Conversational agents that participate in or mediate group interaction introduce challenges that extend beyond supporting individual users, raising new questions about how agents participate in and influence groups. To characterise this emerging design space, we present a systematic review of 53 peer-reviewed studies on group conversational agents (GCAs). We analyse how GCAs intervene in group-level processes, including participation regulation, conflict mediation, task alignment, and execution support. Using concepts from group research as an analytic lens, we organise prior GCA work around recurring group interactional challenges (orientation, conflict, alignment, and execution), and examine the roles agents are designed to play in addressing these challenges. We find that GCAs are predominantly designed as short-term, role-bounded interventions targeting isolated challenges in bounded interactional contexts. We further identify recurring structural tensions in GCA design, including tradeoffs between visibility and discretion, proactivity and group autonomy, and agent authority and group ownership. Together, these findings clarify how current GCAs are positioned within group interaction, surface the implicit assumptions embedded in their designs, and outline open questions for future research on conversational agents as group-level interventions.

While reciprocal self-disclosure drives intimacy, digital tools seldom scaffold autonomy, competence, and relatedness—the motivational underpinnings defined by Self-Determination Theory (SDT) that enable deep exchange. We introduce a chatbot employing dual-layer scaffolding to satisfy these needs: first providing enabling affordances (instrumental support) for vulnerability, then mediating affordances (relational support) for responsiveness. In a randomized study (N = 72; 36 couples) comparing Partner Support (PS: both layers), Direct Support (DS: enabling only), and Basic Prompt (BP: questions only), results reveal a critical distinction. While enabling affordances (PS, DS) were sufficient to deepen disclosure, only mediating affordances (PS) reliably elicited partner-provided need support and increased perceived closeness. Furthermore, controlled motivation decreased across conditions, and scaffolding buffered vitality, which remained stagnant in BP. We contribute empirical evidence that SDT-guided mediation fosters connection, offering a practical framework for designing AI-mediated conversations that support, rather than replace, human intimacy.

Social platforms have expanded opportunities for deliberation with the comments being used to inform one’s opinion. However, using such information to form opinions is challenged by unsubstantiated or false content. To enhance the quality of opinion formation and potentially confer resistance to misinformation, we developed Iffy-Or-Not ( ION ), a browser extension that seeks to invoke critical thinking when reading texts. With three features guided by argumentation theory, ION highlights fallacious content, suggests diverse queries to probe them with, and offers deeper questions to consider and chat with others about. From a user study ( \(N=18\) ), we found that ION encourages users to be more attentive to the content, suggests queries that align with or are preferable to their own, and poses thought-provoking questions that expands their perspectives. However, some participants expressed aversion to ION due to misalignments with their information goals and thinking predispositions. Potential backfiring effects with ION are discussed.

Nudging participants with text-based reflective nudges enhances deliberation quality on online deliberation platforms. The effectiveness of multimodal reflective nudges, however, remains largely unexplored. Given the multi-sensory nature of human perception, incorporating diverse modalities into self-reflection mechanisms has the potential to better support various reflective styles. This paper explores how presenting reflective nudges of different types (direct: persona and indirect: storytelling) in different modalities (text, image, video and audio) affects deliberation quality. We conducted two user studies with 20 and 200 participants respectively. The first study identifies the preferred modality for each type of reflective nudges, revealing that text is most preferred for persona and video is most preferred for storytelling. The second study assesses the impact of these modalities on deliberation quality. Our findings reveal distinct effects associated with each modality, providing valuable insights for developing more inclusive and effective online deliberation platforms.

Mutual reminiscence, defined as revisiting shared positive memories through reciprocal self-disclosure, strengthens emotional bonds, enhances well-being, and deepens intimacy. However, most technology-mediated reminiscence tools emphasize individual reflection or one-way storytelling, which overlooks the dynamic, interactive dialogue essential for meaningful mutual reminiscence. To address this limitation, we introduce Remini, a chatbot designed to support reciprocal self-disclosure between close partners such as couples, friends, or family members. Grounded in the Social Functions of Autobiographical Memory (SFAM) framework, Remini uses conversational AI to guide emotionally rich exchanges through five narrative phases: rapport building, memory narration, elaboration, reflection, and summary. In a mixed-method, both between- and within- subjects study (N = 48, 24 dyads), we compare Remini to a baseline chatbot that offers minimal memory-trigger prompts. Our findings show that structured guidance from Remini significantly improves positive affect, feeling of connection, and engagement. It also fosters more detailed narrative co-construction and greater reciprocal self-disclosure. Participant feedback highlights the practical value, perceived benefits, and design considerations of chatbot-mediated reminiscence. We contribute empirically grounded design implications for conversational agents that strengthen human connection through mutual reminiscence.

