Posts Tagged virtual reality

[Abstract] Upper Limb Movement Modelling for Adaptive and Personalised Physical Rehabilitation in Virtual Reality – Thesis

Abstract

Stroke is one of the leading causes of disability with over three-quarters of patients experiencing an upper limb impairment varying in severity. Early, intense, and frequent physical rehabilitation is important for quicker recovery of the upper limbs and the prevention of further deterioration of their upper limb impairment. Rehabilitation begins almost immediately at the hospital. Once released from the hospital it is intended that patients continue their rehabilitation program at home supported by a community stroke team. However, there are two main barriers to rehabilitation continuing effectively at this stage. The first is limited contact with a physiotherapist or occupational therapist to guide and support an intensive rehabilitation programme. The second is that conventional rehabilitation is tough to maintain immediately after stroke due to fatigue, lack of concentration, depression and other effects. Stroke patients can find exercises monotonous and tiring, and a lack of motivation can result in patients failing to engage fully with their treatment. Lack of participation in prescribed rehabilitation exercises may affect recovery or cause deterioration of mobility.

This thesis examines the hypothesis that upper limb stroke rehabilitation can be made more accessible and enjoyable through the use of modern commercial virtual reality (VR) hardware, with personalised models of user hand motion adapted to user capability over time, and VR games with tasks that utilise natural hand gestures as input controls to execute personalised physical rehabilitation exercises. To support the investigation of this hypothesis a novel adaptive, gamebased, virtual reality (VR) rehabilitation system has been designed and developed for self-managed rehabilitation. Hands are tracked using a Leap Motion Controller, with hand movements and gestures used as in input controller for VR tasks. A user-centred design methodology was adopted, and the final version of the system was evolved through several versions and iterative testing and feedback through trials with able-bodied testers, stroke survivor volunteers, and practising clinicians.

A key finding of the research was that an adapted form of Fitts’s law, that models difficulty of reaching and touching objects in 3D interaction spaces, could be used to profile movement capability for able-bodied people and stroke patients vii in upper arm VR stroke rehabilitation. It was also found that even when Fitts’s law was less effective, that the statistics of the regression quality were still informative in profiling users. Fitts law regression statistics along with information on task performance (such as percentage of hits) could be used to adapt task difficulty or advising rest. Further, it was found that multiple regression could provide better movement capability profiles with a modified form of Fitts law to account for varying degrees of difficulty due to the angles of motion in 3D space. In addition, a novel approach was developed which profiled sectors of the 3D VR interaction space separately, rather than treat movement through the whole space as being equally difficult. This approach accounts for some stroke patients having more difficulty moving in some directions than others, e.g. up and left. Results demonstrate that this has potential but may need to be investigated further with stroke patients and with larger numbers of people.

The VR system that utilised the movement capability model was evolved over time with a user-centred design methodology, with input from able-bodied people, stroke patients, and clinicians. A final longitudinal study investigated the suitability of three bespoke games, the usability of the system over a longer time, and the effectiveness of the movement profiler and adaptive system. Throughout this experiment, the system provided informative user movement profile variations that could identify unique movement behaviour traits in individuals. Results showed that user performance varied over time and the adaptive system proved effective in changing the difficulty of the tasks for individuals over multiple sessions. The VR rehabilitation games incorporated enhanced gameplay and feedback, and users expressed enjoyment with the interactive experience. Throughout all of the experiments, users enjoyed wearing a VR headset, preferring it over a standard PC monitor. Most users subjectively felt that they were more effective in completing tasks within VR, and results from experiments provided empirical evidence to support this view. Results within this thesis support the proposal that an appropriately designed, adaptive gamebased VR system can provide an accessible, personalised and enjoyable rehabilitation system that can motivate more regular rehabilitation participation and promote improved motor function.

via Upper Limb Movement Modelling for Adaptive and Personalised Physical Rehabilitation in Virtual Reality — Ulster University

, , , , , , , , , ,

Leave a comment

[Abstract + References] Game Design Principles Influencing Stroke Survivor Engagement for VR-Based Upper Limb Rehabilitation: A User Experience Case Study – Proceedings

ABSTRACT

Engagement with one’s rehabilitation is crucial for stroke survivors. Serious games utilising desktop Virtual Reality could be used in rehabilitation to increase stroke survivors’ engagement. This paper discusses the results of a user experience case study that was conducted with six stroke survivors to determine which game design principles are or would be important for engaging them with a desktop VR serious games designed for the upper limb rehabilitation. The results of our study showed the game design principles that warrant further investigation are awareness, feedback, interactivity, flow and challenge; and also important to a great extent are attention, involvement, motivation, effort, clear instructions, usability, interest, psychological absorption, purpose and a first-person view.

