Gamification of Hand Rehabilitation Process Using Virtual Reality Tools: Using Leap Motion for Hand Rehabilitation

Alimanova, Madina; Borambayeva, Saulet; Kozhamzharova, Dinara; Kurmangaiyeva, Nurgul; Ospanova, Dinara; Tyulepberdinova, Gulnar; Gaziz, Gulnur; Kassenkhan, Aray

doi:10.1109/irc.2017.76

Cited by 65 publications

(32 citation statements)

References 17 publications

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“…The hardware, provided by the video game consoles emerged as a brilliant opportunity because it is designed to obtain the 3D position of game players in real-time. In [125], the authors present a VR tool for hand rehabilitation. The application in the form of a game has different options, tasks and exercises related to 3D grabbing, reaching, pointing, lifting, throwing and other activities for hand rehabilitation where the leap motion is the central concept of VR and physiotherapy.…”

Section: Special Needs Educationmentioning

confidence: 99%

Virtual Reality and Its Applications in Education: Survey

et al. 2019

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In the education process, students face problems with understanding due to the complexity, necessity of abstract thinking and concepts. More and more educational centres around the world have started to introduce powerful new technology-based tools that help meet the needs of the diverse student population. Over the last several years, virtual reality (VR) has moved from being the purview of gaming to professional development. It plays an important role in teaching process, providing an interesting and engaging way of acquiring information. What follows is an overview of the big trend, opportunities and concerns associated with VR in education. We present new opportunities in VR and put together the most interesting, recent virtual reality applications used in education in relation to several education areas such as general, engineering and health-related education. Additionally, this survey contributes by presenting methods for creating scenarios and different approaches for testing and validation. Lastly, we conclude and discuss future directions of VR and its potential to improve the learning experience.Information 2019, 10, 318 2 of 20 must be carried out under supervision; therefore, students cannot self-configure lab equipment, experience states of emergency or effects of misconfiguration which may lead to equipment damage. Moreover, there is no possibility to practice and catch up outside the laboratory schedule. Currently, the solutions are modern technologies such as online courses [8,9], blended learning [10-13], different computer-based platforms [14-18] and many others, which allow the students to repeat several times the same topic, make mistakes and learn from them. Numerous examples of hardware and software which have been successful in educational processes indicate that edtech industry can improve learning outcomes for the majority of students [19]. More and more educational centres around the world are starting to introduce powerful new technology tools that help them to meet the needs of diverse student populations. Traditional books are being replaced by digital instructional content (especially from open educational resources) [20]. Notebooks, tablets or cell phones with dedicated application have replaced classical copybooks [21]. Distance [22] and personalised learning [23] are used to tailor education to each student's academic strengths, weaknesses, preferences and goals.It is well known that the use of information and communication technologies have been found to improve student attitudes towards learning [24][25][26][27]. It is a rapidly growing field of research, continually developing and looking for new technological solutions. Over the last several years, Virtual Reality (VR), which provides an interactive computer-generated environment, has moved from being the purview of the gaming to the professional development such as military, psychology, medicine and teaching applications.In 1987, Jaron Lanier, together with Steve Bryson, formulated the first definition of VR, which they desc...

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Section: Special Needs Educationmentioning

confidence: 99%

Virtual Reality and Its Applications in Education: Survey

et al. 2019

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“…In recent years, the increasingly broad range of available technologies for physical activity monitoring enabled a face-paced advancement of these approaches. Application domains in the scope of digital rehabilitation include the usage of technologies ranging from: video analysis [15,16], wearable technologies [17], robotics [18,19], distributed sensing [20], and gamification [21,22]. This work focuses on physical rehabilitation.…”

