Trends in virtual reality technologies for the learning patient

NextMed convened the Medicine Meets Virtual Reality 22 (MMVR 22) conference in 2016. Since 1992, the conference has brought together a diverse group of researchers to share creative solutions for the evolving challenge of integrating virtual reality tools into medical education. Virtual reality (VR) and its enabling technologies utilize hardware and software to simulate environments and encounters where users can interact and learn. The MMVR 22 symposium proceedings contain projects that support a variety of learners: medical students, practitioners, soldiers, and patients. This report will contemplate the trends in virtual reality technologies for patients navigating their medical and healthcare learning. The learning patient seeks more than intervention; they seek prevention. From virtual humans and environments to motion sensors and haptic devices, patients are surrounded by increasingly rich and transformative data-driven tools. Applied data enables VR applications to simulate experience, predict health outcomes, and motivate new behavior. The MMVR 22 presents investigations into the usability of wearable devices, the efficacy of avatar inclusion, and the viability of multi-player gaming. With increasing need for individualized and scalable programming, only committed open source efforts will align instructional designers, technology integrators, trainers, and clinicians. Curriculum and InstructionCurriculum and Instructio

A cost-effective virtual environment for simulating and training powered wheelchairs manoeuvres

Control of a powered wheelchair is often not intuitive, making training of new users a challenging and sometimes hazardous task. Collisions, due to a lack of experience can result in injury for the user and other individuals. By conducting training activities in virtual reality (VR), we can potentially improve driving skills whilst avoiding the risks inherent to the real world. However, until recently VR technology has been expensive and limited the commercial feasibility of a general training solution. We describe Wheelchair-Rift, a cost effective prototype simulator that makes use of the Oculus Rift head mounted display and the Leap Motion hand tracking device. It has been assessed for face validity by a panel of experts from a local Posture and Mobility Service. Initial results augur well for our cost-effective training solutio

The Implementation and Validation of a Virtual Environment for Training Powered Wheelchair Manoeuvres

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.Navigating a powered wheelchair and avoiding collisions is often a daunting task for new wheelchair users. It takes time and practice to gain the coordination needed to become a competent driver and this can be even more of a challenge for someone with a disability. We present a cost-effective virtual reality (VR) application that takes advantage of consumer level VR hardware. The system can be easily deployed in an assessment centre or for home use, and does not depend on a specialized high-end virtual environment such as a Powerwall or CAVE. This paper reviews previous work that has used virtual environments technology for training tasks, particularly wheelchair simulation. We then describe the implementation of our own system and the first validation study carried out using thirty three able bodied volunteers. The study results indicate that at a significance level of 5% then there is an improvement in driving skills from the use of our VR system. We thus have the potential to develop the competency of a wheelchair user whilst avoiding the risks inherent to training in the real world. However, the occurrence of cybersickness is a particular problem in this application that will need to be addressed

Upper Body-Based Power Wheelchair Control Interface for Individuals with Tetraplegia

Many power wheelchair control interfaces are not sufficient for individuals with severely limited upper limb mobility. The majority of controllers that do not rely on coordinated arm and hand movements provide users a limited vocabulary of commands and often do not take advantage of the user's residual motion. We developed a body-machine interface (BMI) that leverages the flexibility and customizability of redundant control by using high dimensional changes in shoulder kinematics to generate proportional control commands for a power wheelchair. In this study, three individuals with cervical spinal cord injuries were able to control a power wheelchair safely and accurately using only small shoulder movements. With the BMI, participants were able to achieve their desired trajectories and, after five sessions driving, were able to achieve smoothness that was similar to the smoothness with their current joystick. All participants were twice as slow using the BMI however improved with practice. Importantly, users were able to generalize training controlling a computer to driving a power wheelchair, and employed similar strategies when controlling both devices. Overall, this work suggests that the BMI can be an effective wheelchair control interface for individuals with high-level spinal cord injuries who have limited arm and hand control

Virtual and Mixed Reality Support for Activities of Daily Living

Rehabilitation and training are extremely important process that help people who have suffered some form of trauma to regain their ability to live independently and successfully complete activities of daily living. VR and MR have been used in rehabilitation and training, with examples in a range of areas such as physical and cognitive rehabilitation, and medical training. However, previous research has mainly used non-immersive VR such as using video games on a computer monitor or television. Immersive VR Head-Mounted Displays were first developed in 1965 but the devices were usually large, bulky and expensive. In 2016, the release of low-cost VR HMDs allowed for wider adoption of VR technology. This thesis investigates the impact of these devices in supporting activities of daily living through three novel applications: training driving skills for a powered wheelchair in both VR and MR; and using VR to help with the cognitive rehabilitation of stroke patients. Results from the acceptability study for VR in cognitive rehabilitation showed that patients would be likely to accept VR as a method of rehabilitation. However, factors such as visual issues need to be taken into consideration. The validation study for the Wheelchair-VR project showed promising results in terms of user improvement after the VR training session but the majority of the users experienced symptoms of cybersickness. Wheelchair-MR didn’t show statistically significant results in terms of improvements but did show a mean average improvement compared to the control group. The effects of cybersickness were also greatly reduced compared to VR. We conclude that VR and MR can be used in conjunction with modern games engines to develop virtual environments that can be adapted to accelerate the rehabilitation and training of patients coping with different aspects of daily life