References

  1. B. Ploderer, J. Stuart, V. Tran, T. Green, and J. Muller, “The transition of stroke survivors from hospital to home: understanding work and design opportunities,” in OZCHI, Brisbane, Australia, 2017, pp. 1–9.Google Scholar
  2. G. A. MacDonald, N. M. Kayes, and F. Bright, “Barriers and facilitators to engagement in rehabilitation for people with stroke: a review of the literature,” New Zealand Journal of Physiotherapy, vol. 41, p. 112, 2013.Google Scholar
  3. J. W. Burke, M. D. J. McNeill, D. K. Charles, P. J. Morrow, J. H. Crosbie, and S. M. McDonough, “Optimising engagement for stroke rehabilitation using serious games,” The Visual Computer, vol. 25, pp. 1085–1099, 2009.Google ScholarDigital Library
  4. G. C. Peron, L. I. B. dos Santos, L. M. Brasil, R. C. Silva, F. Bombonato, P. S. de Lima, et al., “Serious games in cognitive rehabilitation,” 2011, pp. 94–95.Google Scholar
  5. D. Jack, R. Boian, A. S. Merians, M. Tremaine, G. C. Burdea, S. V. Adamovich, et al., “Virtual reality-enhanced stroke rehabilitation,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 9, pp. 308–318, 2001.Google ScholarCross Ref
  6. D. Webster and O. Celik, “Systematic review of Kinect applications in elderly care and stroke rehabilitation,” Journal of neuroengineering and rehabilitation, vol. 11, pp. 108–108, 2014.Google ScholarCross Ref
  7. A. Henderson, N. Korner-Bitensky, and M. Levin, “Virtual reality in stroke rehabilitation: a systematic review of its effectiveness for upper limb motor recovery,” Topics in stroke rehabilitation, vol. 14, pp. 52–61, 2007.Google ScholarCross Ref
  8. D. Sadihov, B. Migge, R. Gassert, and Y. Kim, “Prototype of a VR upper-limb rehabilitation system enhanced with motion-based tactile feedback,” pp. 449–454.Google Scholar
  9. O. Dele-Ajayi, J. Sanderson, R. Strachan, and A. Pickard, “Learning mathematics through serious games: An engagement framework,” 2016, pp. 1–5.Google Scholar
  10. H. Jokinen, S. Melkas, R. Ylikoski, T. Pohjasvaara, M. Kaste, T. Erkinjuntti, et al., “Post-stroke cognitive impairment is common even after successful clinical recovery,” European Journal of Neurology, vol. 22, pp. 1288–1294, 2015.Google ScholarCross Ref
  11. K. Lohse, N. Shirzad, A. Verster, N. Hodges, and H. F. M. Van der Loos, “Video Games and Rehabilitation: Using Design Principles to Enhance Engagement in Physical Therapy,” Journal of Neurologic Physical Therapy, vol. 37, pp. 166–175, 2013.Google ScholarCross Ref
  12. T. M. Connolly, T. Hainley, E. Boyle, G. Baxter, and P. Moreno-Ger, Psychology, Pedagogy, and Assessment in Serious Games. Hershey, Pennsylvania: Information Science Reference, 2014.Google Scholar
  13. A. K. Przybylski, C. S. Rigby, and R. M. Ryan, “A Motivational Model of Video Game Engagement,” Review of General Psychology, vol. 14, pp. 154–166, 2010.Google ScholarCross Ref
  14. M. A. Bruno and L. Griffiths, “Serious games: supporting occupational engagement of people aged 50+ based on intelligent tutoring systems/Juegos serios: apoyo a la participación ocupacional de personas mayores de 50 años basado en sistemas de tutoría inteligente,” Ingeniare: Revista Chilena de Ingenieria, vol. 22, p. 125, 2014.Google ScholarCross Ref
  15. S. Arnab, I. Dunwell, and K. Debattista, Serious games for healthcare: applications and implications. Hershey, PA: Medical Information Science Reference, 2013.Google ScholarCross Ref
  16. R. S. Kalawsky, The Science of Virtual Reality and Virtual Environments: A Technical, Scientific and Engineering Reference on Virtual Environments. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc., 1993.Google Scholar
  17. K. Pimentel and K. Teixeira, Virtual Reality: Through the New Looking Glass, 2nd ed. New York: Intel/McGraw-Hill, 1995.Google Scholar
  18. S. Rabin, Introduction to game development, 2nd ed. Boston, MA: Course Technology, Cengage Learning, 2010.Google Scholar
  19. A. Oxarart, J. Weaver, A. Al-Bataineh, and T. A. B. Mohamed, “Game Design Principles and Motivation,” International Journal of Arts & Sciences, vol. 7, p. 347, 2014.Google Scholar
  20. H. Desurvire and D. Wixon, “Game principles: choice, change & creativity: making better games,” pp. 1065–1070.Google Scholar
  21. R. McDaniel, S. Fiore, M., and D. Nicholson, “Serious Storytelling: Narrative Considerations for Serious Games Researchers and Developers,” in Serious Game Design and Development: Technologies for Training and Learning, ed Hershey, PA, USA: IGI Global, 2010, pp. 13–30.Google Scholar
  22. R. M. Martey, K. Kenski, J. Folkestad, L. Feldman, E. Gordis, A. Shaw, et al., “Measuring Game Engagement: Multiple Methods and Construct Complexity,” Simulation & Gaming, vol. 45, pp. 528–547, 2014.Google ScholarDigital Library
  23. H. L. O’Brien and E. G. Toms, “What is user engagement? A conceptual framework for defining user engagement with technology,” Journal of the American Society for Information Science and Technology, vol. 59, pp. 938–955, 2008.Google ScholarDigital Library
  24. J. H. Brockmyer, C. M. Fox, K. A. Curtiss, E. McBroom, K. M. Burkhart, and J. N. Pidruzny, “The development of the Game Engagement Questionnaire: A measure of engagement in video game-playing,” Journal of Experimental Social Psychology, vol. 45, pp. 624–634, 2009.Google ScholarCross Ref
  25. N. Whitton, “Game Engagement Theory and Adult Learning,” Simulation & Gaming, vol. 42, pp. 596–609, 2011.Google ScholarCross Ref
  26. B. Bongers and S. Smith, “Interactivated rehabilitation device,” in OZCHI, Brisbane, Australia, 2010, pp. 410–411.Google Scholar
  27. E. V. Ekusheva and I. V. Damulin, “Post-Stroke Rehabilitation: Importance of Neuroplasticity and Sensorimotor Integration Processes,” Neuroscience and Behavioral Physiology, vol. 45, pp. 594–599, 2015.Google ScholarCross Ref
  28. Y. Sagi, I. Tavor, S. Hofstetter, S. Tzur-Moryosef, T. Blumenfeld-Katzir, and Y. Assaf, “Learning in the Fast Lane: New Insights into Neuroplasticity,” Neuron, vol. 73, pp. 1195–1203, 2012.Google ScholarCross Ref
  29. S. Hofstetter, I. Tavor, S. Tzur Moryosef, and Y. Assaf, “Short-term learning induces white matter plasticity in the fornix,” The Journal of neuroscience: the official journal of the Society for Neuroscience, vol. 33, p. 12844, 2013.Google ScholarCross Ref
  30. I. Tavor, S. Hofstetter, and Y. Assaf, “Micro-structural assessment of short term plasticity dynamics,” NeuroImage, vol. 81, pp. 1–7, 2013.Google ScholarCross Ref
  31. Murdoch University. (2015, 6/3/2019). Virtual Reality software brings hope to stroke survivors. Available: http://web.archive.org/web/20180331035704/http://media.murdoch.edu.au/virtualreality-software-brings-hope-to-stroke-survivorsGoogle Scholar
  32. S. Brown. (2010). Likert Scale Examples for Surveys. Available: http://www.extension.iastate.edu/Documents/ANR/LikertScaleExamplesforSurveys.pdfGoogle Scholar
  33. Oxford Dictionary of English, 3rd ed. New York, NY: Oxford University Press, 2010.Google Scholar

via Game Design Principles Influencing Stroke Survivor Engagement for VR-Based Upper Limb Rehabilitation | Proceedings of the 31st Australian Conference on Human-Computer-Interaction

, , , , , , , ,

Leave a comment

[ARTICLE] Upper Extremity Function Assessment Using a Glove Orthosis and Virtual Reality System – Full Text

Abstract

Hand motor control deficits following stroke can diminish the ability of patients to participate in daily activities. This study investigated the criterion validity of upper extremity (UE) performance measures automatically derived from sensor data during manual practice of simulated instrumental activities of daily living (IADLs) within a virtual environment. A commercial glove orthosis was specially instrumented with motion tracking sensors to enable patients to interact, through functional UE movements, with a computer-generated virtual world using the SaeboVR software system. Fifteen stroke patients completed four virtual IADL practice sessions, as well as a battery of gold-standard assessments of UE motor and hand function. Statistical analysis using the nonparametric Spearman rank correlation reveals high and significant correlation between virtual world-derived measures and the gold-standard assessments. The results provide evidence that performance measures generated during manual interactions with a virtual environment can provide a valid indicator of UE motor status.

