Browsing by Author "Chattopadhyay, Debaleena"

Now showing 1 - 10 of 11
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    Categorization-based stranger avoidance does not explain the uncanny valley effect
    (Elsevier, 2017-04) MacDorman, Karl F.; Chattopadhyay, Debaleena; BioHealth Informatics, School of Informatics and Computing
    The uncanny valley hypothesis predicts that an entity appearing almost human risks eliciting cold, eerie feelings in viewers. Categorization-based stranger avoidance theory identifies the cause of this feeling as categorizing the entity into a novel category. This explanation is doubtful because stranger is not a novel category in adults; infants do not avoid strangers while the category stranger remains novel; infants old enough to fear strangers prefer photographs of strangers to those more closely resembling a familiar person; and the uncanny valley’s characteristic eeriness is seldom felt when meeting strangers. We repeated our original experiment with a more realistic 3D computer model and found no support for categorization-based stranger avoidance theory. By contrast, realism inconsistency theory explains cold, eerie feelings elicited by transitions between instances of two different, mutually exclusive categories, given that at least one category is anthropomorphic: Cold, eerie feelings are caused by prediction error from perceiving some features as features of the first category and other features as features of the second category. In principle, realism inconsistency theory can explain not only negative evaluations of transitions between real and computer modeled humans but also between different vertebrate species.
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    Endorsement, Prior Action, and Language: Modeling Trusted Advice in Computerized Clinical Alerts
    (ACM, 2016-05) Chattopadhyay, Debaleena; Duke, Jon; Bolchini, Davide; Human-Centered Computing, School of Informatics and Computing
    The safe prescribing of medications via computerized physician order entry routinely relies on clinical alerts. Alert compliance, however, remains surprisingly low, with up to 95% often ignored. Prior approaches, such as improving presentational factors in alert design, had limited success, mainly due to physicians' lack of trust in computerized advice. While designing trustworthy alert is key, actionable design principles to embody elements of trust in alerts remain little explored. To mitigate this gap, we introduce a model to guide the design of trust-based clinical alerts-based on what physicians value when trusting advice from peers in clinical activities. We discuss three key dimensions to craft trusted alerts: using colleagues' endorsement, foregrounding physicians' prior actions, and adopting a suitable language. We exemplify our approach with emerging alert designs from our ongoing research with physicians and contribute to the current debate on how to design effective alerts to improve patient safety.
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    Familiar faces rendered strange: Why inconsistent realism drives characters into the uncanny valley
    (ARVO, 2016-09-01) Chattopadhyay, Debaleena; MacDorman, Karl F.; Department of Human Centered Computing, School of Informatics and Computing
    Computer-modeled characters resembling real people sometimes elicit cold, eerie feelings. This effect, called the uncanny valley, has been attributed to uncertainty about whether the character is human or living or real. Uncertainty, however, neither explains why anthropomorphic characters lie in the uncanny valley nor their characteristic eeriness. We propose that realism inconsistency causes anthropomorphic characters to appear unfamiliar, despite their physical similarity to real people, owing to perceptual narrowing. We further propose that their unfamiliar, fake appearance elicits cold, eerie feelings, motivating threat avoidance. In our experiment, 365 participants categorized and rated objects, animals, and humans whose realism was manipulated along consistency-reduced and control transitions. These data were used to quantify a Bayesian model of categorical perception. In hypothesis testing, we found reducing realism consistency did not make objects appear less familiar, but only animals and humans, thereby eliciting cold, eerie feelings. Next, structural equation models elucidated the relation among realism inconsistency (measured objectively in a two-dimensional Morlet wavelet domain inspired by the primary visual cortex), realism, familiarity, eeriness, and warmth. The fact that reducing realism consistency only elicited cold, eerie feelings toward anthropomorphic characters, and only when it lessened familiarity, indicates the role of perceptual narrowing in the uncanny valley.