Master of Science

thesisThe objective of this research is to improve the ability of a human operator to drive an omnidirectional robot by using omnidirectional force-feedback. Omnidirectional vehicles offer improved mobility over conventional vehicles and can potentially benefit people requiring motorized transportation and industries where vehicles must operate in confined spaces. However, omnidirectional vehicles require more skill to control due to the additional degrees of freedom inherent in the vehicle’s design. We hypothesize that providing force-feedback to the driver through an omnidirectional joystick will allow the robot to assist the driver in navigating and avoiding collisions with obstacles in a manner that is natural to the operator. This research is the first attempt to use true omnidirectional 3-DOF (degree of freedom) force-feedback to provide navigational assistance for a human to drive an omnidirectional vehicle. While 2-DOF force-feedback has been used in a limited capacity for obstacle avoidance on omnidirectional vehicles, this is the first study to include a third rotational axis of force-feedback and use it to guide a driver along planar collision-avoiding trajectories with a natural coordination of orientation. Unique intellectual merits put forth by this research include use of a novel omnidirectional haptic device and force-feedback strategies to guide operators and experiments to quantify the ability of force-feedback to improve omnidirectional driving performance and driver experience in a real time scenario

Uma arquitetura de telerreabilitação baseada em realidade aumentada para apoiar o treinamento de usuários de cadeiras de rodas motorizadas

Many people worldwide have been experimenting a decrease in their mobility as a result of aging, accidents and degenerative diseases. In many cases, a Powered Wheelchair (PW) is an alternative help. Currently, in Brazil, patients can receive a PW from the Unified Health System, following prescription criteria. However, they do not have an appropriate previous training for driving the PW. Consequently, users might suffer accidents since a customized training protocol is not available. Nevertheless, due to financial and/or health limitations, many users are unable to attend a rehabilitation center. To overcome these limitations, we developed an Augmented Reality (AR) Telerehabilitation System Architecture based on the Power Mobility Road Test (PMRT), for supporting PW user’s training. In this system, the therapists can remotely customize and evaluate training tasks and the user can perform the training in safer conditions. Video stream and data transfer between each environment were made possible through UDP (User Datagram Protocol). To evaluate and present the system architecture potential, a preliminary test was conducted with 3 spinal cord injury participants. They performed 3 basic training protocols defined by a therapist. The following metrics were adopted for evaluation: number of control commands; elapsed time; number of collisions; biosignals and a questionary was used to evaluate system features by participants. Results demonstrate the specific needs of individuals using a PW, thanks to adopted (qualitative and emotional) metrics. Also, the results have shown the potential of the training system with customizable protocols to fulfill these needs. User’s evaluation demonstrates that the combination of AR techniques with PMRT adaptations, increases user’s well-being after training sessions. Furthermore, a training experience helps users to overcome their displacement problems, as well as for appointing challenges before large scale use. The proposed system architecture allows further studies on telerehabilitation of PW users.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorTese (Doutorado)Muitas pessoas em todo o mundo estão vivenciando uma diminuição de sua mobili- dade como resultado de envelhecimento, acidentes e doenças degenerativas. Em muitos casos, uma cadeira de rodas motorizada (CRM) é uma ajuda alternativa. Atualmente, no Brasil, os pacientes podem receber uma CRM do Sistema Único de Saúde, seguindo os critérios de prescrição. No entanto, eles não têm um treinamento prévio apropriado para dirigir a CRM. Conseqüentemente, os usuários podem sofrer acidentes, pois um protocolo de treinamento personalizado não está disponível. Além disto, devido a limi- tações financeiras e / ou de saúde, muitos usuários não podem comparecer a um centro de reabilitação. Para superar essas limitações, desenvolvemos uma arquitetura de sistema de telereabilitação com Realidade Aumentada (RA) baseado no PMRT (Power Mobility Road Test), para apoiar o treinamento de usuários de CRM. Nesse sistema, os terapeutas podem personalizar e avaliar remotamente as tarefas de treinamento e o usuário pode realizar o treinamento em condições mais seguras. O fluxo de vídeo e a transferência de dados entre cada ambiente foram possíveis através do UDP (User Datagram Protocol). Para avaliar e apresentar o potencial da arquitetura do sistema, foi realizado um teste preliminar de três participantes com lesão medular. Eles realizaram três protocolos básicos de treinamento definidos por um terapeuta. As seguintes métricas adotadas para avaliação foram: número de comandos de controle; tempo decorrido; número de colisões e biossinais. Além disso, um questionário foi usado para avaliar os recursos do sistema. Os resultados demonstram as necessidades específicas dos indivíduos que usam uma CRM, graças às métricas adotadas (qualitativas e emocionais). Além disso, os resultados mostraram o potencial do sistema de treinamento com protocolos personalizáveis para atender a essas necessidades. A avaliação do usuário demonstra que a combinação de técnicas de RA com adaptações PMRT aumenta o bem-estar do usuário após as sessões de treinamento. Além disso, esta experiência de treinamento ajuda os usuários a superar seus problemas de deslocamento, bem como a apontar desafios antes do uso em larga escala. A arquitetura de sistema proposta, permite estudos adicionais sobre a telerreabilitação de usuários de CRM