Researchers increasingly explore deploying brain-computer interfaces (BCIs) for able-bodied users, with the motivation of accessing mental states more directly than allowed by existing body-mediated interaction.This motivation seems to contradict the long-standing HCI emphasis on embodiment, namely the general claim that the body is crucial for cognition.This paper addresses this apparent contradiction through a review of insights from embodied cognition and interaction.We first critically examine the recent interest in BCIs and identify the extent cognition in the brain is integrated with the wider body as a central concern for research.We then define the implications of an integrated view of cognition for interface design and evaluation.A counterintuitive conclusion we draw is that embodiment per se should not imply a preference for body-mediated interaction over BCIs.It can instead guide research by 1) providing bodygrounded explanations for BCI performance, 2) proposing evaluation considerations that are neglected in modular views of cognition, and 3) through the direct transfer of its design insights to BCIs.We finally reflect on HCI's understanding of embodiment and identify the neural dimension of embodiment as hitherto overlooked.

Exploratory search starts with ill-defined goals and involves browsing, learning, and formulating new targets for search. To fluidly support such dynamic search behaviours, we focus on devising interactive visual facets (IVF), visualising information facets to support user comprehension and control of the information space. To do this, we reviewed existing faceted search interfaces and derived two design requirements (DR) that have not been fully addressed to support fluid interactions in exploratory search. We then exemplified the requirements through devising an IVF tool, which coordinates a linear and a categorical facet representing the distribution and summarisation of items, respectively, and providing context for faceted exploration (DR1). To support rapid transitions between search criteria (DR2), the tool introduces a novel design concept of using facets to select items without filtering the item space. Particularly, we propose a filter-swipe technique that enables users to drag a categorical facet value sequentially over linear facet bars to view the items in the intersection of the two facets along with the categorical facet dynamically summarizing the items in the interaction. A user study of 11 participants with realistic email search tasks shows that dynamic suggestions through the timeline navigation can help discover useful suggestions for search; the novel design concept was favoured over using facet values as filters. Based on these practices, we derive IVF design implications for fluid, exploratory searches.

The term implicit interaction is often used to denote interactions that differ from traditional purposeful and attention demanding ways of interacting with computers. However, there is a lack of agreement about the term's precise meaning. This paper develops implicit interaction further as an analytic concept and identifies the methodological challenges related to HCI's particular design orientation. We first review meanings of implicit as unintentional, attentional background, unawareness, unconsciousness and implicature, and compare them in regards to the entity they qualify, the design motivation they emphasize and their constructive validity for what makes good interaction. We then demonstrate how the methodological challenges can be addressed with greater precision by using an updated, intentionality-based definition that specifies an input-effect relationship as the entity of implicit. We conclude by identifying a number of new considerations for design and evaluation, and by reflecting on the concepts of user and system agency in HCI.

The use of implicit relevance feedback from neurophysiology could deliver effortless information retrieval. However, both computing neurophysiologic responses and retrieving documents are characterized by uncertainty because of noisy signals and incomplete or inconsistent representations of the data. We present the first-of-its-kind, fully integrated information retrieval system that makes use of online implicit relevance feedback generated from brain activity as measured through electroencephalography (EEG), and eye movements. The findings of the evaluation experiment (N = 16) show that we are able to compute online neurophysiology-based relevance feedback with performance significantly better than chance in complex data domains and realistic search tasks. We contribute by demonstrating how to integrate in interactive intent modeling this inherently noisy implicit relevance feedback combined with scarce explicit feedback. Although experimental measures of task performance did not allow us to demonstrate how the classification outcomes translated into search task performance, the experiment proved that our approach is able to generate relevance feedback from brain signals and eye movements in a realistic scenario, thus providing promising implications for future work in neuroadaptive information retrieval (IR).