Collaborative Qualitative Analysis (CQA) can enhance qualitative analysis rigor and depth by incorporating varied viewpoints. Nevertheless, ensuring a rigorous CQA procedure itself can be both complex and costly. To lower this bar, we take a theoretical perspective to design a one-stop, end-to-end workflow, CollabCoder, that integrates Large Language Models (LLMs) into key inductive CQA stages. In the independent open coding phase, CollabCoder offers AI-generated code suggestions and records decision-making data. During the iterative discussion phase, it promotes mutual understanding by sharing this data within the coding team and using quantitative metrics to identify coding (dis)agreements, aiding in consensus-building. In the codebook development phase, CollabCoder provides primary code group suggestions, lightening the workload of developing a codebook from scratch. A 16-user evaluation confirmed the effectiveness of CollabCoder, demonstrating its advantages over the existing CQA platform. All related materials of CollabCoder, including code and further extensions, will be included in: https://gaojie058.github.io/CollabCoder/.

The deliberative potential of online platforms has been widely examined. However, little is known about how various interface-based reflection nudges impact the quality of deliberation. This paper presents two user studies with 12 and 120 participants, respectively, to investigate the impacts of different reflective nudges on the quality of deliberation. In the first study, we examined five distinct reflective nudges: persona, temporal prompts, analogies and metaphors, cultural prompts and storytelling. Persona, temporal prompts, and storytelling emerged as the preferred nudges for implementation on online deliberation platforms. In the second study, we assess the impacts of these preferred reflectors more thoroughly. Results revealed a significant positive impact of these reflectors on deliberative quality. Specifically, persona promotes a deliberative environment for balanced and opinionated viewpoints while temporal prompts promote more individualised viewpoints. Our findings suggest that the choice of reflectors can significantly influence the dynamics and shape the nature of online discussions.

We study user's valuations of smartphone sensing resources and the factors mediating them through a systematic auction study with 108 bids from$N=18$participants, two resource use conditions [fixed battery (FB) and variable battery (VB)] and three sensors (camera, microphone, and GPS) with differing energy and privacy costs. We use a second-price sealed-bid reverse auction as this allows us to elicit the participants’ truthful perceived value for sharing resources. We show that most users would be willing to share even highly-privacy intrusive sensors if they are sufficiently compensated. At the FB level, participants placed much lower value for sharing GPS (€13) than camera (€30) or microphone (€32.5). The values people place on sharing access to resources generally reflect four considerations: 1) the perceived value of the sensor type; 2) the value of the data captured by the sensor; 3) the impact of sharing on the device; and 4) personal variations related to sharing motives, personal tendencies, and the broader sharing context. We address the practical impact of our results by presenting two case studies (collaborative sensing and collaborative AI). Finally, we derive design implications for sharing sensing resources on personal devices.

While AI-assisted individual qualitative analysis has been substantially studied, AI-assisted collaborative qualitative analysis (CQA) – a process that involves multiple researchers working together to interpret data—remains relatively unexplored. After identifying CQA practices and design opportunities through formative interviews, we designed and implemented CoAIcoder, a tool leveraging AI to enhance human-to-human collaboration within CQA through four distinct collaboration methods. With a between-subject design, we evaluated CoAIcoder with 32 pairs of CQA-trained participants across common CQA phases under each collaboration method. Our findings suggest that while using a shared AI model as a mediator among coders could improve CQA efficiency and foster agreement more quickly in the early coding stage, it might affect the final code diversity. We also emphasize the need to consider the independence level when using AI to assist human-to-human collaboration in various CQA scenarios. Lastly, we suggest design implications for future AI-assisted CQA systems.