Introduction

Virtual world-based games, when combined with human motion sensing, can enable a neurorehabilitation patient to engage in realistic occupations that involve repetitive practice of functional tasks (). An important component of such a system is the ability to automatically track patient movements and use those data to produce indices related to movement quality (). Before these technology-derived measures can be considered relevant to clinical outcomes, criterion validity must be established. If validated, measures of virtual task performance may reasonably be interpreted as reflective of real-world functional status.

The objective of the study described in this article was to investigate the criterion validity of upper extremity (UE) performance measures automatically derived from sensor data collected during practice of simulated instrumental activities of daily living (IADLs) in a virtual environment. A commercially available SaeboGlove orthosis () was specially instrumented to enable tracking of finger and thumb movements. This instrumented glove was employed with an enhanced version of the Kinect sensor-based SaeboVR software system () to enable employment of the hand, elbow, and shoulder in functional interactions with a virtual world. Performance measures were automatically generated during patient use through a combination of arm tracking data from the Kinect and the glove’s finger and thumb sensors. The primary investigational objective was to determine whether performance indices produced by this system for practice of virtual IADLs are valid indicators of a stroke patient’s UE motor status.

Previous investigations into combining hand tracking with video games to animate UE therapy have produced evidence for the efficacy of such interventions. A recent study compared a 15-session hand therapy intervention using a smart glove system and video games with a usual care regimen (). Stroke patients using the smart glove system realized greater gains in Wolf Motor Function Test (WMFT) score compared with dosage-balanced conventional therapy. Another study investigating a similar glove-based device found significantly greater improvements in Fugl-Meyer and Box and Blocks test results for stroke patients who performed 15 sessions that included the technology-aided therapy compared with subjects receiving traditional therapy only (). An instrumented glove has also been used to support video game therapy that incorporates gripping-like movements and thumb-finger opposition ().

Past research into the use of human motion tracking (sometimes referred to as motion capture) technologies for assessment of UE function has produced encouraging results. One group of researchers compared naturalistic point-to-point reaching movements with standardized reaching movements embedded in a virtual reality system, and established concurrent validity between the two (). An investigation involving a device that incorporates handgrip strength and pinch force measurement into virtual reality exercises provided support for system use as an objective evaluation of hand function, and for the potential of replacing conventional goniometry and dynamometry (). In another study, researchers employed a Kinect sensor in a software system that attempts to emulate a subset of the Fugl-Meyer Upper Extremity (FMUE) assessment (). Pearson correlation analysis between the Kinect-derived scores and traditionally administered FMUE test results for 41 hemiparetic stroke patients revealed a high correlation. Previous research involving the SaeboVR system established a moderate and statistically significant correlation between virtual IADL performance scores and the WMFT (). Due to limitations of the Kinect optical tracking system, this previous work involving the SaeboVR system did not include tracking of grasp-release manual interactions with virtual objects (). The present research addresses this limitation by fusing data from the Kinect sensor with data from finger- and wrist-mounted sensors on the SaeboGlove orthosis to reconstruct the kinematic pose of the patient’s UE.

The use of an assistive glove orthosis in the present work fills an important clinical need. Inability to bring the hand and wrist into a neutral position due to weakness and/or lack of finger extension can prevent participation in occupation-oriented functional practice (). A common technique to enable stroke patients to achieve a functional hand position (and thus participate in rehabilitation) is a dynamic splint that supports finger and/or wrist extension. When larger forces are necessary (e.g., to overcome abnormal muscle tone), an outrigger-type splint may be employed. For patients with no more than mild hypertonicity, a lower-profile device such as the SaeboGlove orthosis () can be used. Employment of an assistive glove orthosis in the context of virtual IADLs practice thus addresses some of the leading causes of hand motor control deficits following stroke and their adverse impact on ability to participate in daily activities ().

Method

Participants

Candidates were recruited from a population of stroke patients receiving in-patient rehabilitation care, outpatient rehabilitation, or who had been previously discharged from rehabilitative care at the UVA Encompass Health Rehabilitation Hospital (Charlottesville, VA, USA). Table 1 includes the study characteristics. Of 17 patients enrolled in the study, 15 completed the protocol. One subject dropped out due to unrelated illness. A second subject was disenrolled due to an inability to adequately express an understanding of consent during re-verification at the beginning of the first post-consent study session.

Table 1.

Patient Characteristics (n = 17).

Age, years, median (range) 67 (25-83)
Time since stroke onset in months, median (range) 12 (1-72)
Sex, M/F, n (%) 10 (59)/7 (41)
Race category, Black/White, n (%) 3 (18)/14 (82)
Ethnic category, Hispanic/non-Hispanic, n (%) 0 (0)/17 (100)
Side of hemiplegia, L/R, n (%) 10 (59)/7 (41)
Affected side dominance, dominant/nondominant, n (%) 9 (53)/8 (47)

All study activities were conducted under the auspices of the University of Virginia Institutional Review Board for Health Sciences Research (IRB-HSR). All study sessions took place in a private room within the UVA Encompass Health outpatient clinic between October 20, 2017, and February 9, 2018. Licensed Occupational Therapists trained in study procedures and registered with the IRB-HSR were responsible for all patient contact, recruitment, consent, and protocol administration.

Verification of inclusion/exclusion criteria was through a three-step process including an initial medical record review prior to recruitment, verbal confirmation prior to administration of consent, and an evaluation screen conducted by a study therapist following consent. Inclusion criteria included history of stroke with hemiplegia, ongoing stroke-related hand impairment, sufficient active finger flexion at the metacarpal phalangeal joint in at least one finger to be detected by visual observation by a study therapist, antigravity strength at the elbow to at least 45° of active flexion, antigravity shoulder strength to at least 30° each in active flexion and abduction/adduction, and 15° in active shoulder rotation from an upright seated position. Participants had visual acuity with corrective lenses of 20/50 or better and were able to understand and follow verbal directions. The study excluded patients with visual field deficit in either eye that would impair ability to view the computer monitor and/or with hemispatial neglect that would impair an individual’s ability to process and perceive visual stimuli. The study also excluded individuals with motor limb apraxia, significant muscle spasticity, or contractures of the muscles, joints, tendons, ligaments, or skin that would restrict normal UE movement.