Motivation: Precision medicine requires the ability to predict the efficacies of different treatments for a given individual using high-dimensional genomic measurements. However, identifying predictive features remains a challenge when the sample size is small. Incorporating expert knowledge offers a promising approach to improve predictions, but collecting such knowledge is laborious if the number of candidate features is very large. Results: We introduce a probabilistic framework to incorporate expert feedback about the impact of genomic measurements on the outcome of interest and present a novel approach to collect the feedback efficiently, based on Bayesian experimental design. The new approach outperformed other recent alternatives in two medical applications: prediction of metabolic traits and prediction of sensitivity of cancer cells to different drugs, both using genomic features as predictors. Furthermore, the intelligent approach to collect feedback reduced the workload of the expert to approximately 11%, compared to a baseline approach. Availability and implementation: Source code implementing the introduced computational methods is freely available at https://github.com/AaltoPML/knowledge-elicitation-for-precision-medicine. Supplementary information: Supplementary data are available at Bioinformatics online.

We explore the combination of above-surface sensing with eye tracking to facilitate concurrent interaction with multiple regions on touch screens. Conventional touch input relies on positional accuracy, thereby requiring tight visual monitoring of one's own motor action. In contrast, above-surface sensing and eye tracking provides information about how user's hands and gaze are distributed across the interface. In these situations we facilitate interaction by 1) showing the visual feedback of the hand hover near user's gaze point and 2) decrease the requisite of positional accuracy by employing gestural information. We contribute input and visual feedback techniques that combine these modalities and demonstrate their use in example applications. A controlled study showed the effectiveness of our techniques for manipulation tasks against conventional touch, while the effectiveness in acquisition tasks depended on the amount of mid-air motion, leading to our conclusion that the techniques can benefit interacting with multiple interface regions.

We present a preliminary design study for utilizing eye tracking to support interacting with a multi-document visualization. Complex information seeking tasks can involve collection and comparison of multiple documents, resulting in long and sustained search sessions. The sustained and evolving nature of the session also provides the search interface the opportunity to gather information on the user state and interaction history, which can be used to adapt the information content and representation. We designed a system to evaluate how eye tracking information can be used for adapting the visual salience of information entities. The interface features documents and related keywords that are arranged in a radial layout configuration called the intent radar. Reading history and visual attention, as registered by eye tracking data, are respectively used to trace read items and for visual cueing. We evaluated the interface with 16 participants to gather subjective feedback about specific components and features of the interface. The overall results show that the interface and gaze-related appearance of keywords was positively received by the users.

We propose using eye tracking to support interface use with decreased reliance on visual guidance. While the design of most graphical user interfaces take visual guidance during manual input for granted, eye tracking allows distinguishing between the cases when the manual input is conducted with or without guidance. We conceptualize the latter cases as input with uncertainty that require separate handling. We describe the design space of input handling by utilizing input resources available to the system, possible actions the system can realize and various feedback techniques for informing the user. We demonstrate the particular action mechanisms and feedback techniques through three applications we developed for touch interaction on a large screen. We conducted a two stage study of positional accuracy during target acquisition with varying visual guidance, to determine the selection range around a touch point due to positional uncertainty. We also conducted a qualitative evaluation of example applications with participants to identify perceived utility and hand eye coordination challenges while using interfaces with decreased visual guidance.

This paper aims to broaden the understanding of computer mediated creativity from a material perspective, by emphasizing the qualities of resistance and making users' actions explicit in the design process. Resistance of material refers to the challenging nature of realizing one's intention through material during the design process. Materials are also instrumental in making user actions of creating artifacts explicit through temporary structures, residues and tools. By drawing on the accounts of craft work and design, the paper discusses how these two qualities can be deliberately addressed in the design of tools to support creative activity. The design approach is operationalized in a 3D drawing tool with the use of indirect control to control curves. The prototype was evaluated with industrial design students and practitioners in two stages, in recorded sessions and through self-documentation. The participant responses give insights into the concept of materiality in creativity support tools and in which cases these features were embraced or dismissed.