grown in popularity as a method to increase repeated practice of challenging and engaging movements for people after stroke. Training using interactive VR games can provide task oriented, unpredictable and graduated learning , and augmented feedback regarding performance and results which motivate and engage players .
Although there is insufficient evidence to compare different upper limb interventions , the literature suggests that interactive VR game training is at least as effective as conventional exercises to elicit improvements in the upper limb after stroke . However, many studies use a broad range of gaming systems in mostly acute stroke survivors where participants were typically based in hospital settings . Consequently, the effects of virtual reality gaming upon the upper limb function of community dwelling stroke survivors who have had their strokes many months or years ago are not established. Furthermore, only a few studies have considered the views of participants about using virtual reality gaming systems for rehabilitation of the upper limb. Whilst these views have been largely positive, similar findings cannot be assumed between different training locations and gaming systems .
Therefore, this small, prospective mixed methods study was developed to
- examine the feasibility of a custom made virtual reality upper limb interactive gaming tool called the YouGrabber® (YouRehab) in people after stroke who are attending a community outpatient rehabilitation centre,
- describe the changes in upper limb function after using the YouGrabber and estimate the magnitude of the change in order to inform the sample size needed for a future trial,
- explore the experiences of participants who had used the YouGrabber for rehabilitation of the upper limb after stroke.
[ARTICLE] Closed-Loop Task Difficulty Adaptation during Virtual Reality Reach-to-Grasp Training Assisted with an Exoskeleton for Stroke Rehabilitation – Full Text
Stroke patients with severe motor deficits of the upper extremity may practice rehabilitation exercises with the assistance of a multi-joint exoskeleton. Although this technology enables intensive task-oriented training, it may also lead to slacking when the assistance is too supportive. Preserving the engagement of the patients while providing “assistance-as-needed” during the exercises, therefore remains an ongoing challenge. We applied a commercially available seven degree-of-freedom arm exoskeleton to provide passive gravity compensation during task-oriented training in a virtual environment. During this 4-week pilot study, five severely affected chronic stroke patients performed reach-to-grasp exercises resembling activities of daily living. The subjects received virtual reality feedback from their three-dimensional movements. The level of difficulty for the exercise was adjusted by a performance-dependent real-time adaptation algorithm. The goal of this algorithm was the automated improvement of the range of motion. In the course of 20 training and feedback sessions, this unsupervised adaptive training concept led to a progressive increase of the virtual training space (p < 0.001) in accordance with the subjects’ abilities. This learning curve was paralleled by a concurrent improvement of real world kinematic parameters, i.e., range of motion (p = 0.008), accuracy of movement (p = 0.01), and movement velocity (p < 0.001). Notably, these kinematic gains were paralleled by motor improvements such as increased elbow movement (p = 0.001), grip force (p < 0.001), and upper extremity Fugl-Meyer-Assessment score from 14.3 ± 5 to 16.9 ± 6.1 (p = 0.026). Combining gravity-compensating assistance with adaptive closed-loop feedback in virtual reality provides customized rehabilitation environments for severely affected stroke patients. This approach may facilitate motor learning by progressively challenging the subject in accordance with the individual capacity for functional restoration. It might be necessary to apply concurrent restorative interventions to translate these improvements into relevant functional gains of severely motor impaired patients in activities of daily living.