A contiguous area cartogram is a geographic map in which the area of each region is proportional to numerical data (e.g., population size) while keeping neighboring regions connected. In this study, we investigated whether value-to-area legends (square symbols next to the values represented by the squares' areas) and grid lines aid map readers in making better area judgments. We conducted an experiment to determine the accuracy, speed, and confidence with which readers infer numerical data values for the mapped regions. We found that, when only informed about the total numerical value represented by the whole cartogram without any legend, the distribution of estimates for individual regions was centered near the true value with substantial spread. Legends with grid lines significantly reduced the spread but led to a tendency to underestimate the values. Comparing differences between regions or between cartograms revealed that legends and grid lines slowed the estimation without improving accuracy. However, participants were more likely to complete the tasks when legends and grid lines were present, particularly when the area units represented by these features could be interactively selected. We recommend considering the cartogram's use case and purpose before deciding whether to include grid lines or an interactive legend.

With fact-checking by professionals being difficult to scale on social media, algorithmic techniques have been considered. However, it is uncertain how the public may react to labels by automated fact-checkers. In this study, we investigate the use of automated warning labels derived from misinformation detection literature and investigate their effects on three forms of post engagement. Focusing on political posts, we also consider how partisanship affects engagement. In a two-phases within-subjects experiment with 200 participants, we found that the generic warnings suppressed intents to comment on and share posts, but not on the intent to like them. Furthermore, when different reasons for the labels were provided, their effects on post engagement were inconsistent, suggesting that the reasons could have undesirably motivated engagement instead. Partisanship effects were observed across the labels with higher engagement for politically congruent posts. We discuss the implications on the design and use of automated warning labels.

Artificial intelligence (AI) is increasingly used in digital products for a wide variety of purposes like content creation, recommendation and decision making. With AI technologies designed with the intent of assisting humans becoming more common, understanding how users perceive and interact with the AI becomes an important line of investigation. A key component is trust. Trust is concerned with the confidence users have in the AI and their propensity to use it. While there are many experimental studies evaluating trust in novel AI systems, a review of such studies has called out the inadequacy of the methods used to precisely and sufficiently evaluate trust. Addressing this, we propose an approach that uses the externalization of vulnerability and verbalization of thoughts in experimental studies to more adequately capture actions owing to trust in the AI.

Digital contact tracing can limit the spread of infectious diseases. Nevertheless, barriers remain to attain sufficient adoption. In this study, we investigate how willingness to participate in contact tracing is affected by two critical factors: the modes of data collection and the type of data collected. We conducted a scenario-based survey study among 220 respondents in the United States (U.S.) to understand their perceptions about contact tracing associated with automated and manual contact tracing methods. The findings indicate a promising use of smartphones and a combination of public health officials and medical health records as information sources. Through a quantitative analysis, we describe how different modalities and individual demographic factors may affect user compliance when participants are asked to provide four key information pieces for contact tracing.

Supporting eyes-free interaction, mobility and encumbrance, while providing a broad set of commands on a smartwatch display is a difficult, yet important, task. Bezel-to-bezel (B2B) gestures are valuable for rapid command invocation during eyes-free operation, however we lack knowledge regarding B2B interactions on circular devices during common usage scenarios. We aim to improve our understanding of the dynamics of B2B interactions in these scenarios by conducting two studies and a third analysis: First, we explore the performance of B2B in a seated position; second, we explore the effect of mobility and encumbrance on the B2B interaction; finally, we improve on the B2B accuracies by calculating features and utilizing machine learning. With the limited interaction capabilities on smartwatches and the importance of the scenario of use, we conclude with applications and design guidelines for improved utilization of B2B that enables effective smartwatch control while in common, mobile and eyes-free scenarios.

We advocate for the usage of hotkeys on touch-based devices by capitalising on soft keyboards through four studies. First, we evaluated visual designs and recommended icons with command names for novices while letters with command names for experts. Second, we investigated the discoverability by asking crowdworkers to use our prototype, with some tasks only doable upon successfully discovering the technique. Discovery rates were high regardless of conditions that vary the familiarity and saliency of modifier keys. However, familiarity with desktop hotkeys boosted discoverability. Our third study focused on how prior knowledge of hotkeys could be leveraged and resulted in a 5% selection time improvement and identified the role of spatial memory in retention. Finally, we compared our soft keyboard layout with a grid layout similar to FastTap. The latter offered a 12–16% gain on selection speed, but at a high cost in terms of screen estate and low spatial stability.

Reflection, a process that organizes information into a structure that incorporates both own and others’ perspectives, was previously believed to function mainly as an antecedent of political knowledge. In this paper, we first design a simple interface nudge to encourage users to reflect on their views on political issues. Second, we use an experimental study to show that reflection works in a way more than leading to political knowledge. Results from a between-subjects online experiment (N = 168) covering one crucial public issue in Singapore (i.e., fertility) showed that (a) reflection interacts with information access to influence perceived issue knowledge; (b) reflection enhances perceived attitude certainty, including perceived attitude clarity and perceived attitude correctness; (c) reflection promotes willingness to express opinions in private settings.

