ReflecTrace: Touchless Hover Interaction on Commodity Smartphones via Corneal ReflectionWe propose an approach to detect finger hover inputs on a smartphone screen using corneal reflection images captured by the device’s built-in front camera. This method requires no external sensors or hardware, enabling hover input detection in the near-screen space that is not directly visible to the camera. By leveraging a convolutional neural network (CNN), we estimate the two-dimensional position of a hovering finger and classify it into a predefined screen grid. Experimental results show that our model achieves approximately 95% accuracy for coarse grids and maintains over 88% accuracy for finer divisions. Furthermore, our system demonstrates real-time processing capability with an end-to-end latency of approximately 22 ms on a standard smartphone. These findings highlight the practical feasibility of camera-only hover sensing and suggest a wide range of touchless interaction applications, enabling touchless interaction when touch is undesirable, pre-touch UI adaptation, and accessibility support on commodity mobile devices.2026YNYudai Nakamura et al.Keio UniversityMulti-Touch Interaction TechniquesMobile App User ExperienceMobile Accessibility DesignIUI
DuoTouch: Passive Two-Footprint Attachments Using Binary Sequences to Extend Touch InteractionDuoTouch is a passive attachment for capacitive touch panels that adds tangible input while minimizing content occlusion and loss of input area. It uses two contact footprints and two traces to encode motion as binary sequences and runs on unmodified devices through standard touch APIs. We present two configurations with paired decoders: an aligned configuration that maps fixed-length codes to discrete commands and a phase-shifted configuration that estimates direction and distance from relative timing. To characterize the system's reliability, we derive a sampling-limited bound that links actuation speed, internal trace width, and device touch sampling rate. Through technical evaluations on a smartphone and a touchpad, we report performance metrics that describe the relationship between these parameters and decoding accuracy. Finally, we demonstrate the versatility of DuoTouch by embedding the mechanism into various form factors, including a hand strap, a phone ring holder, and touchpad add-ons.2026KIKaori Ikematsu et al.LY CorporationTangible User Interface DesignPhysical-Digital Hybrid InteractionMulti-Touch Interaction TechniquesCHI
Skewed Dual Normal Distribution Model: Predicting 1D Touch Pointing Success Rate for Targets Near Screen EdgesTypical success-rate prediction models for tapping exclude targets near screen edges; however, design constraints often force such placements. Additionally, in scrollable UIs any element can move close to an edge. In this work, we model how target--edge distance affects 1D touch pointing accuracy. We propose the Skewed Dual Normal Distribution Model, which assumes the tap coordinate distribution is skewed by a nearby edge. The results of two smartphone experiments showed that, as targets approached the edge, the distribution's peak shifted toward the edge and its tail extended away. In contrast to prior reports, the success rate improved when the target touched the edge, suggesting a strategy of ``tapping the target together with the edge.'' By accounting for skew, our model predicts success rates across a wide range of conditions, including edge‑adjacent targets, thus extending coverage to the whole screen and informing UI design support tools.2026NKNobuhito Kasahara et al.Meiji UniversityTouchscreen Usability & Performance Modeling (Fitts' Law)Touch Target Selection & PointingCHI
Improving the Steering Law Throughput Calculation by Defining Effective Parameters for 3D Virtual EnvironmentsThroughput is a widely used performance metric, combining speed and accuracy into a single measure, while reducing the effect of subjective speed–accuracy trade-offs. Despite its wide application in 2D steering tasks, its direct extension to 3D presents unique challenges since 3D trajectories exhibit higher variability, and perceptual–motor factors undermine existing formulations. Consequently, throughput has not been systematically adopted for evaluating steering in 3D virtual environments. In this paper, using a controlled virtual reality user study with a ring-and-wire task, we introduce and validate a novel throughput formulation for 3D steering based on the bivariate standard deviation of the trajectory for the effective width calculation. Our results show that this formulation provides smoother throughput values across subjective speed–accuracy differences and improves model fit compared to traditional approaches. This work advances our theoretical understanding of the Steering law in 3D contexts, provides researchers and practitioners with a robust evaluation method, and establishes a foundation for future studies of complex 3D trajectory interactions.2026MAMohammadreza Amini et al.Concordia UniversityImmersion & Presence ResearchPrototyping & User TestingSocial & Collaborative VRCHI