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    From Critique to Collaboration: Rethinking Computerized Clinical Alerts
    (Office of the Vice Chancellor for Research, 2016-04-08) Bolchini, Davide; Chattopadhyay, Debaleena; Jia, Yuan; Ghahari, Romisa R.; Duke, Jon
    The safe prescribing of medications via computerized physician order entry routinely relies on clinical alerts. Alert compliance, however, remains surprisingly low—with up to 96% of such alerts ignored daily. Prior approaches, such as improving presentational factors in alert design, had limited success, mainly due to physicians’ lack of trust in computerized advice. While designing trustworthy alert is key, actionable design principles to embody elements of trust in alerts remain little explored. To address this issue, we focus on improving the trust between physicians and computerized advice by examining why physicians trust their medical colleagues. To understand trusted advice among physicians, we conducted three contextual inquiries in a hospital setting (n = 22) and corroborated our findings with a survey (n = 37). Drivers that guided physicians in trusting peer advice included: timeliness of the advice, collaborative language, empathy, level of specialization, and medical hierarchy. Based on these findings, we introduced seven design directions for trust-based alerts: endorsement, transparency, team sensing, collaborative, empathic, conflict mitigating, and agency laden. Grounded in these results, we then proposed a model to guide the design of trust-based clinical alerts. Our model constitutes of three key dimensions, using colleagues’ endorsement, foregrounding physicians’ prior actions, and adopting a suitable language. Using this model, we iteratively designed, pruned, and validated a set of novel alert designs. We are currently evaluating eleven alert designs in an online survey with physicians. The ongoing survey evaluates the likelihood of alert compliance and the perceived value of our proposed trust-based alerts. Next, we are planning in-lab studies to evaluate physicians’ cognitive load during decision making and measure attention to different trust cues using gaze duration and trajectories. Our work contributes to the current debate on how to design effective alerts to improve patient safety. Acknowledgements. This research material is based on work supported by the National Science Foundation under Grant #1343973. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the NSF.
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    Laid-Back, Touchless Collaboration around Wall-size Displays: Visual Feedback and Affordances
    (http://www.powerwall.mdx.ac.uk/, 2013-04-27) Chattopadhyay, Debaleena; Bolchini, Davide
    To facilitate interaction and collaboration around ultra-high-resolution, Wall-Size Displays (WSD), post-WIMP interaction modes like touchless and multi-touch have opened up new, unprecedented opportunities. Yet to fully harness this potential, we still need to understand fundamental design factors for successful WSD experiences. Some of these include visual feedback for touchless interactions, novel interface affordances for at-a-distance, high-bandwidth input, and the techno-social ingredients supporting laid-back, relaxed collaboration around WSDs. This position paper highlights our progress in a long-term research program that examines these issues and spurs new, exciting research directions. We recently completed a study aimed at investigating the properties of visual feedback in touchless WSD interaction, and we discuss some of our findings here. Our work exemplifies how research in WSD interaction calls for re-conceptualizing basic, first principles of Human-Computer Interaction (HCI) to pioneer a suite of next-generation interaction environments.
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    NOVEL INTERACTION TECHNIQUES FOR COLLABORATING ON WALL-SIZED DISPLAYS.
    (Office of the Vice Chancellor for Research, 2012-04-13) Chattopadhyay, Debaleena; He, Li; Jia, Yuan; Bolchini, Davide
    Performing and collaborating on information-intensive tasks - like review-ing and analyzing multiple charts - is an essential, but currently difficult, ac-tivity in desktop environments. The problem is the low resolution of the dis-play that forces users to visualize only few pieces of information concurrent-ly, and to switch focus very frequently. To facilitate productivity and collabo-rative decision-making, teams of users are increasingly adopting wall-sized interactive displays. Yet, to harness the full potential of these devices, it is critical to understand how to best support inter-member cognition and navi-gation in such large information spaces. To navigate information, the wall-display’s overwhelming size (often 18 X 6 feet) make existing desktop-driven interaction and organization techniques (like “point-and-click” and “taskbar”) extremely inefficient. Also, with time, users get exhausted walk-ing to reach different elements spread over the wall-display. Moreover, being aware of the collaborative events happening around the display, while work-ing on it, often exceeds users’ cognitive capacity. To address these limita-tions, we are investigating four novel interaction techniques for wall-display user experiences. “Timeline” allows browsing large collections of elements over time, while or after collaborative work; “Cabinet” supports temporary storage and effortless retrieval of displayed elements; “Magnet” enables us-ers to virtually reach remote objects on the wall display; “In-focus” allows facilitated and non-intrusive awareness of members’ interaction. We are planning to prototype and evaluate these techniques using off-the-shelf in-put modalities such as multi-touch gesture and mid-air gesture, as well as software and wall-sized displays made available by the University Infor-mation Technology Services (UITS) at IUPUI. In our evaluation with users, we hypothesize that, with respect to desktop interaction techniques, the proposed techniques will increase efficiency in navigation and information organization tasks, reduce perceived cognitive load, while at the same time engender better collaboration and decision-making.