Materials

A commercial SaeboGlove orthosis was fitted with wrist and finger motion sensors to permit tracking of finger joint angles during grasp-release interactions with a virtual environment. The instrumented glove orthosis is shown in Figure 1. The sensors were attached to the existing tensioner band hooks on the dorsal side of each glove finger. An electronics enclosure mounted to the palmar side of the SaeboGlove’s plastic wrist splint processes the sensor data and transmits information to a personal computer (PC) that hosts the modified SaeboVR software. Data from both the SaeboGlove-integrated sensors and from a Kinect sensor were used by a custom motion capture algorithm, which employs a human UE kinematics model to produce real-time estimates of arm, wrist, and finger joint angles.

An external file that holds a picture, illustration, etc.Object name is 10.1177_1539449219829862-fig1.jpg

Figure 1.
SaeboGlove orthosis with sensors to track grasp interactions.

[…]

 

Continue —->  Upper Extremity Function Assessment Using a Glove Orthosis and Virtual Reality System

, , , , , , , , , ,

Leave a comment

[ARTICLE] Feasibility, Safety and Efficacy of a Virtual Reality Exergame System to Supplement Upper Extremity Rehabilitation Post-Stroke: A Pilot Randomized Clinical Trial and Proof of Principle – Full Text

Abstract

(1) Background: Increasing the amount of therapy time has been shown to improve motor function in stroke survivors. However, it is often not possible to increase the amount of therapy time provided in the current one-on-one therapy models. Rehabilitation-based virtual reality exergame systems, such as Jintronix, can be offered to stroke survivors as an adjunct to traditional therapy. The goal of this study was to examine the safety and feasibility of providing additional therapy using an exergame system and assess its preliminary clinical efficacy.
(2) Methods: Stroke survivors receiving outpatient rehabilitation services participated in this pilot randomized control trial in which the intervention group received 4 weeks of exergaming sessions in addition to traditional therapy sessions.
(3) Results: Nine subjects in the intervention and nine subjects in the control group completed the study. The intervention group had at least two extra sessions per week, with an average duration of 44 min per session and no serious adverse events (falls, dizziness, or pain). The efficacy measures showed statistically meaningful improvements in the activities of daily living measures (i.e., MAL-QOM (motor activity log-quality of movement) and both mobility and physical domains of the SIS (stroke impact scale) with mean difference of 1.0%, 5.5%, and 6.7% between the intervention and control group, respectively) at post-intervention.
(4) Conclusion: Using virtual reality exergaming technology as an adjunct to traditional therapy is feasible and safe in post-stroke rehabilitation and may be beneficial to upper extremity functional recovery.

1. Introduction

Hemiplegia, weakness of one side of the body, is a common consequence of stroke that can lead to significant functional impairments, including loss of arm function that occurs in up to 85% of stroke survivors [1]. The impact of arm-related limitations on activities of daily living, leisure activities, or work is significant as the arm plays a central role in a person’s life from the ability to perform basic activities of daily life to carrying out family and social roles. Guidelines indicate that rehabilitation can improve upper extremity (UE) motor control and functional status post-stroke [2]. Intense and repetitive training post-stroke is widely recognized as being essential to maximize recovery and promote plasticity in the central nervous system [2,3,4,5,6]. However, in reality, the feasibility of providing intensive rehabilitation may be limited in a rehabilitation setting by a lack of resources or motivation from the patient [7]. Furthermore, stroke survivors discharged from acute care receive physical and occupational therapy services primarily in rehabilitation centers, on an in- and out-patient basis or at home, but budgetary constraints and shortage of specialized health care professionals limit accessibility to much needed rehabilitation services.
New models of service delivery and maximizing the use of existing resources are therefore essential. With the emergence of interactive technologies or “gamified” products, innovative treatment strategies are being developed. Virtual reality (VR) and computer games are recent technologies that, as they become more accessible and affordable [8], are increasingly being used in rehabilitation to allow patients to engage in repetitive practice of specific tasks. The so-called exergames or exergaming reflect the idea of exercising through computer games. A number of published reviews and meta-analyses have examined the use of VR and video games for post-stroke rehabilitation, focusing on or including UE rehabilitation [3,4,6,8,9,10,11].
Saposnik and his colleagues [9] examined the effectiveness of rehabilitation using VR on UE motor function post-stroke in a meta-analysis study. In total, 11 of the 12 included studies (5 randomized controlled trials and 7 pre-post interventions) showed a benefit on the primary outcome, with the pooled randomized controlled trials showing a 4.9 higher chance of improvement in motor impairment when VR was used in comparison to control. Similarly, another meta-analysis study included a subgroup of studies related to UE function [6] and showed that VR had a significant effect on arm function (seven studies) and activities of daily living (ADL) (three studies) in comparison to control groups. The updated Cochrane Review of the meta-analysis concluded that virtual reality has a statistically significant effect on upper limb function (based on 12 studies) and ADL outcome (based on 8 studies) [12]. Another meta-analysis looked at the effect of virtual environments and commercial games on each category of the International Classification of Function, Disability, and Health (ICF), i.e., body function, activity, and participation, in post-stroke rehabilitation [11]. The authors reported that there was a significant effect of using virtual environments in improving all three ICF categories and that these outcome improvements by VR rehabilitation are moderately higher than conventional therapy [11]. However, there is still insufficient evidence regarding the best dose of therapy, timing, and types of programs. In addition, few studies report the users’ perception of these technologies, for both patients and therapists, although Lange and her colleagues [4] discussed the importance of activity enjoyment in their review. Celinder and Peoples [13] studied patients’ experiences through interviews and observation of patients using the Wii Sports for in-patient rehabilitation post-stroke. Most patients reported that the Wii provides them with variety, more stimulation, and more meaningful activities in their rehabilitation. Overall, studies agree that there is limited but promising findings that VR and video games, when combined with conventional rehabilitation, have a positive impact on recovery post-stroke. Furthermore, the literature in the field of technology adoption suggests that the user’s perception plays an important role in the actual use of the technology [14].
The Jintronix system (Jintronix Inc., www.jintronix.com), based on the Microsoft Kinect technology, is one such product that allows patients who have had a stroke to train UE movements independently using challenging and engaging programs tailored to their level of ability. This exergame system allows therapists to objectively track patients’ activities during their recovery process and to adjust, as required, the training program. Graded tasks that challenge and provide feedback to the patient can optimize motor learning [2,15]; this system has embedded this concept in their exergames. In addition, eventually, the tracking functionality that the exergame system offers could allow patients to train without direct therapist supervision, thereby offering interesting opportunities for increased dosage of in-clinic rehabilitation as well as for home-based tele-rehabilitation. In other words, following a stroke, people could participate in a more intensive rehabilitation training without increasing staffing. That being said, prior to using this exergame system in a clinical setting when used as an adjunct to conventional therapy, its feasibility, safety, and efficacy must be assessed.
The goals of this pilot study were to assess the feasibility and safety of the rehabilitation exergaming system and to provide preliminary evidence regarding its clinical efficacy for UE functional recovery post-stroke as a supplement to conventional rehabilitation services, as proposed by Saposnik and colleagues [9]. The results of this study will serve as a basis for a larger multicenter trial, in order to determine the effectiveness of exergame systems as a supplement to UE therapy post-stroke.[…]