Despite their participation in standard rehabilitation programs (Jørgensen et al., 1999; Dobkin, 2005), restoration of arm and hand function for activities of daily living is not achieved in the majority of stroke patients. In the first weeks and months after stroke, a positive relationship between the dose of therapy and clinically meaningful improvements has been demonstrated (Lohse et al., 2014; Pollock et al., 2014). In stroke patients with long-standing (>6 months) upper limb paresis, however, treatment effects were small, with no evidence of a dose-response effect of task-specific training on the functional capacity (Lang et al., 2016). This has implications for the use of assistive technologies such as robot-assisted training during stroke rehabilitation. These devices are usually applied to further increase and standardize the amount of therapy. They have the potential to improve arm/hand function and muscle strength, albeit currently available clinical trials provide on the whole only low-quality evidence (Mehrholz et al., 2015). It has, notably, been suggested that technology-assisted improvements during stroke rehabilitation might at least partially be due to unspecific influences such as increased enthusiasm for novel interventions on the part of both patients and therapists (Kwakkel and Meskers, 2014). In particular, a comparison between robot-assisted training and dose-matched conventional physiotherapy in controlled trials revealed no additional, clinically relevant benefits (Lo et al., 2010; Klamroth-Marganska et al., 2014). This might be related to saturation effects. Alternatively, the active robotic assistance might be too supportive when providing “assistance-as-needed” during the exercises (Chase, 2014). More targeted assistance might therefore be necessary during these rehabilitation exercises to maintain engagement without compromising the patients’ motivation; i.e., by providing only as much support as necessary and as little as possible (Grimm and Gharabaghi, 2016). In this context, passive gravity compensation with a multi-joint arm exoskeleton may be a viable alternative to active robotic assistance (Housman et al., 2009; Grimm et al., 2016a). In severely affected patients, performance-dependent, neuromuscular electrical stimulation of individual upper limb muscles integrated in the exoskeleton may increase the range of motion even further (Grimm and Gharabaghi, 2016; Grimm et al., 2016b). These approaches focus on the improvement of motor control, which is defined as the ability to make accurate and precise goal-directed movements without reducing movement speed (Reis et al., 2009; Shmuelof et al., 2012), or using compensatory movements (Kitago et al., 2013, 2015). Functional gains in hemiparetic patients, however, are often achieved by movements that aim to compensate the diminished range of motion of the affected limb (Cirstea and Levin, 2000; Grimm et al., 2016a). Although these compensatory strategies might be efficient in short-term task accomplishment, they may lead to long-term complications such as pain and joint-contracture (Cirstea and Levin, 2007; Grimm et al., 2016a). In this context, providing detailed information about how the movement is carried out, i.e., the quality of the movement, is more likely to recover natural movement patterns and avoid compensatory movements, than to provide information about movement outcome only (Cirstea et al., 2006; Cirstea and Levin, 2007; Grimm et al., 2016a). This feedback, however, needs to be provided implicitly, since explicit information has been shown to disrupt motor learning in stroke patients (Boyd and Winstein, 2004, 2006; Cirstea and Levin, 2007). Information on movement quality has therefore been incorporated as implicit closed-loop feedback in the virtual environment of an exoskeleton-based rehabilitation device (Grimm et al., 2016a). Specifically, the continuous visual feedback of the whole arm kinematics allowed the patients to adjust their movement quality online during each task; an approach closely resembling natural motor learning (Grimm et al., 2016a).
Along these lines, virtual reality and interactive video gaming have emerged as treatment approaches in stroke rehabilitation (Laver et al., 2015). They have been used as an adjunct to conventional care (to increase overall therapy time) or compared with the same dose of conventional therapy. These studies have demonstrated benefits in improving upper limb function and activities of daily living, albeit currently available clinical trials tend to provide only low-quality evidence (Laver et al., 2015). Most of these studies were conducted with mildly to moderately affected patients. In the remaining patient group with moderate to severe upper limp impairment, the intervention effects were more heterogeneous and affected by the impairment level, with either no or only modest additional gains in comparison to dose-matched conventional treatments (Housman et al., 2009; Byl et al., 2013; Subramanian et al., 2013).
With respect to the restoration of arm and hand function in severely affected stroke patients in particular, there is still a lack of evidence for additional benefits from technology-assisted interventions for activities of daily living. The only means of providing such evidence is by sufficiently powered, randomized and adequately controlled trials (RCT).
However, such high-quality RCT studies require considerable resources. Pilot data acquired earlier in the course of feasibility studies may provide the rationale and justification for later large-scale RCT. Such studies therefore need to demonstrate significant improvements, with functional relevance for the participating patients. Then again, costly RCT can be avoided when innovative interventions prove to be feasible but not effective with regard to the treatment goal, i.e., that they do not result in functionally relevant upper extremity improvements in severely affected stroke patients.
One recent pilot study, for example, applied brain signals to control an active robotic exoskeleton within the framework of a brain-robot interface (BRI) for stroke rehabilitation. This device provided patient control over the training device via motor imagery-related oscillations of the ipsilesional cortex (Brauchle et al., 2015). The study illustrated that a BRI may successfully link three-dimensional robotic training to the participant’s effort. Furthermore, the BRI allowed the severely impaired stroke patients to perform task-oriented activities with a physiologically controlled multi-joint exoskeleton. However, this approach did not result in significant upper limb improvements with functional relevance for the participating patients. This training approach was potentially too challenging and may even have frustrated the patients (Fels et al., 2015). The patients’ cognitive resources for coping with the mental load of performing such a neurofeedback task must therefore be taken into consideration (Bauer and Gharabaghi, 2015a; Naros and Gharabaghi, 2015). Mathematical modeling on the basis of Bayesian simulation indicates that this might be achieved when the task difficulty is adapted in the course of the training (Bauer and Gharabaghi, 2015b). Such an adaptation strategy has the potential to facilitate reinforcement learning (Naros et al., 2016b) by progressively challenging the patient (Naros and Gharabaghi, 2015). Recent studies explored automated adaptation of training difficulty in stroke rehabilitation of less severely affected patients (Metzger et al., 2014; Wittmann et al., 2015). More specifically, both robot-assisted rehabilitation of proprioceptive hand function (Metzger et al., 2014) and inertial sensor-based virtual reality feedback of the arm (Wittmann et al., 2015) benefit from assessment-driven adjustments of exercise difficulty. Furthermore, a direct comparison between adaptive BRI training and non-adaptive training (Naros et al., 2016b) or sham adaptation (Bauer et al., 2016a) in healthy patients revealed the impact of reinforcement-based adaptation for the improvement of performance. Moreover, the exercise difficulty has been shown to influence the learning incentive during the training; more specifically, the optimal difficulty level could be determined empirically while disentangling the relative contribution of neurofeedback specificity and sensitivity (Bauer et al., 2016b).