Section: Digital Rehabilitationmentioning

confidence: 99%

Real-Time Compliant Stream Processing Agents for Physical Rehabilitation

Calvaresi

Calbimonte

2020

Sensors

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Digital rehabilitation is a novel concept that integrates state-of-the-art technologies for motion sensing and monitoring, with personalized patient-centric methodologies emerging from the field of physiotherapy. Thanks to the advances in wearable and portable sensing technologies, it is possible to provide patients with accurate monitoring devices, which simplifies the tracking of performance and effectiveness of physical exercises and treatments. Employing these approaches in everyday practice has enormous potential. Besides facilitating and improving the quality of care provided by physiotherapists, the usage of these technologies also promotes the personalization of treatments, thanks to data analytics and patient profiling (e.g., performance and behavior). However, achieving such goals implies tackling both technical and methodological challenges. In particular, (i) the capability of undertaking autonomous behaviors must comply with strict real-time constraints (e.g., scheduling, communication, and negotiation), (ii) plug-and-play sensors must seamlessly manage data and functional heterogeneity, and finally (iii) multi-device coordination must enable flexible and scalable sensor interactions. Beyond traditional top-down and best-effort solutions, unsuitable for safety-critical scenarios, we propose a novel approach for decentralized real-time compliant semantic agents. In particular, these agents can autonomously coordinate with each other, schedule sensing and data delivery tasks (complying with strict real-time constraints), while relying on ontology-based models to cope with data heterogeneity. Moreover, we present a model that represents sensors as autonomous agents able to schedule tasks and ensure interactions and negotiations compliant with strict timing constraints. Furthermore, to show the feasibility of the proposal, we present a practical study on upper and lower-limb digital rehabilitation scenarios, simulated on the MAXIM-GPRT environment for real-time compliance. Finally, we conduct an extensive evaluation of the implementation of the stream processing multi-agent architecture, which relies on existing RDF stream processing engines.

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“…An interaction tools [13] was designed for exploring volume dataset by interaction gestures vis Leap Motion to perform some tasks. Furthermore, the integration of gaming applications was explored into the medical field [8] such as a game for hand rehabilitation [14]. An interactive gesture controlled application [15] was presented and evaluated, which show the effectiveness and high satisfaction of the participants.…”

Section: ) Gesture Interactionsmentioning

confidence: 99%

Interactive Diffusion Tensor Imaging Fiber Data Visualization Via Leap Motion

Fang

Xiao

et al. 2020

IEEE Access

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Diffusion Tensor Imaging (DTI) reveals subtle abnormalities associated with stroke, multiple sclerosis, schizophrenia and dyslexia, which has a broad application prospect in the medical field. The densely sampled 3-D DTI fiber tracts in biological specimens have high geometric, spatial and anatomical complexity. To provide users with more immersive and convenient interactions in exploring DTI fibers, we design specific interactions based on the APIs of Leap Motion. Leap Motion is a somatosensory interaction device focusing on hand tracking. We design four different interaction modes for users to analyze the data in different interaction stages and scenarios, in order to better explore the DTI fibers which users are interested in by Leap Motion gestures. They are Normal Mode, Box Basic Interaction Mode, Box Logic Operation Mode, and Cluster Exploration Mode. Users can conduct tradition manipulations over the whole DTI fiber data in Normal Mode. Boxes are employed to filter out uninteresting tracts in Box Basic Interaction Mode, and expression-based queries are further designed to get logic set operations based on multiple boxes in Box Logic Operation Mode, e.g., the intersection, union and complement of boxes. Complex logic combination queries are allowed to perform to reduce visual clutter and help users explore DTI fibers more precisely. In Cluster Exploration Mode, DTI fibers can be classified by clustering them into spatially and anatomically related tracts and then different clusters can be explored individually by designed gestures. Compared with the explorations through traditional input devices, the evaluation tests show that the proposed approach is more intuitive and efficient in 3-D explorations and provides an immersive experience for users to explore the DTI fiber data. INDEX TERMS Data visualization, data analysis, graphical user interfaces, human computer interaction.

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Gamification of Hand Rehabilitation Process Using Virtual Reality Tools: Using Leap Motion for Hand Rehabilitation

Cited by 65 publications

References 17 publications

Virtual Reality and Its Applications in Education: Survey

Virtual Reality and Its Applications in Education: Survey

Real-Time Compliant Stream Processing Agents for Physical Rehabilitation

Interactive Diffusion Tensor Imaging Fiber Data Visualization Via Leap Motion

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