Continue —->  IJERPH | Free Full-Text | Feasibility, Safety and Efficacy of a Virtual Reality Exergame System to Supplement Upper Extremity Rehabilitation Post-Stroke: A Pilot Randomized Clinical Trial and Proof of Principle | HTML

Ijerph 17 00113 g001

Figure 1. The Jintronix rehabilitation exergaming system.

 

, , , , , , , , , ,

Leave a comment

[Abstract] Examining the potential of virtual reality to deliver remote rehabilitation

Abstract

Remote workers are particularly prone to mental health problems (Bowers et al., 2018). Unfortunately, it is often difficult for them to access the quality psychological help that they need. As a result, psychological treatment is increasingly being delivered to remote workers via telehealth (videoconferencing and telephone calls). However, the perceived remoteness of the therapist during such treatments can greatly hinder progress. This project examined the potential of virtual reality (VR) to deliver psychotherapy to workers located in remote locations (since it can make people separated by great distances feel that they are “present” in the same virtual space). The study compared the experiences of 30 ‘clients’ who participated in both VR and Skype-based mock counselling sessions (delivered by trained psychotherapists). Overall, VR was found to outperform Skype:

1) as a therapeutic tool,

2) in terms of the perceived realism of the session; and

3), in terms of the degree of presence it generated in the clients and the therapists.

Clients did not report feeling sick or stressed when using VR and found it as easy to use as Skype. These study findings (based on formal questionnaire data) were also confirmed by interviews with both the therapists and clients.

Highlights

  • This project examined the potential of virtual reality to deliver psychotherapy to workers located in remote locations.
  • The study compares the experiences of 30 ‘clients’ who participated in both VR and Skype-based mock counselling.
  • VR was found to outperform Skype: as a therapeutic tool, perceived realism of the session; and the degree of presence.
  • Clients did not report feeling sick or stressed when using VR and found it as easy to use as Skype.

via Examining the potential of virtual reality to deliver remote rehabilitation – ScienceDirect

, , , , , , , , , ,

Leave a comment

[ARTICLE] Walking with head-mounted virtual and augmented reality devices: Effects on position control and gait biomechanics – Full Text

Abstract

What was once a science fiction fantasy, virtual reality (VR) technology has evolved and come a long way. Together with augmented reality (AR) technology, these simulations of an alternative environment have been incorporated into rehabilitation treatments. The introduction of head-mounted displays has made VR/AR devices more intuitive and compact, and no longer limited to upper-limb rehabilitation. However, there is still limited evidence supporting the use of VR and AR technology during locomotion, especially regarding the safety and efficacy relating to walking biomechanics. Therefore, the objective of this study is to explore the limitations of such technology through gait analysis. In this study, thirteen participants walked on a treadmill in normal, virtual and augmented versions of the laboratory environment. A series of spatiotemporal parameters and lower-limb joint angles were compared between conditions. The center of pressure (CoP) ellipse area (95% confidence ellipse) was significantly different between conditions (p = 0.002). Pairwise comparisons indicated a significantly greater CoP ellipse area for both the AR (p = 0.002) and VR (p = 0.005) conditions when compared to the normal laboratory condition. Furthermore, there was a significant difference in stride length (p<0.001) and cadence (p<0.001) between conditions. No statistically significant difference was found in the hip, knee and ankle joint kinematics between the three conditions (p>0.082), except for maximum ankle plantarflexion (p = 0.001). These differences in CoP ellipse area indicate that users of head-mounted VR/AR devices had difficulty maintaining a stable position on the treadmill. Also, differences in the gait parameters suggest that users walked with an unusual gait pattern which could potentially affect the effectiveness of gait rehabilitation treatments. Based on these results, position guidance in the form of feedback and the use of specialized treadmills should be considered when using head-mounted VR/AR devices.

Introduction

Over the past two decades, the application of virtual reality (VR) technology in a healthcare setting has become increasingly popular. It has been incorporated into clinical practices such as in the rehabilitation of stroke survivors, as well as patients with cerebral palsy and multiple sclerosis [13]. There is ample evidence suggesting that VR-based rehabilitation facilitates upper limb motion [4] and dynamic balance [5] among stroke survivors. More recently, research groups have also investigated the use of VR in dynamic situations (i.e. treadmill walking), aiming to improve balance and facilitate gait recovery [69].

In current clinical practice, gait retraining often includes treadmill training under the supervision of practitioners or through provision of real-time biofeedback. It is a widely adopted technique that aims to permanently correct faulty gait patterns and has been found to be effective in both walking and running gait modifications [1012]. For example, a recently published randomized controlled trial showed that gait retraining was an effective intervention for reduction of knee loading and also improved symptoms among patients with early knee osteoarthritis [10]. Incorporation of VR technology into conventional gait retraining has the potential to further enhance training outcomes. VR allows users to actively interact with a simulated environment in real-time and offers the opportunity to practice skills acquired in the virtual environments to everyday life [13]. VR-based gait retraining has the potential to facilitate implicit learning, enhance variety, and actively engage the patient during training. These attributes are crucial in the optimization of motor learning and could maximize the training effect [14].

Walking is normally an automatic process. It has been suggested that conscious modification to walking patterns could affect gait retraining adaptations [15]. A previous study found that subjects who trained with distraction were able to retain the training effect longer than the group who focused on correction [15]. VR-based retraining could include different tasks and games while the patients modify their gait pattern as it could help patients to maintain focus and promote implicit motor learning. Moreover, the training environment, feedback type and level of difficulty of tasks can be manipulated within the VR environment relatively effortlessly for the clinician, as compared to conventional gait retraining. Variation in training has been shown to promote a more robust motor pattern and favor adaptation [16,17]. Moreover, motivation and adherence among patients can also be improved with more variation and an adjustable level of difficulty provided in the VR-based training [18]. Stroke survivors were previously found to be more actively engaged in a VR-based training than a conventional task-oriented intervention to improve motor function [19]. The training environment can be designed to simulate real-life activities and include task-specific training and a natural experience can be achieved through immersive VR devices, such as using a head-mounted display (HMD) [20]. Studies have supported task-specific motor skill training with VR in helping to drive neuroplasticity in individuals with progressive neurodegenerative disorder [4,21].

