This paper presents an exploration of how UK radiologists interact with VUI systems and peripherals when authoring diagnostic reports. We conducted a laboratory study with 10 practicing clinical radiologists to investigate the ways in which radiologists utilise speech-based technology to construct, edit and proof their work by having them report on real-world anonymised medical studies on camera. A sample of the participants also participated in interviews in which their data was collaboratively analysed and examined to offer deeper insight into the realism and generalisability of our findings and conclusions. We conclude that better training should be given to radiologists on how VUI systems work, and further investigation should be carried out on the best ways to interact with Speech To Text systems in safety critical environments.

What do pedestrian crossings, ATMs, elevators and ticket machines have in common? These are just a few of the ubiquitous yet essential elements of public-space infrastructure that rely on physical buttons or touchscreens; common interactions that, until recently, were considered perfectly safe to perform. This work investigates how we might integrate touchless technologies into public-space infrastructure in order to minimise physical interaction with shared devices in light of the ongoing COVID-19 pandemic. Drawing on an ethnographic exploration into how public utilities are being used, adapted or avoided, we developed and evaluated a suite of technology probes that can be either retrofitted into, or replace, these services. In-situ community deployments of our probes demonstrate strong uptake and provide insight into how hands-free technologies can be adapted and utilised for the public domain; and, in turn, used to inform the future of walk-up-and use public technologies.

Many of us daily encounter shadow and reflected light patterns alongside macro-level changes in ambient light levels. These are caused by elements—opaque objects, glass, mirrors, even clouds—in our environment interfacing with sunlight or artificial indoor lighting. Inspired by these phenomena, we explored ways of creating digitally-supported displays that use light, shade and reflection for output and harness the energy they need to operate from the sun or indoor ambient light. Through a set of design workshops we developed exemplar devices: SolarPix, ShadMo and GlowBoard. We detail their function and implementation, as well as evidencing their technical viability. The designs were informed by material understandings from the Global North and Global South and demonstrated in a cross-cultural workshop run in parallel in India and South Africa where community co-designers reflected on their uses and value given lived experience of their communication practices and unreliable energy networks.

The world is faced with a growing number of people who live with chronic medical conditions. There have been numerous digital interventions into personal management of these diseases in recent years, yet gaps remain in the HCI literature. In particular, we lack a systematic understanding of user requirements in tools that support independent management while away from external influences. This paper presents a first investigation into low-intervention support for self-management. A mobile application enabled individuals to capture contextual information related to their health in the form of photographs. Through a month-long user study, we identify four management trends amongst our participants and describe their influence on mobile application adoption.

People who suffer from Diabetes are required to make frequent decisions on their personal treatment based on results from self-care devices. Yet these results form only a part of the decision-making process and surrounding contextual information is a highly important aspect. Those who suffer from diabetes have described the daily challenges of dealing with unexpected results and a feeling of 'failure' at managing the disease. This paper describes ongoing research which focuses on using technology to assist in the capture of the contextual information to both aid the understanding of results and to potentially reduce the emotional impact of perceived 'bad' results.