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A woman wearing a mask, testing her hearing using an app and headphones

Type

Editorial

Themes

Assistive & Accessible Technology

Research Group

Social Justice
Developing inclusive and resilient systems: COVID-19 and assistive technology

Emma M. Smith, Malcolm MacLachlan, Ikenna D. Ebuenyi, Catherine Holloway & Victoria Austin

While the inadequacies of our existing assistive technology systems, policies, and services have been highlighted by the acute and rapidly changing nature of the COVID-19 pandemic, these failures are also present and important during non-crisis times. Each of these actions, taken together, will not only address needs for more robust and resilient systems for future crises, but also the day-to-day needs of all assistive technology users. We have a responsibility as a global community, and within our respective countries, to address these inadequacies now to ensure an inclusive future.

Disability & Society; 2020

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Abstract

Developing inclusive and resilient systems: COVID-19 and assistive technology

Assistive technology is a critical component of maintaining health, wellbeing, and the realization of rights for persons with disabilities. Assistive technologies, and their associated services, are also paramount to ensuring individuals with functional limitations have access to important health and social service information, particularly during a pandemic where they may be at higher risk than the general population. Social isolation and physical distancing have further marginalized many within this population. We have an opportunity to learn from the COVID-19response to develop more inclusive and resilient systems that will serve people with disabilities more effectively in the future. In this Current Issues piece, we present a starting point for discussion, based on our experiences working to promote access to assistive technologies through inclusive and sustainable systems and policies.

Cite

Developing inclusive and resilient systems: COVID-19 and assistive technology

Emma M. Smith, Malcolm MacLachlan, Ikenna D. Ebuenyi, Catherine Holloway & Victoria Austin (2021) Developing inclusive and resilient systems: COVID-19 and assistive technology, Disability & Society, 36:1, 151-154, DOI: 10.1080/09687599.2020.1829558

Developing inclusive and resilient systems: COVID-19 and assistive technology

A man is photographed trying out a new Digital Innovation, he is wearing a VR headset

Type

Editorial

Themes

Assistive & Accessible Technology
Culture and Participation

Research Group

Social Justice
Critical Junctures in Assistive Technology and Disability Inclusion

It is clear from the events of the last 18 months that while technology has a huge potential for transforming the way we live and work, the entire ecosystem—from manufacturing to the supply chain—is vulnerable to the vagaries of that ecosystem, as well as having the potential to exacerbate new and existing inequalities [1]. Nowhere has this been more apparent than in the lives of people with disabilities, who make up around 15% of the world’s population and already face barriers to accessing education, employment, healthcare and other services [2]. Some of these barriers are a result of unequal access and opportunities. However, there is a growing movement to better understand how assistive technology systems and services can be designed to enable more robust and equitable access for all. As part of this growing movement, the Paralympic Games in Tokyo this autumn saw the launch of a new global campaign to transform the lives of the world’s 1.2 bn persons with disabilities: the ‘WeThe15’ campaign reached more than 4.5 billion people through its marketing and stands ready to be the biggest of its kind in history. Next year, the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF), AT scale and GDI Hub will publish the first World Report on Access to Assistive Technology, which will include research from the £20 million, UK Aid funded, GDI Hub-led, programme, AT2030. Ahead of that, in this Special Issue, we focus on how some events and situations—as diverse as the coronavirus pandemic and the Paralympics—can act as ‘critical junctures’ that can enable a rethink of the status quo to facilitate and promote change.

Sustainability; 2021

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Cite

Critical Junctures in Assistive Technology and Disability Inclusion

Kett, M.; Holloway, C.; Austin, V. Critical Junctures in Assistive Technology and Disability Inclusion. Sustainability 2021, 13, 12744. https://doi.org/10.3390/su1322...

Critical Junctures in Assistive Technology and Disability Inclusion

Steps leading up around a corner with handrail and colourful wall mural

Type

Journal Paper

Themes

Assistive & Accessible Technology

Research Group

Disability Interactions
Physiological Computing
STEP-UP: Enabling Low-Cost IMU Sensors to Predict the Type of Dementia During Everyday Stair Climbing

Catherine Holloway, William Bhot, Keir X. X. Yong, Ian McCarthy, Tatsuto Suzuki, Amelia Carton, Biao Yang, Robin Serougne, Derrick Boampong, Nick Tyler, Sebastian J. Crutch, Nadia Berthouze and Youngjun Cho

Posterior Cortical Atrophy is a rare but significant form of dementia which affects people's visual ability before their memory. This is often misdiagnosed as an eyesight rather than brain sight problem. This paper aims to address the frequent, initial misdiagnosis of this disease as a vision problem through the use of an intelligent, cost-effective, wearable system, alongside diagnosis of the more typical Alzheimer's Disease.

Frontiers in Computer Science

Abstract

STEP-UP: Enabling Low-Cost IMU Sensors to Predict the Type of Dementia During Everyday Stair Climbing

Posterior Cortical Atrophy is a rare but significant form of dementia which affects people's visual ability before their memory. This is often misdiagnosed as an eyesight rather than brain sight problem. This paper aims to address the frequent, initial misdiagnosis of this disease as a vision problem through the use of an intelligent, cost-effective, wearable system, alongside diagnosis of the more typical Alzheimer's Disease. We propose low-level features constructed from the IMU data gathered from 35 participants, while they performed a stair climbing and descending task in a real-world simulated environment. We demonstrate that with these features the machine learning models predict dementia with 87.02% accuracy. Furthermore, we investigate how system parameters, such as number of sensors, affect the prediction accuracy. This lays the groundwork for a simple clinical test to enable detection of dementia which can be carried out in the wild.

STEP-UP: Enabling Low-Cost IMU Sensors to Predict the Type of Dementia During Everyday Stair Climbing