Improving Data Quality via Pre-Task Participant Screening in Crowdsourced GUI ExperimentsIn crowdsourced user experiments that collect performance data from graphical user interface (GUI) interactions, some participants ignore instructions or act carelessly, threatening the validity of performance models. We investigate a pre-task screening method that requires simple GUI operations analogous to the main task and uses the resulting error as a continuous quality signal. Our pre-task is a brief image-resizing task in which workers match an on-screen card to a physical card; workers whose resizing error exceeds a threshold are excluded from the main experiment. The main task is a standardized pointing experiment with well-established models of movement time and error rate. Across mouse- and smartphone-based crowdsourced experiments, we show that reducing the proportion of workers exhibiting unexpected behavior and tightening the pre-task threshold systematically improve the goodness of fit and predictive accuracy of GUI performance models, demonstrating that brief pre-task screening can enhance data quality.2026TMTakaya Miyama et al.Meiji UniversityCrowdsourcing Task Design & Quality ControlPrototyping & User TestingField StudiesCHI
Normalizing Speed-accuracy Biases in 2D Pointing Tasks with Better Calculation of Effective Target WidthsFor evaluations of 2D target selection using Fitts' law, ISO 9241-411 recommends using the effective target width (W_e) calculated using the univariate standard deviation of selection coordinates. Related research proposed using a bivariate standard deviation; however, the proposal was only tested using a single speed-accuracy bias condition, thus the assessment was limited. We compared the univariate and bivariate techniques in a 2D Fitts' law experiment using three speed-accuracy biases and 346 crowdworkers. Calculating W_e using the univariate standard deviation yielded higher model correlations across all bias conditions and produced more stable throughput among the biases. The findings were also consistent in cases using randomly sampled subsets of the participant data. We recommend that future research should calculate W_e using the univariate standard deviation for fair performance evaluations. Also, we found trivial effects when using nominal or effective amplitude and using different perspectives of the task axis.2026SYShota Yamanaka et al.LY CorporationTouchscreen Usability & Performance Modeling (Fitts' Law)CHI
Verifying Finger-Fitts Models for Normalizing Subjective Speed-Accuracy BiasesPrevious studies on the Finger-Fitts law (FFitts law) are lacking in sufficient experiments to verify its inherent potential. Since the FFitts law is originally a modified version of the effective width method to normalize speed-accuracy biases, the model fit would improve if multiple biases were mixed together and the throughputs would be more stable than using the nominal target width. In this study, we conduct an experiment in which participants tap 1D-bar and 2D-circular targets under three subjective biases: balancing the speed and accuracy, emphasizing speed, and emphasizing accuracy when they perform the tasks. The results showed that applying the effective width to Ko et al.'s refined FFitts law, which represents the touch ambiguity with a free parameter, was the most successful in normalizing biases. Reanalyzing another dataset on ray-casting pointing also led to the same conclusion. We thus recommend using Ko et al.'s model with effective width when researchers compare several experimental conditions such as devices and user groups.2024SYShota Yamanaka et al.Prototyping & User TestingComputational Methods in HCIMobileHCI
The Effect of Latency on Movement Time in Path-steeringIn current graphical user interfaces, there exists a (typically unavoidable) end-to-end latency from each pointing-device movement to its corresponding cursor response on the screen, which is known to affect user performance in target selection, e.g., in terms of movement time (MT). Previous work also reported that a long latency increases MTs in path-steering tasks, but the quantitative relationship between latency and MT had not been previously investigated for path-steering. In this work, we derive models to predict MTs for path-steering and evaluate them with five tasks: goal crossing as a preliminary task for model derivation, linear-path steering, circular-path steering, narrowing-path steering, and steering with target pointing. The results show that the proposed models yielded an adjusted R^2 > 0.94, with lower AICs and smaller cross-validation RMSEs than the baseline models, enabling more accurate prediction of MTs.2024SYShota Yamanaka et al.Yahoo Japan CorporationUser Research Methods (Interviews, Surveys, Observation)Computational Methods in HCICHI
