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Democratizing Neurorehabilitation: How Accessible are Low-Cost Mobile-Gaming Technologies for Self-Rehabilitation of Arm Disability in Stroke?

ABSTRACT: Motor-training software on tablets or smartphones (Apps) offer a low-cost, widely-available solution to supplement arm physiotherapy after stroke. We assessed the proportions of hemiplegic stroke patients who, with their plegic hand, could meaningfully engage with mobile-gaming devices using a range of standard control-methods, as well as by using a novel wireless grip-controller, adapted for neurodisability. We screened all newly-diagnosed hemiplegic stroke patients presenting to a stroke centre over 6 months. Subjects were compared on their ability to control a tablet or smartphone cursor using: finger-swipe, tap, joystick, screen-tilt, and an adapted handgrip. Cursor control was graded as: no movement (0); less than full-range movement (1); full-range movement (2); directed movement (3). In total, we screened 345 patients, of which 87 satisfied recruitment criteria and completed testing. The commonest reason for exclusion was cognitive impairment. Using conventional controls, the proportion of patients able to direct cursor movement was 38-48%; and to move it full-range was 55-67% (controller comparison: p>0.1). By comparison, handgrip enabled directed control in 75%, and full-range movement in 93% (controller comparison: p<0.001). This difference between controllers was most apparent amongst severely-disabled subjects, with 0% achieving directed or full-range control with conventional controls, compared to 58% and 83% achieving these two levels of movement, respectively, with handgrip. In conclusion, hand, or arm, training Apps played on conventional mobile devices are likely to be accessible only to mildly-disabled stroke patients. Technological adaptations such as grip-control can enable more severely affected subjects to engage with self-training software.

SUBMITTER: Rinne P

PROVIDER: S-EPMC5051962 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundStroke is a frequent cause of adult disability that can lead to enduring impairments. However, given the life-long plasticity of the brain one could assume that recovery could be facilitated by the harnessing of mechanisms underlying neuronal reorganization. Currently it is not clear how this reorganization can be mobilized. Novel technology based neurorehabilitation techniques hold promise to address this issue. Here we describe a Virtual Reality (VR) based system, the Rehabilitation Gaming System (RGS) that is based on a number of hypotheses on the neuronal mechanisms underlying recovery, the structure of training and the role of individualization. We investigate the psychometrics of the RGS in stroke patients and healthy controls.MethodsWe describe the key components of the RGS and the psychometrics of one rehabilitation scenario called Spheroids. We performed trials with 21 acute/subacute stroke patients and 20 healthy controls to study the effect of the training parameters on task performance. This allowed us to develop a Personalized Training Module (PTM) for online adjustment of task difficulty. In addition, we studied task transfer between physical and virtual environments. Finally, we assessed the usability and acceptance of the RGS as a rehabilitation tool.ResultsWe show that the PTM implemented in RGS allows us to effectively adjust the difficulty and the parameters of the task to the user by capturing specific features of the movements of the arms. The results reported here also show a consistent transfer of movement kinematics between physical and virtual tasks. Moreover, our usability assessment shows that the RGS is highly accepted by stroke patients as a rehabilitation tool.ConclusionsWe introduce a novel VR based paradigm for neurorehabilitation, RGS, which combines specific rehabilitative principles with a psychometric evaluation to provide a personalized and automated training. Our results show that the RGS effectively adjusts to the individual features of the user, allowing for an unsupervised deployment of individualized rehabilitation protocols.

Project description:BackgroundBaseline physical activity in patients when they initiate cardiac rehabilitation is poorly understood. We used mobile health technology to understand baseline physical activity of patients initiating cardiac rehabilitation within a clinical trial to potentially inform personalized care.MethodsThe VALENTINE (Virtual Application-Supported Environment to Increase Exercise During Cardiac Rehabilitation Study) is a prospective, randomized-controlled, remotely administered trial designed to evaluate a mobile health intervention to supplement cardiac rehabilitation for low- and moderate-risk patients. All participants receive a smartwatch and usual care. Baseline physical activity was assessed remotely after enrollment and included (1) 6-minute walk distance, (2) daily step count, and (3) daily exercise minutes, both over 7 days and for compliant days, defined by >8 hours of watch wear time. Multivariable linear regression identified patient-level features associated with these 3 measures of baseline physical activity.ResultsFrom October 2020 to March 2022, 220 participants enrolled in the study. Participants are mostly White (184 [83.6%]); 67 (30.5%) are female and 84 (38.2%) are >65 years old. Most participants enrolled in cardiac rehabilitation after percutaneous coronary intervention (105 [47.7%]) or coronary artery bypass surgery (39 [17.7 %]). Clinical diagnoses include coronary artery disease (78.6%), heart failure (17.3%), and valve repair or replacement (26.4%). Baseline mean 6-minute walk distance was 489.6 (SD, 143.4) meters, daily step count was 6845 (SD, 3353), and exercise minutes was 37.5 (SD, 33.5). In a multivariable model, 6-minute walk distance was significantly associated with age and sex, but not cardiac rehabilitation indication. Sex but not age or cardiac rehabilitation indication was significantly associated with daily step count and exercise minutes.ConclusionsBaseline physical activity varies substantially in low- and moderate-risk patients enrolled in cardiac rehabilitation. Future studies are warranted to explore whether personalizing cardiac rehabilitation programs using mobile health technologies could optimize recovery.RegistrationURL: https://www.Clinicaltrialsgov; Unique identifier: NCT04587882.

Project description:BackgroundDue to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR.ObjectiveIn this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR.MethodsThe scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR.ResultsA total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies.ConclusionsMultiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.

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Democratizing Neurorehabilitation: How Accessible are Low-Cost Mobile-Gaming Technologies for Self-Rehabilitation of Arm Disability in Stroke?

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