Outputs (2348)

Classifying gait alterations using an instrumented smart sock and deep learning (2022)
Journal Article
Lugoda, P., Hayes, S. C., Hughes-Riley, T., Turner, A., Martins, M. V., Cook, A., Raval, K., Oliveira, C., Breedon, P., & Dias, T. (2022). Classifying gait alterations using an instrumented smart sock and deep learning. IEEE Sensors Journal, 22(23), 23232-23242. https://doi.org/10.1109/jsen.2022.3216459

This article presents a noninvasive method of classifying gait patterns associated with various movement disorders and/or neurological conditions, utilizing unobtrusive, instrumented socks and a deep-learning network. Seamless instrumented socks were... Read More about Classifying gait alterations using an instrumented smart sock and deep learning.

The relationship between trust and attitudes towards the COVID-19 digital contact-tracing app in the UK (2022)
Journal Article
Dowthwaite, L., Wagner, H. G., Babbage, C. M., Fischer, J. E., Barnard, P., Nichele, E., Perez Vallejos, E., Clos, J., Portillo, V., & McAuley, D. (2022). The relationship between trust and attitudes towards the COVID-19 digital contact-tracing app in the UK. PLoS ONE, 17(10), Article e0276661. https://doi.org/10.1371/journal.pone.0276661

During the COVID-19 pandemic, digital contact-tracing has been employed in many countries to monitor and manage the spread of the disease. However, to be effective such a system must be adopted by a substantial proportion of the population; therefore... Read More about The relationship between trust and attitudes towards the COVID-19 digital contact-tracing app in the UK.

The future of manufacturing: Utopia or dystopia? (2022)
Journal Article
Marinescu, A., Argyle, E. M., Duvnjak, J., Wilson, M. L., Lawson, G., Sharples, S., Hubbard, E., & Justham, L. (2023). The future of manufacturing: Utopia or dystopia?. Human Factors and Ergonomics in Manufacturing and Service Industries, 33(2), 184-200. https://doi.org/10.1002/hfm.20976

Digital manufacturing technologies (DMTs) have the potential to transform industry productivity, but their introduction into the workplace is often a complex process, requiring not only technical expertise but also an awareness of ethical and societa... Read More about The future of manufacturing: Utopia or dystopia?.

Recent progress, challenges and outlook for multidisciplinary structural optimization of aircraft and aerial vehicles (2022)
Journal Article
Corrado, G., Ntourmas, G., Sferza, M., Traiforos, N., Arteiro, A., Brown, L., Chronopoulos, D., Daoud, F., Glock, F., Ninic, J., Ozcan, E., Reinoso, J., Schuhmacher, G., & Turner, T. (2022). Recent progress, challenges and outlook for multidisciplinary structural optimization of aircraft and aerial vehicles. Progress in Aerospace Sciences, 135, Article 100861. https://doi.org/10.1016/j.paerosci.2022.100861

Designing an airframe is a complex process as it requires knowledge from multiple disciplines such as aerodynamics, structural mechanics, manufacturing, flight dynamics, which individually lead to very different optimal designs. Furthermore, the grow... Read More about Recent progress, challenges and outlook for multidisciplinary structural optimization of aircraft and aerial vehicles.

Understanding Trust and Changes in Use After a Year With the NHS COVID-19 Contact Tracing App in the United Kingdom: Longitudinal Mixed Methods Study (2022)
Journal Article
Pepper, C., Reyes-Cruz, G., Pena, A. R., Dowthwaite, L., Babbage, C. M., Wagner, H., Nichele, E., & Fischer, J. E. (2022). Understanding Trust and Changes in Use After a Year With the NHS COVID-19 Contact Tracing App in the United Kingdom: Longitudinal Mixed Methods Study. Journal of Medical Internet Research, 24(10), Article e40558. https://doi.org/10.2196/40558

Background: Digital contact tracing (DCT) apps have been implemented as a response to the COVID-19 pandemic. Research has focused on understanding acceptance and adoption of these apps, but more work is needed to understand the factors that may contr... Read More about Understanding Trust and Changes in Use After a Year With the NHS COVID-19 Contact Tracing App in the United Kingdom: Longitudinal Mixed Methods Study.

Feasibility and Acceptability of an Internet of Things–Enabled Sedentary Behavior Intervention: Mixed Methods Study (Preprint) (2022)
Preprint / Working Paper
Huang, Y., Benford, S., Li, B., Price, D., & Blake, H. Feasibility and Acceptability of an Internet of Things–Enabled Sedentary Behavior Intervention: Mixed Methods Study (Preprint)

Background:
Encouraging office workers to break up prolonged sedentary behavior (SB) at work with regular micro-breaks can be beneficial yet challenging. Internet of Things (IoT) offers great promise for delivering more subtle and hence acceptable b... Read More about Feasibility and Acceptability of an Internet of Things–Enabled Sedentary Behavior Intervention: Mixed Methods Study (Preprint).

Ethics by design: Responsible research & innovation for AI in the food sector (2022)
Journal Article
Craigon, P. J., Sacks, J., Brewer, S., Frey, J., Gutierrez, A., Jacobs, N., Kanza, S., Manning, L., Munday, S., Wintour, A., & Pearson, S. (2023). Ethics by design: Responsible research & innovation for AI in the food sector. Journal of Responsible Technology, 13, Article 100051. https://doi.org/10.1016/j.jrt.2022.100051

Here we reflect on how a multidisciplinary working group explored the ethical complexities of the use of new technologies for data sharing in the food supply chain. We used a three-part process of varied design methods, which included collaborative i... Read More about Ethics by design: Responsible research & innovation for AI in the food sector.

Feature Importance Identification for Time Series Classifiers (2022)
Presentation / Conference Contribution
Meng, H., Wagner, C., & Triguero, I. (2022, October). Feature Importance Identification for Time Series Classifiers. Presented at 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Prague, Czech Republic

Time series classification is a challenging research area where machine learning techniques such as deep learning perform well, yet lack interpretability. Identifying the most important features for such classifiers provides a pathway to improving th... Read More about Feature Importance Identification for Time Series Classifiers.

Supporting Awareness of Visual Impairments and Accessibility Reflections through Video Demos and Design Cards (2022)
Presentation / Conference Contribution
Reyes-Cruz, G., Fischer, J., & Reeves, S. (2022, October). Supporting Awareness of Visual Impairments and Accessibility Reflections through Video Demos and Design Cards. Presented at Nordic Human-Computer Interaction Conference (NordiCHI ’22), Aarhus, Denmark

Disabled people's experiences and knowledge are oftentimes not central in design processes. Further, the burden of outreach and sensitising others to these experiences and knowledge is frequently not recognised. This paper offers a workshop approach... Read More about Supporting Awareness of Visual Impairments and Accessibility Reflections through Video Demos and Design Cards.

Legal Provocations for HCI in the Design and Development of Trustworthy Autonomous Systems (2022)
Presentation / Conference Contribution
Urquhart, L. D., McGarry, G., & Crabtree, A. (2022, October). Legal Provocations for HCI in the Design and Development of Trustworthy Autonomous Systems. Presented at NordiCHI '22: Nordic Human-Computer Interaction Conference, Aarhus, Denmark

We propose a series of legal provocations emerging from the proposed European Union Artificial Intelligence Act 2021 (AIA) and explore how they open up new possibilities for HCI in the design and development of trustworthy autonomous systems. The AIA... Read More about Legal Provocations for HCI in the Design and Development of Trustworthy Autonomous Systems.