We investigate how users touch arbitrary shapes. First, we performed semi-structured interviews with a fifteen-shape set as prop to identify touch strategies. Results reveal four main potential touch strategies, from which we devised nine mathematical candidate models. We investigate the ability of these models to predict human behaviour in a controlled experiment. We found that the center of a shape’s bounding box best approximates a user’s target location when touching arbitrary shapes. Our findings not only invite designers to use a larger variety of shapes, but can also be used to design touch interaction adapted to user behaviour using our model. As an example, they are likely to be valuable for the creation of applications exposing shapes of various complexities, like drawing applications.

The ever-increasing ubiquity of smart devices is creating new opportunities for people to interact and engage with digital information using multiple devices. In the simplest case this can refer to choosing which device to use for a particular task (e.g., phone, laptop or smartwatch), whereas a more complex example is simultaneously taking advantage of the capabilities of different devices (e.g., laptop and smart TV). Despite these types of opportunities becoming increasing available, currently the full potential of multi-device interactions is not being realized as people struggle to take advantage of them. As our first contribution, we study people’s willingness to engage with multi-device interactions and rank the factors that mediate this response through an online survey (N = 60). Our results show that users are strongly in favour of using multiple devices, but lack the awareness or information to engage with them, or feel that establishing the interactions is too laborious and would disrupt the fluidity of the interactions. Motivated by this result, as our second contribution we design and evaluate intelligent shifting cues, visualizations that offer information about available interaction opportunities and how to establish them, and study how they influence users willingness to engage in multi-device interactions. Results of our study show that the cues can be effective in helping people to engage with multiple devices, but that the suitability of the proposed device and fit with task are important mediating factors. We end the paper by deriving design implications for intelligent systems that can support people in engaging with multi-device interactions.

Cartograms are map-based data visualizations in which the area of each map region is proportional to an associated numeric data value (e.g., population or gross domestic product). A cartogram is called contiguous if it conforms to this area principle while also keeping neighboring regions connected. Because of their distorted appearance, contiguous cartograms have been criticized as difficult to read. Some authors have suggested that cartograms may be more legible if they are accompanied by interactive features (e.g., animations, linked brushing, or infotips). We conducted an experiment to evaluate this claim. Participants had to perform visual analysis tasks with interactive and noninteractive contiguous cartograms. The task types covered various aspects of cartogram readability, ranging from elementary lookup tasks to synoptic tasks (i.e., tasks in which participants had to summarize high-level differences between two cartograms). Elementary tasks were carried out equally well with and without interactivity. Synoptic tasks, by contrast, were more difficult without interactive features. With access to interactivity, however, most participants answered even synoptic questions correctly. In a subsequent survey, participants rated the interactive features as "easy to use" and "helpful." Our study suggests that interactivity has the potential to make contiguous cartograms accessible even for those readers who are unfamiliar with interactive computer graphics or do not have a prior affinity to working with maps. Among the interactive features, animations had the strongest positive effect, so we recommend them as a minimum of interactivity when contiguous cartograms are displayed on a computer screen.

Bau and Mackays OctoPocus dynamic guide helps novices learn, execute, and remember 2D surface gestures. We adapt OctoPocus to 3D mid-air gestures in Virtual Reality (VR) using an optimization-based recognizer, and by introducing an optional exploration mode to help visualize the spatial complexity of guides in a 3D gesture set. A replication of the original experiment protocol is used to compare OctoPocus in VR with a VR implementation of a crib-sheet. Results show that despite requiring 0.9s more reaction time than crib-sheet, OctoPocus enables participants to execute gestures 1.8s faster with 13.8 percent more accuracy during training, while remembering a comparable number of gestures. Subjective ratings support these results, 75 percent of participants found OctoPocus easier to learn and 83 percent found it more accurate. We contribute an implementation and empirical evidence demonstrating that an adaptation of the OctoPocus guide to VR is feasible and beneficial.

