2,084 research outputs found

    How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

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    Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

    Wayfinding and Navigation for People with Disabilities Using Social Navigation Networks

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    To achieve safe and independent mobility, people usually depend on published information, prior experience, the knowledge of others, and/or technology to navigate unfamiliar outdoor and indoor environments. Today, due to advances in various technologies, wayfinding and navigation systems and services are commonplace and are accessible on desktop, laptop, and mobile devices. However, despite their popularity and widespread use, current wayfinding and navigation solutions often fail to address the needs of people with disabilities (PWDs). We argue that these shortcomings are primarily due to the ubiquity of the compute-centric approach adopted in these systems and services, where they do not benefit from the experience-centric approach. We propose that following a hybrid approach of combining experience-centric and compute-centric methods will overcome the shortcomings of current wayfinding and navigation solutions for PWDs

    Challenges Faced by Persons with Disabilities Using Self-Service Technologies

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    Foreseeable game changing solutions to SSTs will allow for better universal access by better implementing features that are easy and intuitive to use from the inception. Additional robotic advancements will allow for better and easier delivery of goods for consumers. Improvements to artificial intelligence will allow for better communication through natural language and alternative forms of communication. Furthermore, artificial intelligence will aid consumers at SSTs by remembering the consumers preferences and needs. With all foreseeable game changing solutions people with disabilities will be consulted when new and improved SSTs are being developed allowing for the SST to maximize its potential

    Wayfinding and Navigation for People with Disabilities Using Social Navigation Networks

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    Development of a Modular Real-time Shared-control System for a Smart Wheelchair

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    In this paper, we propose a modular navigation system that can be mounted on a regular powered wheelchair to assist disabled children and the elderly with autonomous mobility and shared-control features. The lack of independent mobility drastically affects an individual's mental and physical health making them feel less self-reliant, especially children with Cerebral Palsy and limited cognitive skills. To address this problem, we propose a comparatively inexpensive and modular system that uses a stereo camera to perform tasks such as path planning, obstacle avoidance, and collision detection in environments with narrow corridors. We avoid any major changes to the hardware of the wheelchair for an easy installation by replacing wheel encoders with a stereo camera for visual odometry. An open source software package, the Real-Time Appearance Based Mapping package, running on top of the Robot Operating System (ROS) allows us to perform visual SLAM that allows mapping and localizing itself in the environment. The path planning is performed by the move base package provided by ROS, which quickly and efficiently computes the path trajectory for the wheelchair. In this work, we present the design and development of the system along with its significant functionalities. Further, we report experimental results from a Gazebo simulation and real-world scenarios to prove the effectiveness of our proposed system with a compact form factor and a single stereo camera

    On human-in-the-loop CPS in healthcare: a cloud-enabled mobility assistance service

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    Despite recent advancements on cloud-enabled and human-in-the-loop cyber-physical systems, there is still a lack of understanding of how infrastructure-related quality of service (QoS) issues affect user-perceived quality of experience (QoE). This work presents a pilot experiment over a cloud-enabled mobility assistive device providing a guidance service and investigates the relationship between QoS and QoE in such a system. In our pilot experiment, we employed the CloudWalker, a system linking smart walkers and cloud platforms, to physically interact with users. Different QoS conditions were emulated to represent an architecture in which control algorithms are performed remotely. Results point out that users report satisfactory interaction with the system even under unfavorable QoS conditions. We also found statistically significant data linking QoE degradation to poor QoS conditions. We finalize discussing the interplay between QoS requirements, the human-in-the-loop effect, and the perceived QoE in healthcare applications

    Safe and Efficient E-wayfinding (SeeWay) Assistive Navigation for the Visually Impaired

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    69A3551747117Despite its challenges, independent travel for blind and visually impaired (BVI) individuals is an essential component of quality of life, enabling travel to work and recreational activities. Autonomous vehicle technologies have the potential of meeting these challenges. However, efficiently and safely guiding BVI travelers between indoor environments and vehicles outdoors remains a key obstacle. In the future transportation system, assistive navigation technologies, connecting BVI travelers and vehicles, will be of extraordinary importance for BVI individuals in the context of social justice and health care/public health. Conventional research is mainly based on robotic navigation approaches through localization, mapping, and path-planning frameworks. They require heavy manual annotation of semantic information in maps and its alignment with sensor mapping. Inspired by the fact that we human beings naturally rely on language instruction inquiry and visual scene understanding to navigate in an unfamiliar environment, this study proposes a novel vision-language model-based approach for BVI navigation. It does not need heavy-labeled indoor maps and provides a Safe and Efficient E-Wayfinding (SeeWay) assistive solution for BVI individuals. The system consists of a scene-graph map construction module, a navigation path generation module for global path inference by vision-language navigation (VLN), and a navigation with obstacle avoidance module for real-time local navigation. The SeeWay system was deployed on portable iPhone devices with cloud computing assistance for the VLN model inference. The field tests show the effectiveness of the VLN global path finding and local path re-planning. Experiments and quantitative results reveal that heuristic-style instruction outperforms direction/detailed-style instructions for VLN success rate (SR), and the SR decreases as the navigation length increases
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