In the present 4-week pilot study, we combined these approaches and customized them for the requirements of patients with severe upper extremity impairment by applying a multi-joint exoskeleton for task-oriented arm and hand training in an adaptive virtual environment. Notably, due to the severity of their impairment, these patients were not able to practice the reach-to-grasp movements without the exoskeleton. The set-up was, however, limited to pure antigravity support, i.e., it provided passive rather than active assistance. Furthermore, it tested the feasibility of closed-loop online adaptation of exercise difficulty and aimed at automated progression of task challenge.
[ARTICLE] Therapists’ Perspective on Virtual Reality Training in Patients after Stroke: A Qualitative Study Reporting Focus Group Results from Three Hospitals – Full Text
Background. During the past decade, virtual reality (VR) has become a new component in the treatment of patients after stroke. Therefore aims of the study were (a) to get an insight into experiences and expectations of physiotherapists and occupational therapists in using a VR training system and (b) to investigate relevant facilitators, barriers, and risks for implementing VR training in clinical practice.
Methods. Three focus groups were conducted with occupational therapists and physiotherapists, specialised in rehabilitation of patients after stroke. All data were audio-recorded and transcribed verbatim. The study was analysed based on a phenomenological approach using qualitative content analysis.
Results. After code refinements, a total number of 1289 codes emerged out of 1626 statements. Intercoder reliability increased from 53% to 91% until the last focus group. The final coding scheme included categories on a four-level hierarchy: first-level categories are (a) therapists and VR, (b) VR device, (c) patients and VR, and (d) future prospects and potential of VR developments.
Conclusions. Results indicate that interprofessional collaboration is needed to develop future VR technology and to devise VR implementation strategies in clinical practice. In principal, VR technology devices were seen as supportive for a general health service model.
Stroke is a frequent cause of livelong disability in adulthood and is one of the most expensive diseases regarding patient-centred care . To reduce the burden of upper limb limitations and to improve patients’ outcomes and independence, new treatment concepts have to be developed and effectiveness of patient outcomes has to be investigated, respectively . Virtual reality (VR) is a novel computer technology that was adapted for rehabilitation over the past decade . It is a computer technology that simulates real-life learning while providing augmented feedback and a high intensity of massed practiced tasks . VR can be differentiated into immersive and nonimmersive gaming systems. Immersive systems enable players to move an avatar in a simulated environment. Nonimmersive systems often focus on arm or leg movements in simulated 3D environments . VR provides a safe environment for patients to explore functional capability without interference from their physical or cognitive limitations . As an example of a therapeutic VR system, YouGrabber (YG, YouRehab© Ltd.) will be explored in this study: it is a training system for upper limb training in stroke rehabilitation (Figure 1). It provides training of bimanual reaching and grasping in combination with different game options on a computer or television screen. Patients’ movements are captured by two size-adjustable data gloves and infrared arm tracking . As Saposnik and Levin reported in their meta-analysis, there are beneficial effects for upper limb rehabilitation using VR in combination with conventional treatment approaches . Analysed studies evaluated different aspects of VR including number of repetitions and exercise intensity. While rehabilitation targets are functional skills, most of VR implementation is working with simulations that are playful but not directly relevant to patients’ daily life . To maximise benefits, the therapeutic application of VR should be compatible with the therapeutic goal setting . Moreover, patients’ motivation and attention are important factors stimulating motor relearning after stroke .
Summary: Using virtual reality technology may allow people to regain motor control in damaged limbs, a new study reports.
Novel training may rehabilitate impaired limbs by allowing healthy limbs to lead “by example,” say TAU researchers.
A combination of traditional physical therapy and technology may improve the motor skills and mobility of an impaired hand by having its partner, more mobile hand lead by example through virtual reality training, new Tel Aviv University research suggests.