Visually impaired people encounter many challenges in their everyday life, especially when it comes to navigating and representing space. The issue of shopping is addressed mostly on the level of navigation and product detection, but conveying clues about the object position to the user is rarely implemented. This work presents a prototype of vibrotactile wristband using spatiotemporal patterns to help visually impaired users reach an object in the 2D plane in front of them. A pilot study on twelve blindfolded sighted subjects showed that discretizing space in a seven by seven targets matrix and conveying clues with a discrete pattern on the vertical axis and a continuous pattern on the horizontal axis is an intuitive and effective design.

There exists a multitude of online video tutorials to teach physical movements such as exercises. Yet, users lack support to verify the accuracy of their movements when following such videos and have to rely on their own perception. To address this, we developed a web-based application that performs human pose estimation using both video inputs from the online video and web camera, then provides different types of visual feedback to a user. Our study suggests that a user's skeleton overlaid on the user's camera feed improves user performance, whereas a user's skeleton on its own or trainer's skeleton with the trainer video offered limited benefits. Our application demonstrates the potential to enhance learning physical movements from online videos and provides a basis for other guidance systems to design suitable visualizations.

Previous work has looked closely at the challenges of using patient-generated data to enable remote assessment and monitoring by healthcare professionals. In this paper, we examine family caregivers who act as proxies for patients who may not have the capacity of capturing the necessary data. We worked with occupational therapists to develop an application for remote assessment of the safety of patients' homes by occupational therapists with the assistance of family caregivers. We evaluated the application with family caregivers and found two features unique to communication between family caregivers and healthcare professionals: Caregivers want to be able to direct healthcare professionals' attention to support problem-solving at home, and they include their perspective on how to best meet the patient's health needs. We discuss the importance of these findings for home systems in the domain of long-term chronic care.

Cognitive load is a significant challenge to users for being deliberative. Interface design has been used to mitigate this cognitive state. This paper surveys literature on the anchoring effect, partitioning effect and point-of-choice effect, based on which we propose three interface nudges, namely, the word-count anchor, partitioning text fields, and reply choice prompt. We then conducted a 2×2×2 factorial experiment with 80 participants (10 for each condition), testing how these nudges affect deliberativeness. The results showed a significant positive impact of the word-count anchor. There was also a significant positive impact of the partitioning text fields on the word count of response. The reply choice prompt showed a surprisingly negative affect on the quantity of response, hinting at the possibility that the reply choice prompt induces a fear of evaluation, which could in turn dampen the willingness to reply.

Touch-based devices, despite their mainstream availability, do not support a unified and efficient command selection mechanism, available on every platform and application. We advocate that hotkeys, conventionally used as a shortcut mechanism on desktop computers, could be generalized as a command selection mechanism for touch-based devices, even for keyboard-less applications. In this paper, we investigate the performance and usage of soft keyboard shortcuts or hotkeys (abbreviated SoftCuts) through two studies comparing different input methods across sitting, standing and walking conditions. Our results suggest that SoftCuts not only are appreciated by participants but also support rapid command selection with different devices and hand configurations. We also did not find evidence that walking deters their performance when using the Once input method.

Vibration is an efficient way of conveying information from a device to its user, and it is increasingly used for wrist or finger-worn devices such as smart rings. Unexpected vibrations or sounds from the environment may disrupt the perception of such information. Although disruptive effects have been systematically explored in vision and audition, they have been less thoroughly examined in the haptic domain. Here we briefly review the relevant literature from HCI and psychology, distilling principles of when distraction is likely. We then investigate these principles through four experiments, examining how the timing and modality of relatively rare or unexpected stimuli (surprise distractors) affect the detection and recognition of vibrotactile target patterns. At short distractor-target delays (<350 ms), both auditory and vibrotactile surprise distractors impaired performance. At a longer delay (1,050 ms), performance was not affected overall, even being improved with repeated exposure to the vibrotactile distractors. We discuss the importance of our findings in the context of HCI and cognitive psychology, and we provide design guidelines for mitigating the effects of distraction on haptic devices.

Online deliberation offers a way for citizens to collectively discuss an issue and provide input for policymakers. The overall experience of online deliberation can be affected by multiple factors. We decided to investigate the effects of moderation and opinion heterogeneity on the perceived deliberation experience, by running the first online deliberation experiment in Singapore. Our study took place in three months with three phases. In phase 1, our 2,006 participants answered a survey, that we used to create groups of different opinion heterogeneity. During the second phase, 510 participants discussed about the population issue on the online platform we developed. We gathered data on their online deliberation experience during phase 3. We found out that higher levels of moderation negatively impact the experience of deliberation on perceived procedural fairness, validity claim and policy legitimacy; and that high opinion heterogeneity is important in order to get a fair assessment of the deliberation experience.