Although multiple studies have reported positive results of gait retraining using VR among various patient groups within the lab [1,5,22,23], there is still little understanding of the limitations and challenges for using VR technology clinically. One overriding concern for using VR technology in clinical applications, especially an HMD, is safety. The user may not be able to recognize his/her own body position when using an immersive VR device, which could result in physical injuries, particularly if the user fails to stay within the boundaries of the treadmill. Suspension devices (i.e. an over-head harness) have been used for protection during VR-based gait rehabilitation [8], and a recent study showed that both young and older adults were able to use HMD during walking without adverse effects [21]. However, the limit of VR technology on safety was not quantified or discussed. Recent technological advances in both the hardware and software of HMD might allow for safer use. However, there is still a need for evidence-based support and quantifiable data, which could help with practical considerations among VR applications in a clinical setting.

Another concern for gait rehabilitation would be the regularity and quality of gait. Through studying spatiotemporal gait parameters, some studies have reported that walking in a projected VR environment can induce gait instability even in healthy participants [24,25]. Nowadays, VR-based gait retraining using HMD focuses primarily on gait restoration after stroke [8]; the changes in natural gait due to the use of HMD may not be clinically significant. However, it is crucial for particular patient groups undergoing gait modification to maintain a certain level of regularity in their gait pattern. For instance, knee loading can be affected by spatiotemporal parameters such as cadence and step length [26] and VR was previously found to alter such parameters in an over-ground setting [24]. The treatment effect of gait retraining in reducing knee loading would likely be affected if the patient’s baseline walking gait was already altered by the use of HMD or other VR devices. The aforementioned studies did not quantify the changes in walking biomechanics when using a HMD, therefore, this study aimed to identify gait parameters that were affected by the use of HMD.

An alternative to VR is Augmented Reality (AR), which does not fully immerse the user in a simulated environment but includes virtual elements that are superimposed on a real-world view [27]. For example, external cues on foot placement could be overlaid on to the walking surface in order to facilitate gait adjustments [28,29]. The addition of feedback in AR-based gait retraining allows for variations in training and could enhance the gait retraining effect. Yet, there is also a lack of understanding of the limitation of using AR devices. Therefore, this study also aimed to examine the biomechanical changes induced by the HMD within an AR setting.

This study was designed to assess whether the use of commercially available HMD in VR and AR settings were suitable for clinical gait retraining. Specifically, the aim was to quantify the limitations of current VR and AR technology based on two practical concerns for clinical applications: 1) safety: the ability of the user to maintain a relatively stable position within the treadmill and 2) natural gait patterns: deviation of walking biomechanics from that of normal-treadmill walking. We hypothesized that there would be variations in the control of body position relative to the treadmill between both VR and AR conditions when compared with normal-treadmill walking. Also, based on altered gait biomechanics reported with the use of HMD in an over-ground setting [24], we hypothesized there would be variation in the spatiotemporal and joint kinematic measures while walking in VR and AR conditions, when compared with normal-treadmill walking.

Materials and methods

Participants

A total of 13 participants (7 females, 6 males; age = 24.6 ± 4.5 years; weight = 63.1 ± 14.5 kg; height = 1.68 ± 0.11 m) were recruited for this study through convenient sampling, which is a comparable sample size to previous studies [3032]. Participants were free of any musculoskeletal, neurological, neuromuscular or cardiovascular pathology that might hinder walking. The experimental procedures were reviewed and approved by the Departmental Research Committee of the department of Rehabilitation Sciences, The Hong Kong Polytechnic University (Ref.: HSEARS20161018001) and written informed consent was obtained from all participants prior to the experiment.

Experimental procedures

Participants were asked to walk at a self-selected pace for four minutes to allow for treadmill adaptation prior to data collection [33]. Anthropometric data, including leg length, knee width and ankle width [3436], were recorded and 39 reflective markers were affixed to specific bony landmarks based on the Vicon Plug-in-Gait® full body model [34]. The marker model was previously established for the measurement of lower-limb kinematics [35]. This study was designed to assess HMD in VR and AR settings using a commercially available model within a typical clinical setting. Thus, the conditions were designed to be simple and without the use of additional lab equipment. All walking trials were conducted on a dual-belt instrumented treadmill (Force-sensing tandem treadmill, AMTI, Watertown, MA, USA; length x width = 1.2 x 0.6 m). Participants wore their own usual shoes and walked under different conditions at 3.0 km/h (0.83 m/s) for three minutes each. The three conditions were Control, VR and AR, details were as follows:

Control: Treadmill walking without the HMD;

Virtual reality (VR): Immersive 360° panoramic image of the laboratory captured by the Samsung Gear 360 Cam (Samsung, Seoul, South Korea), set up instructions and image file used are provided in the supporting information (S1 File and S1 Fig).

Augmented reality (AR): Real-time display through the rear camera of the HMD, set up instructions are provided in the supporting information (S2 File).

For the AR and VR conditions, participants wore a head-mounted VR device (Samsung Gear VR SM-R322 and Samsung Galaxy S7, Samsung, Seoul, South Korea; width x height x depth: 201.93 x 92.71 x 116.33 mm). The immersive VR/AR environment within this study refers to the panoramic display in a first-person perspective with complete visual obstruction to the real-world environment. The HMD used in this study weighs a total of 470 g, which is comparable to typical commercial HMD models (HTC VIVE Pro: 555 g [37] and Oculus Rift DK2: 440 g [38]). Adjustments to the device were made for fit, focus, and orientation for each participant. Participant’s comfort was confirmed through subjective reporting before the beginning of each walking trial.