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    Reducing consistency in human realism increases the uncanny valley effect; increasing category uncertainty does not
    (Elsevier, 2016-01) MacDorman, Karl F.; Chattopadhyay, Debaleena; Human-Centered Computing, School of Informatics and Computing
    Human replicas may elicit unintended cold, eerie feelings in viewers, an effect known as the uncanny valley. Masahiro Mori, who proposed the effect in 1970, attributed it to inconsistencies in the replica’s realism with some of its features perceived as human and others as nonhuman. This study aims to determine whether reducing realism consistency in visual features increases the uncanny valley effect. In three rounds of experiments, 548 participants categorized and rated humans, animals, and objects that varied from computer animated to real. Two sets of features were manipulated to reduce realism consistency. (For humans, the sets were eyes–eyelashes–mouth and skin–nose–eyebrows.) Reducing realism consistency caused humans and animals, but not objects, to appear eerier and colder. However, the predictions of a competing theory, proposed by Ernst Jentsch in 1906, were not supported: The most ambiguous representations—those eliciting the greatest category uncertainty—were neither the eeriest nor the coldest.
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    Understanding Advice Sharing among Physicians: Towards Trust-Based Clinical Alerts
    (Oxford, 2016-06) Chattopadhyay, Debaleena; Ghahari, Romisa Rohani; Duke, Jon; Bolchini, Davide; Department of Human-Centered Computing, School of Informatics and Computing
    Safe prescribing of medications relies on drug safety alerts, but up to 96% of such warnings are ignored by physicians. Prior research has proposed improvements to the design of alerts, but with limited increase in adherence. We propose a different perspective: before re-designing alerts, we focus on improving the trust between physicians and computerized advice by examining why physicians trust their medical colleagues. To understand trusted advice among physicians, we conducted three contextual inquiries in a hospital setting (22 participants), and corroborated our findings with a survey (37 participants). Drivers that guide physicians in trusting peer advice include: timeliness of the advice, collaborative language, empathy, level of specialization and medical hierarchy. Based on these findings, we introduce seven design directions for trust-based alerts: endorsement, transparency, team sensing, collaborative, empathic, conflict mitigating and agency laden. Our work contributes to novel alert design strategies to improve the effectiveness of drug safety advice.
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    Understanding interaction mechanics in touchless target selection
    (2016-07-28) Chattopadhyay, Debaleena; Bolchini, Davide; MacDorman, Karl F.; Voida, Stephen; Stolterman, Erik
    We use gestures frequently in daily life—to interact with people, pets, or objects. But interacting with computers using mid-air gestures continues to challenge the design of touchless systems. Traditional approaches to touchless interaction focus on exploring gesture inputs and evaluating user interfaces. I shift the focus from gesture elicitation and interface evaluation to touchless interaction mechanics. I argue for a novel approach to generate design guidelines for touchless systems: to use fundamental interaction principles, instead of a reactive adaptation to the sensing technology. In five sets of experiments, I explore visual and pseudo-haptic feedback, motor intuitiveness, handedness, and perceptual Gestalt effects. Particularly, I study the interaction mechanics in touchless target selection. To that end, I introduce two novel interaction techniques: touchless circular menus that allow command selection using directional strokes and interface topographies that use pseudo-haptic feedback to guide steering–targeting tasks. Results illuminate different facets of touchless interaction mechanics. For example, motor-intuitive touchless interactions explain how our sensorimotor abilities inform touchless interface affordances: we often make a holistic oblique gesture instead of several orthogonal hand gestures while reaching toward a distant display. Following the Gestalt theory of visual perception, we found similarity between user interface (UI) components decreased user accuracy while good continuity made users faster. Other findings include hemispheric asymmetry affecting transfer of training between dominant and nondominant hands and pseudo-haptic feedback improving touchless accuracy. The results of this dissertation contribute design guidelines for future touchless systems. Practical applications of this work include the use of touchless interaction techniques in various domains, such as entertainment, consumer appliances, surgery, patient-centric health settings, smart cities, interactive visualization, and collaboration.
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    Understanding Visual Feedback in Large-Display Touchless Interactions: An Exploratory Study
    (2014-07-20) Chattopadhyay, Debaleena; Bolchini, Davide
    Touchless interactions synthesize input and output from physically disconnected motor and display spaces without any haptic feedback. In the absence of any haptic feedback, touchless interactions primarily rely on visual cues, but properties of visual feedback remain unexplored. This paper systematically investigates how large-display touchless interactions are affected by (1) types of visual feedback—discrete, partial, and continuous; (2) alternative forms of touchless cursors; (3) approaches to visualize target-selection; and (4) persistent visual cues to support out-of-range and drag-and-drop gestures. Results suggest that continuous was more effective than partial visual feedback; users disliked opaque cursors, and efficiency did not increase when cursors were larger than display artifacts’ size. Semantic visual feedback located at the display border improved users’ efficiency to return within the display range; however, the path of movement echoed in drag-and-drop operations decreased efficiency. Our findings contribute key ingredients to design suitable visual feedback for large-display touchless environments.