Active progress bars : facilitating the switch to temporary activities

International audienceIn this paper, we seek to find a better way of effective task management when a progress bar interrupts user's primary activity. We propose to augment progress bars with user controlled functionalities facilitating the switch to temporary activities. We detail a taxonomy of waiting period contexts and possible temporary tasks, then report on 5 participatory design, and a follow-up survey of 96 respondents. Finally we describe an early prototype of active progress bars, and report on initial use

Active progress bars : aiding the switch to temporary activities

International audienceCan we design an interface to help people make use of the idle time spent looking at progress bars? We propose to augment progress bars with user-controlled functionalities facilitating the switch to temporary activities. We propose a taxonomy of waiting period contexts and possible temporary tasks, then report on participatory design sessions, and a follow-up survey. Finally we describe an early prototype of active progress bar and report a small controlled experiment used to identify the impact of the tool on primary task satisfaction. The findings suggest that Active Progress Bars lead to significantly higher satisfaction when compared to a control condition

Punch-Sketching E-textiles:Exploring Punch Needle as a Technique for Sustainable, Accessible, and Iterative Physical Prototyping with E-textiles

Tangible toolkits enable individuals to explore concepts through combining components together and taking them apart. The strength and limitation of many e-textile toolkits is that threads hold them in place, and once put together they need destructive methods to take them apart. In this paper, we propose Punch-Sketching e-textiles, a drawing technique that uses a punch needle to iteratively prototype soft circuits. The benefits of this approach is sustainability and reusability where users can easily pull out circuits without damaging the materials or creating waste, while also testing out concepts using the actual threads that will be used in the final prototype. To validate our technique, we ran three studies comparing sewing and punching e-textiles through: 1) Understanding the process with two fiber artists; 2) Exploring the potential with four beginner users; and 3) Utilizing our methods further with 10 occupational therapists. Insights from these three studies include when and how to use each method, toolkit recommendations, considerations for iterative physical prototyping, sustainability, and accessibility

Co-Designing Accessible Computer and Smartphone Input Using Physical Computing

Significant obstacles persist in meeting the accessibility needs of computer and smartphone users with mild-to-moderate upper limb motor impairments as they use their devices at work and home. Multimodal input can help, but has not been widely adopted. We build on existing literature with a discovery survey and semistructured follow-up interviews in which we identify common themes related to the limitations of today’s solutions and the ad hoc workarounds which are adopted. We ran a series of co-design workshop sessions to understand the potential of modern “physical computing” electronic device prototyping technologies to provide new and effective input options for our target user base. We present the resulting prototype solutions and describe the technology choices made. Finally, we discuss how the co-design process, in conjunction with access to suitable physical prototyping technologies, can be a powerful approach for designing accessibility-focused input systems

Towards adaptive user interfaces using real time fNIRS

Enhancing user experience is a constant goal for human computer interaction (HCI) researchers, and the methods to achieve this goal are widespread, from changing the properties of the interface to adapting the task to the user’s ability level. By sensing user’s cognitive states, such as interest, workload, frustration, flow, we can adapt the interface immediately to keep them working optimally. This new train of thought in the brain computer interfaces community considers brain activity as an additional source of information, to augment and adapt the interface in conjunction with standard devices, instead of controlling it directly with the brain. To obtain measures of brain activity, I adopt the relatively less-explored brain sensing technique called functional near-infrared spectroscopy (fNIRS), a safe, non-invasive measurement of changes in blood oxygenation. This dissertation presents a body of technologies and tools that enable the use of real time measures of cognitive load for adaptive interfaces, to support the thesis that fNIRS is an input technology usable in conventional HCI contexts, especially when applied to the general, healthy public as an additional input. First, I discuss the practicality and applicability of the technology in realistic, desktop environments. Our work shows that fNIRS signals are robust enough to remain unaffected by typing and clicking but that some facial and head movements interfere with the measurements. Then, I investigate the use of fNIRS to obtain meaningful data related to mental workload. My studies progress from very controlled experiments that help us identify centers of brain activity, to experiments using simple user interfaces, showing how this technique may be applied to more realistic, complex interfaces. Our first study distinguishes levels of workload and interaction styles, and our second differentiates levels of game difficulty. Statistical analysis and machine learning classification results show that we discriminate well between subjects performing a mentally demanding task or resting, and distinguish between two levels with some success. Finally, I present a real time analysis and classification system that can communicate user cognitive load information to an application. I categorize adaption of interfaces with brain as an input, and propose a series of adaptations possible using our system

Adaptive brain-computer interface

Passive brain-computer interfaces are designed to use brain activity as an additional input, allowing the adaptation of the interface in real time according to the user's mental state. While most current brain computer interface research (BCI) is designed for direct use with disabled users, I focus my research on passive BCIs for healthy users. The goal of my dissertation is to employ functional near-infrared spectroscopy (fNIRS), a non-invasive brain measurement device, to augment an interface so it uses brain activity measures as an additional input channel. I have measured and classified brain signals that are interesting in HCI context, such as mental workload and difficulty level of a task. My future work will focus on creating an interface that responds to one of those measures by adapting the interface. By combining brain signal measured with an adaptive interface I expect to contribute a functional passive brain-computer interface that measures and adapts to the user's brain signal

Augmenting bend gestures with pressure zones on flexible displays

Flexible displays have paved the road for a new generation of interaction styles that allow users to bend and twist their devices. We hypothesize that bend gestures can be augmented with "hot-key" like pressure areas. This would allow single corner bends to have multiple functions. We created three pressure and bend interaction styles and compared them to bend-only gestures on two deformable prototypes. Users preferred the bend only prototype but still appreciated the pressure & bend prototype, particularly when it came to the lock/unlock application. We found that pressure interaction is a poor replacement for touch interaction, and present design suggestions to improve its performance