The test sequence was randomized using a web-based software (www.randomizer.org). To ensure safety, participants were supported by an overhead safety harness providing 0% bodyweight support. The experimental setup is indicated in Fig 1. The individual in Fig 1 of this manuscript has given written informed consent (as outlined in PLOS consent form) to publish the photograph.

thumbnail

Ground reaction force and coordinates of the center of pressure (CoP) were sampled through the instrumented treadmill at 1,000 Hz. Marker trajectories were sampled at 200 Hz using an 8-camera motion capture system (Vicon, Oxford Metrics Group, UK). The instrumented treadmill and motion capture system were synchronized and were set for data collection for three minutes after the treadmill reached the testing speed.[…]

 

Continue —->  Walking with head-mounted virtual and augmented reality devices: Effects on position control and gait biomechanics

, , , , ,

Leave a comment

[Abstract] Effectiveness of Virtual Reality- and Gaming-Based Interventions for Upper Extremity Rehabilitation Post-Stroke: A Meta-Analysis

Abstract

Objective

To investigate the efficacy of virtual reality (VR)- and gaming-based interventions for improving upper extremity function post-stroke, and to examine demographic and treatment-related factors that may moderate treatment response.

Data Sources

A comprehensive search was conducted within the PubMed, CINAHL/EBSCO, SCOPUS, Ovid MEDLINE and EMBASE databases for articles published between 2005 and 2019 (PROSPERO Registration number 95052).

Study Selection

Articles investigating gaming and VR methods of treatment for upper extremity weakness were collected with the following study inclusion criteria: 1) participants aged 18 or older with upper extremity deficits, 2) randomized controlled trials or prospective study design, 3) Downs-Black rating score of >= 18, and 4) outcome measure was the Wolf Motor Functioning Test (WMFT), the Fugl-Meyer (FM) or the Action Research Arm Test (ARAT).

Data Extraction

Thirty-eight articles met inclusion criteria. The primary outcome was proportional improvement on the WMFT, FM, or ARAT. The following individual or treatment factors were extracted: VR/gaming dose, total treatment dose, chronicity (> or < 6 months), severity of motor impairment, and presence of a gaming component.

Data analysis

Random effects meta-analysis models were utilized to quantify 1) the proportional recovery that occurs following VR/gaming, 2) the comparative treatment effect of VR/gaming versus conventional physiotherapy, and 3) whether the benefit of virtual reality differed based on participant characteristics or elements of the treatment.

Results

On average, VR/gaming interventions produced an improvement of 28.5% of the maximal possible improvement. Dose and severity of motor impairment did not significantly influence rehabilitation outcomes. Treatment gains were significantly larger overall (10.8%) when the computerized training involved a gaming component versus just visual feedback. VR/gaming interventions showed a significant treatment advantage (10.4%) over active control treatments.

Conclusions

Overall, VR/gaming-based upper extremity rehabilitation post-stroke appears to be more effective than conventional methods. Further in-depth study of variables impacting improvement, such as individual motor presentation, treatment dose, and the relationship between the two, are needed.

via Effectiveness of Virtual Reality- and Gaming-Based Interventions for Upper Extremity Rehabilitation Post-Stroke: A Meta-Analysis – ScienceDirect

, , , , , , ,

Leave a comment

[Abstract] Using telerehabilitation to improve cognitive function in post-stroke survivors

Post-stroke cognitive disorders can affect different domains, depending on typology of stroke and lesion localization, onset time, age and diagnostic tools used. In recent years, telerehabilitation using virtual reality has been used to reduce the healthcare costs encouraging continuity of care.

The aim of our study is to evaluate the efficacy of a virtual reality rehabilitation system in improving cognitive function in stroke survivors. Forty patients affected by stroke were enrolled in this study and randomized into either the control or the experimental groups in order of recruitment.

The study lasted 6 months, and included two phases: (1) during the first phase the experimental group underwent cognitive rehabilitation training using the Virtual Reality Rehabilitation System-Evo, whereas the control group was submitted to standard cognitive training; (2) in the second phase (after discharge), the experimental group was treated by means of virtual reality rehabilitation system Home Tablet (three sessions a week, each session lasting about 50 minutes), and the control group continued the traditional training, with the same amount of treatment. The patients underwent a neuropsychological evaluation before and at the end of the treatment. Linear mixed-effects analysis results showed that the scores of Montreal overall cognitive assessment, attentive matrices, Trail Making Test B, Phonemic Fluency, Semantic Fluency, Rey Auditory Verbal Learning Test I, Hamilton Rating Scale-Anxiety and Hamilton Rating Scale-Depression were affected by the type of the rehabilitative treatment.

Our data show the effectiveness of telerehabilitation for the treatment of cognitive disorders following stroke.

via Using telerehabilitation to improve cognitive function in po… : International Journal of Rehabilitation Research

, , ,

Leave a comment

[ARTICLE] Mechanisms Of Functional Adaptation Of Post Stroke Patients During Upper Limb Rehabilitation – Full Text

INTRODUCTION

Task oriented approach training of the patient with the arm weight unloading with feedback through the mirror.

Figure 1. Arm weight support training

Stroke is a leading cause of disability of the adult population worldwide. Successful recovery of upper limb motor function occurs only in 20% of cases [1]. Upper limb motor recovery is a most challenging goal, due to lack of patient’s motivation, training intensity and pathological synergy which is very difficult to correct using traditional methods. Poststroke upper limb paresis, spasticity and caused by them pathological synergies is the main problem on the way to daily living activities recovery. The problem of pathological synergies correction and transformation in rehabilitation practice are linked with the complexity of the required motor training approach [2]. A combination of cost-efficient, task-oriented, isolated and complex movement training with biofeedback is required to make synergy a compensatory mechanism for daily activities instead of pathological synkinesia.A promising but insufficiently studied method is virtual reality (VR), as well as its combination with other techniques like arm weight support training. Motor training in virtual reality (VR) with arm weight support creates the necessary facilitated environment for motor skills relearning [3].

MATERIALS AND METHODS.

45 patients (27 males and 18 females) with medium age 55 [45;65] years were enrolled in this study. All patients had one supratentorial lesion due to ischemic or hemorrhagic stroke (confirmed by MRI). Medium stroke age was 7 [4;12] months. All patients had moderate to severe upper limb paresis measured by Medical Research Council Scale for Muscle Strength and Fugl-Meyer assessment of physical performance (FMAS) upper extremity subscore 45 [35;55]. All patients received 2 weeks of a rehabilitation course, 5 days per week, 45 minutes daily.

Upper limb exoskeleton with weight support system and functional tasks in virtual environment.

Figure 2. Virtual reality with arm weight support training

Main group (n=25)  received 10 training sessions 45  minutes each on Armeo Spring system with separately adjusted weight support for shoulder and forearm and VR imitation of daily living activities such as reaching and grasping. The session includes 10 games like exercises and consistent increase of degrees of freedom from shoulder to the wrist. This condition allows teaching the patient voluntarily prevent pathologic synergy while performing a motor task.

The control group (n=20) received conventional therapy sessions with arm weight support (a system of pulleys), visual feedback (via mirror) and comparable set of tasks – reaching, grasping, manipulating objects.

The reaching test paradigm for motion analysis.

