Abstract:

Shape-changing interfaces physically mutate their visual display surface to better represent on-screen content, provide an additional information channel, and facilitate tangible interaction with digital content. The HCI community has recently shown increasing interest in this area, with their physical dynamicity fundamentally changing how we think about displays. This talk will describe our current work supporting the design and prototyping of shape-changing displays: understanding shape-changing application areas through public engagement brainstorming, characterising fundamental touch input actions, creating tools to support design, and demonstrating example implementations. It will end with a look at future challenges and directions for research.

Bio:

Jason is a lecturer in the School of Computing and Communications at Lancaster University. His primary research area is Human-Computer Interaction, with a particular interest in bridging the physical-digital divide using novel physical interaction devices and techniques. He was previously a post-doctoral researcher in the Bristol Interaction and Graphics (BIG) group at the University of Bristol. Before that he was a Ph.D. student in the HCI and Multimedia Lab at the University of Canterbury, New Zealand. More information can be found at http://www.scc.lancs.ac.uk/~jason/

This seminar is part of our ongoing series from researchers in HCI. See here for our current schedule.

Abstract:
In the UK, more than 70% of mobile users now own a smartphone. These increasingly powerful, sensor-rich, and personal devices present an immense opportunity to monitor health-related behaviours and deliver digital behaviour-change interventions at unprecedented scale.

However, designing and building systems to measure and intervene on health behaviours presents a number of challenges. These range from balancing between energy efficiency and data granularity, translating between behavioural theory and design, making long psychological assessments usable for end users, and making sense of the sensor and survey data these apps collect in a multidisciplinary setting.

Approximately 18 months ago, we launched Emotion Sense, a mood-tracking app for Android where we tried to address some of these challenges. To date, the app has been downloaded over 35,000 times and has an active user base of about 2,000 people: in this talk, I will describe how we designed, trialled, and launched Emotion Sense, and the insights we are obtaining about diurnal patterns of activity and happiness that we are finding by mining the 100 million+ accelerometer samples the app has collected to date. I’ll close with future directions of this technology — including a novel smoking cessation intervention (Q Sense), and a generic platform (Easy M) that we have developed to allow researchers to conduct their own studies.

http://emotionsense.org/
http://www.qsense.phpc.cam.ac.uk/
http://www.cl.cam.ac.uk/~nkl25/easym/

Bio:
Neal is a Senior Research Associate in Cambridge University’s Computer Laboratory. His research to date falls somewhere in the intersection of data mining, mobile systems, ubiquitous/pervasive systems, and personalisation/ recommender systems, applied to a variety of contexts where we measure human behaviour by their digital footprints. He has a PhD in Computer Science from University College London. More info/contact http://www.cl.cam.ac.uk/~nkl25/

This seminar is part of our ongoing series from researchers in HCI. See here for our current schedule.

Abstract:
The process of learning to write is both cognitive and motoric. Forming symbols into words and committing them to a surface is a process laden with complexity; creating the meaning that will be represented by these words is even more complex.
Digital technologies provide opportunities and insights for the study of writing processes. With keyboard capture and pen stroke capture important information can be gathered to make writing systems more child suited and to provide useful assistance to beginner writers. Data captured during the electronic transcription of writing can also provide insights into how writing emerges as a form.
This talk will present child computer interaction against the context of children writing using electronic means. The marriage of the text input space, the digital ink space and the child will be explored using examples from recent research.
Bio:
Prof. Janet C Read (BSc, PGCE, PhD) is an international expert in Child Computer Interaction having supervised 7 PhD students to completion, examined 14 PhD students in six different European countries and currently supervising 8 PhD students studying a range of topics including the use of colour in teenage bedrooms, the design of interactive systems for dogs, the use of scaffolding in serious games, the use of text input to detect fraudulent password use, collaborative gaming for children, evaluation of systems for children and the forensic detection process. Her personal current research is in three main areas – she has recently published several papers on the ethics of engaging with children in participatory research activities offering a model for working with children which ensures they are given full information, and also a set of techniques that can be used to ensure that children’s contributions to interaction design are treated with respect. A second strand of interest is in the study of fun and the study of means to measure it. The Fun Toolkit, which is a set of tools to measure the experience of children when using interactive technology, is her most cited work and this is work that has developed over time but is still being examined. The uses of digital ink with children, and the whole area of text input for children, both with standard keyboards and with `handwriting recognition completes her current research portfolio. Professor Read has acted as PI on several projects (see below) and is the Editor in Chief of the International Journal of Child Computer Interaction.
This seminar is part of our ongoing series from researchers in HCI. See here for our current schedule.

