Designing, developing and deploying assistive technologies at a scale and cost which makes them accessible to people is challenging. Traditional models of manufacturing would appear to be insufficient at helping the world's 1 billion disabled people in accessing the technologies they require. In addition, many who receive assistive technologies simply abandon them as they do not meet their needs. In this study the authors explore the changing world of design for disability. A landscape which includes the rise of the maker movement, the role of ubiquitous sensing and the changing role of the 'user' to one of designer and maker. The authors argue they are on the cusp of a revolution in healthcare provision, where the population will soon have the ability to manage their own care with systems in place for diagnosis, monitoring, individualised prescription and action/reaction. This will change the role of the clinician from that of diagnostician, gatekeeper and resource manager/deliverer to that of consultant informatics manager and overseer; perhaps only intervening to promote healthy behaviour, prevent crisis and react at flash moments.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5168724 | PMC |
| http://dx.doi.org/10.1049/htl.2016.0087 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Prevalence of Popular Smoking Cessation Aids in England and Associations With Quit Success.
JAMA Netw Open
January 2025
Department of Behavioural Science and Health, University College London, London, United Kingdom.
Importance: A wide range of medications, noncombustible nicotine products, behavioral support, and alternative treatments are available in England to help people stop smoking. Understanding their effectiveness outside of clinical trial settings can support informed decision-making.
Objectives: To provide up-to-date estimates of the prevalence of different smoking cessation aids and associations with quit success and to explore moderation by socioeconomic position.
Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification.
PLoS One
January 2025
School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, Tamil Nadu, India.
In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges due to their complexity, dynamic nature, and low signal-to-noise ratio (SNR). Traditional EEG pattern recognition algorithms typically involve two key steps: feature extraction and feature classification, both crucial for accurate operation.
View Article and Find Full Text PDFPerspectives and needs of assistive technology advisors and suppliers in Queensland, Australia.
Disabil Rehabil Assist Technol
January 2025
Faculty of Health, Southern Cross University, Queensland, Australia.
Purpose: An assistive technology ecosystem requires co-ordinated collaboration between policy, products, provision processes, and personnel. A needs assessment was conducted of the assistive technology sector in Queensland to examine these components from the perspective of all key stakeholders. This paper reports the findings of the expressed needs of the assistive technology sector as experienced by the AT advisors and suppliers.
View Article and Find Full Text PDFCardiometabolic Health Intervention Using Music and Exercise (CHIME) Delivered via Telehealth to Wheelchair Users: Protocol for a Randomized Controlled Trial.
JMIR Res Protoc
January 2025
Department of Physical Medicine and Rehabilitation, University of Alabama at Birmingham, Birmingham, AL, United States.
Background: Wheelchair users live predominantly sedentary lifestyles and have a substantially higher risk for cardiometabolic disease and mortality compared to people without disabilities. Exercise training has been found to be effective in improving cardiometabolic health (CMH) outcomes among people without disabilities, but research on wheelchair users is limited and of poor quality.
Objective: The primary aim of this study is to examine the immediate and sustained effects of a 24-week, telehealth, movement-to-music cardiovascular (M2M-C) exercise program on core indicators of CMH among adult wheelchair users compared to an active control group.
Enhancing the Travel Experience for People with Visual Impairments through Multimodal Interaction: NaviGPT, A Real-Time AI-Driven Mobile Navigation System.
GROUP ACM SIGCHI Int Conf Support Group Work
January 2025
College of Information Sciences and Technology, The Pennsylvania State University, University Park, Pennsylvania, USA.
Assistive technologies for people with visual impairments (PVI) have made significant advancements, particularly with the integration of artificial intelligence (AI) and real-time sensor technologies. However, current solutions often require PVI to switch between multiple apps and tools for tasks like image recognition, navigation, and obstacle detection, which can hinder a seamless and efficient user experience. In this paper, we present NaviGPT, a high-fidelity prototype that integrates LiDAR-based obstacle detection, vibration feedback, and large language model (LLM) responses to provide a comprehensive and real-time navigation aid for PVI.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!