Figure 3. The reaching test.

For primary outcome assessment was used Fugl-Meyer assessment scale for upper limb, Action Research Arm Test (ARAT), Ashworth scale and Frenchay arm test. For motion analysis was used Russian Motion Capture System (Biosoft 3D). The paradigm for biomechanical analysis was presented with the functional reaching test. The reaching test was performed before and after the training course. Sitting at the table patient had to reach and grasp an empty glass located in front of him on the distance of extended healthy arm. For primary outcome were chosen reaching trajectory and arm kinematics, but patients were instructed to focus on the grasping movement to keep reaching movement more automatic. Normal reaching pattern was investigated on 10 healthy volunteers.

RESULTS.

FM and ARAT results on the main and control group before and after rehabilitation course.FM and ARAT results on the main and control group before and after rehabilitation course.
Figure 4. FM and ARAT scales before and after rehabilitation.
Table 1. Time of reaching test.
  Before rehabilitation After rehabilitation p-level
Moderate paresis, Ме [25%;75%] 1,5 [1,24; 1,71] 1,26 [0,9; 1,62] p=0,045
Severe paresis, Ме [25%;75%] 2,25 [1,65; 3,76] 2,66 [1,11; 3,05] p=0,043
Normal, Ме [25%;75%] 0,96 [0,87; 1,16]

In our study, the clinical assessment (FM and ARAT scales) showed that paretic hand recovery was found more in patients with moderate and severe paresis. Statistically significant improvements in the arm motor function (FMAS) were found in both groups. However, subsection analysis revealed that the patients of the main group compared to the control group had a more significant improvement in wrist movements. In ARAT was found that in patients with moderate paresis significant improvements occur in both main and control groups. In patients with severe paresis, improvements were observed only in the main group.

However, after motion analysis, a different stereotype of movement recovery was found in different groups of patients. In patients with severe paresis, an increase in the deviation of the movement pattern from the physiological movement was observed. At the same time, the normalization of the motor pattern was noted in patients with moderate paresis.

Table 2. Kinematics parameters in sever hand paresis.
Movement Before rehabilitation, Ме [25%;75%] After rehabilitation, Ме [25%;75%] p-level
Elbow extension 124 [116;126] 112 [109; 125] 0,01
Shoulder  flexion 36 [27; 41] 21 [20; 32] 0,02
Shoulder abduction 10 [10; 17] 19 [18; 22] 0,04
Velocity shoulder abduction 17 [13; 20] 48 [39; 65] 0,02
Velocity elbow extension 39 [26; 69] 29 [18,39] 0,02

The time of reaching test execution in patients with severe paresis after rehabilitation was longer than before and exceeded the normal time more than twice. Curiously,  these changes in patients with severe paresis were associated with an increase in functionality in the paretic arm (p>0,05).

The kinematic parameters such as elbow extension, shoulder abduction and angular velocity in shoulder and elbow joints after rehabilitation were worsened. After a rehabilitation course was founded decreasing of the angular velocity of the elbow joint extension, increasing of the angular velocity of the shoulder joint, decreasing of the flexion in the shoulder joint and angular speed of the elbow joint extension.

The analysis of trunk movements in severe paresis patients was shown that after rehabilitation course the trunk compensatory strategy was increased (trunk was mowed forward when patient reach the glass). These changes were associated with an increase in functionality in the paretic arm (p>0,05).

CONCLUSIONS.

Table 3. Body displacement in reaching test.
Shoulder displacement Before rehabilitation, Ме [25%;75%] After rehabilitation, Ме [25%;75%]
Healthy shoulder 23 [19,8; 57,44] 66 [49;81]
Paretic shoulder 169 [88; 178] 215 [162; 229]

If we summarized data of clinical and biomechanical parameters we see, that patients with severe paresis formed the new compensatory strategy of motion. Because of the significant changes in functional recovery are combined with worsened of biomechanical parameters.

It is believed that it is the resistance to pathological synergies and the forced training in physiological movement is the most effective method. However, correction of pathological synergies allows developing the most energy-efficient stereotype of movements for patients with regard to their individual capabilities. Combined VR and weight support training can be more effective to restore the impaired motor function after stroke than conventional weight support training. This approach contributes to the motor pattern reorganization through biomechanical and visual feedback, projected into the virtual space.

REFERENCES

[1] Beebe J.A., Lang C.E. Active range of motion predicts upper extremity function 3 months after stroke. Stroke. 2009 40 (5): 1772–1779.

[2] Cirstea M.C., Levin M.F. Compensatory strategies for reaching in stroke. Brain. 2000 123 (5): 940–953.

[3] Laver K.E., George S.,J.E. Thomas, M. Deutsch. Crotty Virtual reality for stroke rehabilitation. Cochrane Database Syst Rev.  2015 12 (2): 83.

via Mechanisms Of Functional Adaptation Of Post Stroke Patients During Upper Limb Rehabilitation.

, , , , , , , , , , , ,

Leave a comment

[Abstract] Autonomous Use of the Home Virtual Rehabilitation System: A Feasibility and Pilot Study

Objective: This article describes the findings of a study examining the ability of persons with strokes to use home virtual rehabilitation system (HoVRS), a home-based rehabilitation system, and the impact of motivational enhancement techniques on subjects’ motivation, adherence, and motor function improvements subsequent to a 3-month training program.

Materials and Methods: HoVRS integrates a Leap Motion controller, a passive arm support, and a suite of custom-designed hand rehabilitation simulations. For this study, we developed a library of three simulations, which include activities such as flexing and extending fingers to move a car, flying a plane with wrist movement, and controlling an avatar running in a maze using reaching movements. Two groups of subjects, the enhanced motivation (EM) group and the unenhanced control (UC) group, used the system for 12 weeks in their homes. The EM group trained using three simulations that provided 8–12 levels of difficulty and complexity. Graphics and scoring opportunities increased at each new level. The UC group performed the same simulations, but difficulty was increased utilizing an algorithm that increased difficulty incrementally, making adjustments imperceptible.

Results: Adherence to both the EM and UC protocols exceeded adherence to home exercise programs described in the stroke rehabilitation literature. Both groups demonstrated improvements in upper extremity function. Intrinsic motivation levels were better for the EM group and motivation levels were maintained for the 12-week protocol.

Conclusion: A 12-week home-based training program using HoVRS was feasible. Motivational enhancement may have a positive impact on motivation, adherence, and motor outcome.

 

via Autonomous Use of the Home Virtual Rehabilitation System: A Feasibility and Pilot Study | Games for Health Journal

, , , , , , , , , , , , , ,

Leave a comment

%d bloggers like this: