Buttons are everywhere and are one of the most common interaction elements in both physical and digital interfaces. While virtual buttons offer versatility, enhancing them with realistic haptic ...feedback is challenging. Achieving this requires a comprehensive understanding of the tactile perception of physical buttons and their transferability to virtual counterparts. This research investigates tactile perception concerning button attributes such as shape, size, and roundness and their potential generalization across diverse button types. In our study, participants interacted with each of the 36 buttons in our search space and provided a response to which one they thought they were touching. The findings were used to establish six substitute buttons capable of effectively emulating tactile experiences across various buttons. In a second study, these substitute buttons were validated against virtual buttons in VR. Highlighting the potential use of the substitute buttons as haptic proxies for applications such as encountered-type haptics.
Welcome to this issue of the Proceedings of the ACM on Human-Computer Interaction, bringing together contributions from the community on Engineering Interactive Computing Systems (EICS). The EICS ...track of the PACM-HCI is the primary venue for research contributions at the intersection of Human-Computer Interaction (HCI) and Software Engineering. This year, over the three rounds of submissions, for the issue of PACM-HCI we received 68 valid submissions (out of 90 submissions in total), of which we carefully selected 19 papers, bringing our acceptance rate to 27.9%. The result of this selection process is presented in this issue of the Proceedings of the ACM.
When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided ...Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project.
FORTNIoT Coppers, Sven; Vanacken, Davy; Luyten, Kris
Proceedings of ACM on interactive, mobile, wearable and ubiquitous technologies,
12/2020, Letnik:
4, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Ubiquitous environments, such as smart homes, are becoming more intelligent and autonomous. As a result, their behavior becomes harder to grasp and unintended behavior becomes more likely. ...Researchers have contributed tools to better understand and validate an environments' past behavior (e.g. logs, end-user debugging), and to prevent unintended behavior. There is, however, a lack of tools that help users understand the future behavior of such an environment. Information about the actions it will perform, and why it will perform them, remains concealed. In this paper, we contribute FORTNIoT, a well-defined approach that combines self-sustaining predictions (e.g. weather forecasts) and simulations of trigger-condition-action rules to deduce when these rules will trigger in the future and what state changes they will cause to connected smart home entities. We implemented a proof-of-concept of this approach, as well as a visual demonstrator that shows such predictions, including causes and effects, in an overview of a smart home's behavior. A between-subject evaluation with 42 participants indicates that FORTNIoT predictions lead to a more accurate understanding of the future behavior, more confidence in that understanding, and more appropriate trust in what the system will (not) do. We envision a wide variety of situations where predictions about the future are beneficial to inhabitants of smart homes, such as debugging unintended behavior and managing conflicts by exception, and hope to spark a new generation of intelligible tools for ubiquitous environments.
Abstract
Feedback and feedforward are two fundamental mechanisms that support users’ activities while interacting with computing devices. While feedback can be easily solved by providing information ...to the users following the triggering of an action, feedforward is much more complex as it must provide information before an action is performed. For interactive applications where making a mistake has more impact than just reduced user comfort, correct feedforward is an essential step toward correctly informed, and thus safe, usage. Our approach, Fortunettes, is a generic mechanism providing a systematic way of designing feedforward addressing both action and presentation problems. Including a feedforward mechanism significantly increases the complexity of the interactive application hardening developers’ tasks to detect and correct defects. We build upon an existing formal notation based on Petri Nets for describing the behavior of interactive applications and present an approach that allows for adding correct and consistent feedforward.
Smart home inhabitants can specify trigger-condition-action rules to control the home's behavior. As the number of rules and their complexity grow, however, so does the probability of issues such as ...inconsistencies and redundancies. These can lead to unintended behavior, including security vulnerabilities and wasted resources, which harms the inhabitants' trust in the system. Existing approaches to handle unintended behavior typically require inhabitants to define all-encompassing, permanent solutions by modifying the rules. Although this is fitting in certain situations, some unforeseen situations might occur. We argue that the user always must have the last word to avoid unwanted behaviors, without altering the overall behavior. With FortClash, we present an approach to predict many different types of unintended behavior, and contribute four novel mechanisms to mediate them that rely on making one-time exceptions. With FortClash, inhabitants gain a new tool to deal with unintended behavior in the short-term that is compatible with existing long-term approaches such as editing rules.
As robots are equipped with software that makes them increasingly autonomous, it becomes harder for humans to understand and control these robots. Human users should be able to understand and, to a ...certain amount, predict what the robot will do. The software that drives a robotic system is often very complex, hard to understand for human users, and there is only limited support for ensuring robotic systems are also intelligible. Adding intelligibility to the behavior of a robotic system improves the predictability, trust, safety, usability, and acceptance of such autonomous robotic systems. Applying intelligibility to the interface design can be challenging for developers and designers of robotic systems, as they are expert users in robot programming but not necessarily experts on interaction design. We propose Choreobot, an interactive, online, and visual dashboard to use with our reference framework to help identify where and when adding intelligibility to the interface design is required, desired, or optional. The reference framework and accompanying input cards allow developers and designers of robotic systems to specify a usage scenario as a set of actions and, for each action, capture the context data that is indispensable for revealing when feedforward is required. The Choreobot interactive dashboard generates a visualization that presents this data on a timeline for the sequence of actions that make up the usage scenario. A set of heuristics and rules are included that highlight where and when feedforward is desired. Based on these insights, the developers and designers can adjust the interactions to improve the interaction for the human users working with the robotic system.
Navigating the interaction landscape of Virtual Reality (VR) and Augmented Reality (AR) presents significant complexities due to the plethora of available input hardware and interaction modalities, ...compounded by spatially diverse visual interfaces. Such complexities elevate the likelihood of user errors, necessitating frequent backtracking. To address this, we introduce ViRgilites, a virtual guidance framework that delivers multi-level feedforward information covering the available interaction techniques as well as the future possibilities to interact with virtual objects, anticipating the interaction effects and how they fit with the overall user's goal. ViRgilites is engineered to facilitate task execution, empowering users to make informed decisions about action methodologies and alternative courses of action. This paper presents the architecture and functionality of ViRgilites and demonstrates its efficacy through evaluation with a formative user study.
In domains where users are exposed to large variations in visuo-spatial features among designs, they often spend excess time searching for common elements (features) on an interface. This article ...contributes individualised predictive models of visual search, and a computational approach to restructure graphical layouts for an individual user such that features on a new, unvisited interface can be found quicker. It explores four technical principles inspired by the human visual system (HVS) to predict expected positions of features and create individualised layout templates: (I) the interface with highest frequency is chosen as the template; (II) the interface with highest predicted recall probability (serial position curve) is chosen as the template; (III) the most probable locations for features across interfaces are chosen (visual statistical learning) to generate the template; (IV) based on a generative cognitive model, the most likely visual search locations for features are chosen (visual sampling modelling) to generate the template. Given a history of previously seen interfaces, we restructure the spatial layout of a new (unseen) interface with the goal of making its features more easily findable. The four HVS principles are implemented in Familiariser, a web browser that automatically restructures webpage layouts based on the visual history of the user. Evaluation of Familiariser (using visual statistical learning) with users provides first evidence that our approach reduces visual search time by over 10%, and number of eye-gaze fixations by over 20%, during web browsing tasks.
PDF