Previous research demonstrated the ability for users to accurately recognize Spatiotemporal Vibrotactile Patterns (SVP): sequences of vibrations on different motors occurring either sequentially or simultaneously. However, the experiments were only run in a lab setting and the ability for users to recognize SVP in a real-world environment remains unclear. In this paper, we investigate how several factors may affect recognition: (1) physical activity (running), (2) cognitive task (i.e. primary task, typing), (3) distribution of the vibration motors across body parts and (4) temporality of the patterns. Our results suggest that physical activity has very little impact, specifically compared to cognitive task, location of the vibrations or temporality. We discuss these results and propose a set of guidelines for the design of SVPs.

Wearables are increasingly used during training to quantify performance and provide valuable real-time information. However, interacting with these devices in motion may disrupt the movements of the activity. We propose a method of interaction involving tapping specific locations on the body, identify candidate locations for running and cycling, and compare them in a series of controlled experiments with athletes. A purpose-built prototype measures speed of interaction and gives feedback cues for athletes to report the physical effects on the activity itself. Our results suggest that specific locations are faster and have minimal disruption to movement, even under induced fatigue conditions. The overall method is fast - 1.31s for running and 1.65s for cycling. Preferred locations differ significantly across sports, with stable body parts ranking higher. We effectively demonstrated the use of a single hand for interaction during running with two distinct tap gestures. A set of guidelines inform the design of new sports technologies.

We present Follow-My-Lead, an alternative indoor navigation technique that uses visual information recorded on an actual navigation path as a navigational guide. Its design revealed a trade-off between the fidelity of information provided to users and their effort to acquire it. Our first experiment revealed that scrolling through a continuous image stream of the navigation path is highly informative, but it becomes tedious with constant use. Discrete image checkpoints require less effort, but can be confusing. A balance may be struck by adding fast video transitions between image checkpoints, but precise control is required to handle difficult situations. Authoring still image checkpoints is also difficult, and this inspired us to invent a new technique using video checkpoints. We conducted a second experiment on authoring and navigation performance and found video checkpoints plus fast video transitions to be better than both image checkpoints plus fast video transitions and traditional written instructions.

GooseBumps is a wearable device that enables users to get spatial information using haptic feedback through servo motors. By rotating the motors, spatial information on a single axis can be encoded and processed by the users in real time. In this demonstration, the participants will be trained to use the system to use a simple driving game similar to Out Run [2] while being blindfolded. Our system thus provides sensory substitution, where visual information (such as car position and road orientation) will be encoded with haptic information. GooseBumps has multiple applications, from Virtual Reality to Visually Impaired people. This demo, in a reduced form, has been presented previously at the 2016 HacknRoll competition, where it was presented with the first prize.

Controlled experiment, an approach that has been adopted from research methods in psychology, is now widely used in HCI. Design an effective controlled experiment is not necessarily easy, even for experienced researchers. Existing controlled experiment designing tools focused more on the process of designing, but they are often not intuitive and guided enough for less experienced users to use. In this demo paper, we introduce NexP (Next Experiment Tool), a web-based open-source tool for designing controlled experiments. NexP introduces a 5-step approach to guide users through the experimental design process, and helped them to better understand the experimental design process, making it both a useful and educational tool.

Most existing colorblind aids help their users to distinguish and recognize colors but not compare them. We present HaptiColor, an assistive wristband that encodes discrete color information into spatiotemporal vibrations to support colorblind users to recognize and compare colors. We ran three experiments: the first found the optimal number and placement of motors around the wrist-worn prototype, and the second tested the optimal way to represent discrete points between the vibration motors. Results suggested that using three vibration motors and pulses of varying duration to encode proximity information in spatiotemporal patterns is the optimal solution. Finally, we evaluated the HaptiColor prototype and encodings with six colorblind participants. Our results show that the participants were able to easily understand the encodings and perform color comparison tasks accurately (94.4% to 100%).