Abstract:
This talk outlines David Harris-Birtill’s previous research (at the Institute of Cancer Research and Imperial College London) focusing on applications in detecting and treating cancer. The talk will discuss photoacoustic imaging in the clinic, photothermal therapy with gold nanorods, and the advantages of imaging in a variety of settings and in it’s many forms from a nano to a macro scale to help the fight against cancer. This talk will also touch on the importance of displaying the right type of information to the right type of user and why data analysis skills are so important in efficient scientific research.
For any questions please email David on dcchb@st-andrews.ac.uk.

Bio:
Dr David Harris-Birtill is a Research Fellow in the School of Computer Science at the University of St Andrews. His current research is in human computer interaction and information visualisation, and is particularly interested in data analysis, sensors and automising research.

David’s work has been published in journals including Astronomy and Astrophysics and the Journal of Biomedical Optics, and has presented his research across the globe at conferences including San Francisco (SPIE Photonics WEST) and Hong Kong (Acoustics 2012). He has created open source image analysis programs which have been downloaded by over 100 researchers all over the globe, has run a course on “Introduction to Matlab for busy researchers and clinicians” and supervised research by Masters and PhD students.

This seminar is part of our ongoing series from researchers in HCI. See here for our current schedule.

Title: AwToolkit: Attention-Aware User Interface Widgets
Authors: Juan-Enrique Garrido, Victor M. R. Penichet, Maria-Dolores Lozano, Aaron Quigley, Per Ola Kristensson.

Abstract: Increasing screen real-estate allows for the development of applications where a single user can manage a large amount of data and related tasks through a distributed user inter- face. However, such users can easily become overloaded and become unaware of display changes as they alternate their attention towards different displays. We propose Aw- Toolkit, a novel widget set for developers that supports users in maintaining awareness in multi-display systems. The Aw- Toolkit widgets automatically determine which display a user is looking at and provide users with notifications with different levels of subtlety to make the user aware of any unattended display changes. The toolkit uses four notification levels (unnoticeable, subtle, intrusive and disruptive), ranging from an almost imperceptible visual change to a clear and visually salient change. We describe AwToolkit’s six widgets, which have been designed for C# developers, and the design of a user study with an application oriented towards healthcare environments. The evaluation results re- veal a marked increase in user awareness in comparison to the same application implemented without AwToolkit.

TItle: An Evaluation of Dasher with a High-Performance Language Model as a Gaze Communication Method
Authors: Daniel Rough, Keith Vertanen, Per Ola Kristensson

Abstract: Dasher is a promising fast assistive gaze communication method. However, previous evaluations of Dasher have been inconclusive. Either the studies have been too short, involved too few participants, suffered from sampling bias, lacked a control condition, used an inappropriate language model, or a combination of the above. To rectify this, we report results from two new evaluations of Dasher carried out using a Tobii P10 assistive eye-tracker machine. We also present a method of modifying Dasher so that it can use a state-of-the-art long-span statistical language model. Our experimental results show that compared to a baseline eye-typing method, Dasher resulted in significantly faster entry rates (12.6 wpm versus 6.0 wpm in Experiment 1, and 14.2 wpm versus 7.0 wpm in Experiment 2). These faster entry rates were possible while maintaining error rates comparable to the baseline eye-typing method. Participants’ perceived physical demand, mental demand, effort and frustration were all significantly lower for Dasher. Finally, participants significantly rated Dasher as being more likeable, requiring less concentration and being more fun.