Varying Subjective Speed-accuracy Biases to Evaluate the Generalizability of Experimental Findings on Pointing-facilitation TechniquesIn typical experiments to evaluate novel pointing-facilitation techniques, participants are asked to perform a task as rapidly and accurately as possible. However, the balance can differ among participants, and the techniques' effectiveness would change if the majority of participants give weight to either speed or accuracy. We investigated the effects of three subjective biases (emphasizing speed, neutral, and emphasizing accuracy) on the evaluation results of pointing-facilitation techniques, namely Bubble Cursor and Bayesian Touch Criterion (BTC). The results indicate that Bubble Cursor outperformed the baseline in terms of movement time and error rate under all bias conditions, while BTC underperformed a simpler target-prediction technique, which was an inconsistent outcome to the original study. Examining multiple biases enables researchers to discuss the (dis)advantages of novel or existing techniques more precisely, which can be beneficial to reach a more reliable conclusion.2023SYShota Yamanaka et al.Yahoo Japan CorporationVoice User Interface (VUI) DesignComputational Methods in HCICHI
Exploring Nudge Designs to Help Adolescent SNS Users Avoid Privacy and Safety ThreatsA nudge is a method to influence individual choices without taking away freedom of choice. We are interested in whether nudges can help adolescents avoid privacy and safety threats on social network services (SNS). We conducted an online survey to compare how 11 different nudge designs influence decisions on 9 scenarios featuring various privacy and safety threats. We collected 29,608 responses from adolescent SNS users (self-claimed high school and university students), and found that nudges can help to educe potentially risk choices. Participants were more likely to avoid potentially risky choices when presented with negative frames (e.g., "90% of users would not share a photo without permission'') than affirmative ones (e.g., "10% of users would''). Social nudges displaying statistics on how likely other people would make potentially risky decisions can have a negative effect in comparison to a nudge with only general privacy and safety suggestions. We conclude by providing design considerations for privacy/safety nudges targeting adolescent SNS users.2020HMHiroaki Masaki et al.University of TokyoPrivacy by Design & User ControlDark Patterns RecognitionCHI
Modeling Fully and Partially Constrained Lasso Movements in a Grid of IconsLassoing objects is a basic function in illustration software and presentation tools. Yet, for many common object arrangements lassoing is sometimes time-consuming to perform and requires precise pen operation. In this work, we studied lassoing movements in a grid of objects similar to icons. We propose a quantitative model to predict the time to lasso such objects depending on the margins between icons, their sizes, and layout, which all affect the number of stopping and crossing movements. Results of two experiments showed that our models predict fully and partially constrained movements with high accuracy. We also analyzed the speed profiles and pen stroke trajectories and identified deeper insights into user behaviors, such as that an unconstrained area can induce higher movement speeds even in preceding path segments.2019SYShota Yamanaka et al.Yahoo Japan CorporationPrototyping & User TestingComputational Methods in HCICHI
Steering Performance with Error-accepting DelaysIn steering law tasks, deviating from the path is immediately considered an error operation. However, in navigating a hierarchical menu item, which is a representative application of the law, a deviation within a short duration is sometimes permitted. We tested the validity of the steering law model with various durations of such error-accepting delays and found that it showed high fits for each delay condition (R^(2) > 0.96) but poor fits if the delay values were not separated (R^(2) = 0.58). Because the average movement speed linearly increased as the delay increased, we refined the model by taking the delay into account, and the fitness was significantly improved (R^(2) = 0.97). Our model will help GUI designers estimate the average operational time on the basis of the menu item length, width, and error-accepting delay.2019SYShota YamanakaYahoo Japan CorporationPrototyping & User TestingComputational Methods in HCICHI
Steering through Successive ObjectsWe investigate stroking motions through successive objects with styli. There are several promising models for stroking motions, such as crossing tasks, which require endpoint accuracy of a stroke, or steering tasks, which require continuous accuracy throughout the trajectory. However, a task requiring users to repeatedly steer through constrained path segments has never been studied, although such operations are needed in GUIs, e.g., for selecting icons or objects on illustration software through lassoing. We empirically confirmed that the interval, trajectory width, and obstacle size significantly affect the movement speed. Existing models can not accurately predict user performance in such tasks. We found several unexpected results such as that steering through denser objects sometimes required less times than expected. Speed profile analysis showed the reasons behind such behaviors, such as participants' anticipation strategies. We also discuss the applicability of exiting performance models and revisions.2018SYShota Yamanaka et al.Yahoo Japan CorporationPrototyping & User TestingCHI