Previous works illustrate that one's palm can reliably recognize 10 or more spatiotemporal vibrotactile patterns. However, recognition of the same patterns on other body parts is unknown. In this paper, we investigate how users perceive spatiotemporal vibrotactile patterns on the arm, palm, thigh, and waist. Results of the first two experiments indicate that precise recognition of either position or orientation is difficult across multiple body parts. Nonetheless, users were able to distinguish whether two vibration pulses were from the same location when played in quick succession. Based on this finding, we designed eight spatiotemporal vibrotactile patterns and evaluated them in two additional experiments. The results demonstrate that these patterns can be reliably recognized (>80%) across the four tested body parts, both in the lab and in a more realistic context.

Physical Loci, a technique based on an ancient memory technique, allows users to quickly learn a large command set by leveraging spatial, object and verbal/semantic memory to create a cognitive link between individual commands and nearby physical objects in a room (called loci). We first report on an experiment that showed that for learning 25 items Physical Loci outperformed a mid-air Marking Menu baseline. A long-term retention experiment with 48 items then showed that recall was nearly perfect one week later and, surprisingly, independent of whether the command/locus mapping was one's own choice or somebody else's. A final study suggested that recall performance is robust to alterations of the learned mapping, whether systematic or random.

We conducted an empirical investigation of wearable interactive rings on the noticeability of four instantaneous notification channels (light, vibration, sound, poke) and a channel with gradually increased temperature (thermal) during five levels of physical activity (laying down, sitting, standing, walking, and running). Results showed that vibration was the most reliable and fastest channel to convey notification, followed by poke and sound which shared similar noticeability. The noticeability of these three channels was not affected by the level of physical activity. The other two channels, light and thermal, were less noticeable and were affected by the level of physical activity. Our post-experimental survey indicates that while noticeability has a significant influence on user preference, each channel has its own unique advantages that make it suitable for different notification scenarios.

We present Botential, an on-body interaction method for a wearable input device that can identify the location of on-body tapping gestures, using the entire human body as an interactive surface to expand the usually limited interaction space in the context of mobility. When the sensor is being touched, Botential identifies a body part's unique electric signature, which depends on its physiological and anatomical compositions. This input method exhibits a number of advantages over previous approaches, which include: 1) utilizing the existing signal the human body already emits, to accomplish input with various body parts, 2) the ability to also sense soft and long touches, 3) an increased sensing range that covers the whole body, and 4) the ability to detect taps and hovering through clothes.

Copy-Paste (CP) operations on touchscreen smartphones are not as easy to perform as compared with similar operations on desktop computers. The smaller screen size and input area make both text selection and application switching more difficult to perform. To enable faster copy-paste on touchscreen smartphones, we introduce BezelCopy, a copy-paste technique that uses a bezel-swipe gesture to determine a rough area of interest in the document. Chosen text is magnified in a new panel to enable fast and precise selection. With the new panel, users can perform easy tap-and-drag gestures to select the exact content, and tap the application icon on the bottom of the panel to paste it to the target application. Users can further adjust the location of the pasted text in the target application using drag and drop. We conducted two experiments to compare the performance of BezelCopy with alternative approaches, and our results show that BezelCopy outperform existing copy-paste techniques for a number of commonly performed copy-paste tasks.

We present WatchIt, a prototype device that extends interaction beyond the watch surface to the wristband, and two interaction techniques for command selection and execution. Because the small screen of wristwatch computers suffers from visual occlusion and the fat finger problem, we investigated the use of the wristband as an available interaction resource. Not only does WatchIt use a cheap, energy efficient and invisible technology, but it involves simple, basic gestures that allow good performance after little training, as suggested by the results of a pilot study. We propose a novel gesture technique and an adaptation of an existing menu technique suitable for wristband interaction. In a user study, we investigated their usage in eyes-free contexts, finding that they perform well. Finally, we present techniques where the bracelet is used in addition to the screen to provide precise continuous control over list scrolling. We also report on a preliminary survey of traditional and digital jewelry that points to the high frequency of watches and bracelets in both genders and gives a sense of the tasks people feel like performing on such devices.

The widely-held view that Fitts' law expresses a speed/accuracy trade-off is presumably correct, but it is vague. We outline a simple resource-allocation theory of Fitts' law in which movement time and error trade for each other. The theory accounts quite accurately for the data of Fitts' (1954) seminal study, as well as some fresh data of our own. In both data sets we found the time/error trade-off to obey a power law. Our data, which we could analyze more thoroughly than Fitts', are consistent with a square-root function with a single adjustable constant. We suggest that the resource-allocation framework should help combine information and energy considerations to allow a more complete account of Fitts' law.