“Patients suffering from hemiparesis — the weakness or paralysis of one of two paired limbs — undergo physical therapy, but this therapy is challenging, exhausting, and usually has a fairly limited effect,” said lead investigator Prof. Roy Mukamel of TAU’s School of Psychological Sciences and Sagol School of Neuroscience, who conducted the research with his student Ori Ossmy. “Our results suggest that training with a healthy hand through a virtual reality intervention provides a promising way to repair mobility and motor skills in an impaired limb.” The research was published in Cell Reports.
Does the left hand know what the right hand is doing?
53 healthy participants completed baseline tests to assess the motor skills of their hands, then strapped on virtual reality headsets that showed simulated versions of their hands. The virtual reality technology, however, presented the participants with a “mirror image” of their hands — when they moved their real right hand, their virtual left hand would move.
In the first experiment, participants completed a series of finger movements with their right hands, while the screen showed their “virtual” left hands moving instead. In the next, participants placed motorized gloves on their left hands, which moved their fingers to match the motions of their right hands. Again, the headsets presented the virtual left hands moving instead of their right hands.
The research team found that when subjects practiced finger movements with their right hands while watching their left hands on 3D virtual reality headsets, they could use their left hands more efficiently after the exercise. But the most notable improvements occurred when the virtual reality screen showed the left hand moving while in reality the motorized glove moved the hand.
Tricking the brain
“We effectively tricked the brain,” said Prof. Mukamel.
“Technologically, these experiments were a big challenge,” Prof. Mukamel continued. “We manipulated what people saw and combined it with the passive, mechanical movement of the hand to show that our left hand can learn even when it is not moving under voluntary control.”
The researchers are optimistic that this research could be applied to patients in physical therapy programs who have lost the strength or control of one hand. “We need to show a way to obtain high-performance gains relative to other, more traditional types of therapies,” said Prof. Mukamel. “If we can train one hand without voluntarily moving it and still show significant improvements in the motor skills of that hand, we’ve achieved the ideal.”
The researchers are currently examining the applicability of their novel VR training scheme to stroke patients.
Funding: Funding provided by Japan Society for the Promotion of Science, Ministry of Education, Culture, Sports, Science and Technology Japan, Takeda Science Foundation.
Image Source: NeuroscienceNews.com image is in the public domain.
Original Research:Full open access research for “Neural Network Underlying Intermanual Skill Transfer in Humans” by Ori Ossmy and Roy Mukamel in Cell Reports. Published online December 13 2016 doi:10.1016/j.celrep.2016.11.009
Neural Network Underlying Intermanual Skill Transfer in Humans
•Unimanual training also enhances performance in the untrained hand (cross-education)
•Real-time manipulation of visual feedback enhances magnitude of cross-education
•Yoking movement of untrained to trained hand further increases cross-education
•Functional connectivity with SPL during training predicts cross-education
Physical practice with one hand results in performance gains of the other (un-practiced) hand, yet the role of sensory feedback and underlying neurophysiology is unclear. Healthy subjects learned sequences of finger movements by physical training with their right hand while receiving real-time movement-based visual feedback via 3D virtual reality devices as if their immobile left hand was training. This manipulation resulted in significantly enhanced performance gain with the immobile hand, which was further increased when left-hand fingers were yoked to passively follow right-hand voluntary movements. Neuroimaging data show that, during training with manipulated visual feedback, activity in the left and right superior parietal lobule and their degree of coupling with motor and visual cortex, respectively, correlate with subsequent left-hand performance gain. These results point to a neural network subserving short-term motor skill learning and may have implications for developing new approaches for learning and rehabilitation in patients with unilateral motor deficits.
“Neural Network Underlying Intermanual Skill Transfer in Humans” by Ori Ossmy and Roy Mukamel in Cell Reports. Published online December 13 2016 doi:10.1016/j.celrep.2016.11.009
We present a novel multi-user virtual reality (VR) environment for post-stroke rehabilitation that can be used independently in the home to improve upper extremity motor function. This project represents a collaborative multidisciplinary approach to upper extremity therapy that reinvents engagement with health, social communication and well-being for stroke survivors. This work is in the pre-clinical phase of an ongoing interdisciplinary research effort at the Rehabilitation Institute of Chicago which involves a team of artists, engineers, researchers and occupational therapists. This work bridges art, science and healthcare research. Our project attempts to extend traditional occupational therapy and make virtual reality art accessible for all people. It inspires a playful and natural social interaction in the comfort of the home setting for stroke survivors with hemiparesis by furthering social engagement through the rehabilitation exercises. It fosters interaction and collaboration between individual users and encourages the exchange of user-generated content. At the same time, the system captures continuous kinematic data, which can be used to better tailor therapy to the individual.