Haptic and sensing devices

会議の名前
CHI 2023
DataLev: Mid-air Data Physicalisation Using Acoustic Levitation
要旨

Data physicalisation is a technique that encodes data through the geometric and material properties of an artefact, allowing users to engage with data in a more immersive and multi-sensory way. However, current methods of data physicalisation are limited in terms of their reconfigurability and the types of materials that can be used. Acoustophoresis—a method of suspending and manipulating materials using sound waves—offers a promising solution to these challenges. In this paper, we present DataLev, a design space and platform for creating reconfigurable, multimodal data physicalisations with enriched materiality using acoustophoresis. We demonstrate the capabilities of DataLev through eight examples and evaluate its performance in terms of reconfigurability and materiality. Our work offers a new approach to data physicalisation, enabling designers to create more dynamic, engaging, and expressive artefacts.

著者
Lei Gao
University College London, London, United Kingdom
Pourang Irani
University of British Columbia (Okanagan), Kelowna, British Columbia, Canada
Sriram Subramanian
University College London, London, United Kingdom
Gowdham Prabhakar
University College London, London, United Kingdom
Diego Martinez Plasencia
University College of London, London, United Kingdom
Ryuji Hirayama
University College London, London, United Kingdom
論文URL

https://doi.org/10.1145/3544548.3581016

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In-vehicle Performance and Distraction for Midair and Touch Directional Gestures
要旨

We compare the performance and level of distraction of expressive directional gesture input in the context of in-vehicle system commands. Center console touchscreen swipes and midair swipe-like movements are tested in 8-directions, with 8-button touchscreen tapping as a baseline. Participants use these input methods for intermittent target selections while performing the Lane Change Task in a virtual driving simulator. Input performance is measured with time and accuracy, cognitive load with deviation of lane position and speed, and distraction from frequency of off-screen glances. Results show midair gestures were less distracting and faster, but with lower accuracy. Touchscreen swipes and touchscreen tapping are comparable across measures. Our work provides empirical evidence for vehicle interface designers and manufacturers considering midair or touch directional gestures for centre console input.

著者
Arman Hafizi
Computer Science, Waterloo, Ontario, Canada
Jay Henderson
University of Waterloo, Waterloo, Ontario, Canada
Ali Neshati
University of Waterloo, Waterloo, Ontario, Canada
Wei Zhou
Huawei, Markham, Ontario, Canada
Edward Lank
University of Waterloo, Waterloo, Ontario, Canada
Daniel Vogel
University of Waterloo, Waterloo, Ontario, Canada
論文URL

https://doi.org/10.1145/3544548.3581335

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Enabling Voice-Accompanying Hand-to-Face Gesture Recognition with Cross-Device Sensing
要旨

Gestures performed accompanying the voice are essential for voice interaction to convey complementary semantics for interaction purposes such as wake-up state and input modality. In this paper, we investigated voice-accompanying hand-to-face (VAHF) gestures for voice interaction. We targeted on hand-to-face gestures because such gestures relate closely with speech and yield significant acoustic features (e.g., impeding voice propagation). We conducted a user study to explore the design space of VAHF gestures, where we first gathered candidate gestures and then applied a structural analysis to them in different dimensions (e.g., contact position and type), outputting a total of 8 VAHF gestures with good usability and least confusion. To facilitate VAHF gesture recognition, we proposed a novel cross-device sensing method that leverages heterogeneous channels (vocal, ultrasound, and IMU) of data from commodity devices (earbuds, watches, and rings). Our recognition model achieved an accuracy of 97.3\% for recognizing 3 gestures and 91.5\% for recognizing 8 gestures \revision{(excluding the "empty" gesture)}, proving the high applicability. Quantitative analysis also shed light on the recognition capability of each sensor channel and their different combinations. In the end, we illustrated the feasible use cases and their design principles to demonstrate the applicability of our system in various scenarios.

受賞
Honorable Mention
著者
Zisu Li
The Hong Kong University of Science and Technology, Hong Kong SAR, China
Chen Liang
Tsinghua University, Beijing, Beijing, China
Yuntao Wang
Tsinghua University, Beijing, China
Yue Qin
Tsinghua University, Beijing, China
Chun Yu
Tsinghua University, Beijing, China
Yukang Yan
Tsinghua University, Beijing, China
Mingming Fan
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
Yuanchun Shi
Tsinghua University, Beijing, China
論文URL

https://doi.org/10.1145/3544548.3581008

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Evaluating Across-Hinge Dragging with Pen and Touch on Curved and Foldable Displays
要旨

Foldable touch screens are increasingly popular, but little research has explored how the hinge impacts usability and performance. We evaluate across- and along-hinge drag gestures on a series of prototypes emulating foldable all-screen laptops with a curved hinge radius ranging from 1mm to 24mm. Results show that using a large 24mm hinge radius instead of a small 1mm hinge radius can decrease drag time by 13% and movement variability by 7% for touch input. However, hinge radius had no effect on performance for pen input. Further, we found that dragging along the hinge was up to 30% faster than dragging across the hinge, especially when dragging across at an acute angle to the hinge. Using these results, we demonstrate use cases for across- and along-hinge gestures. Our findings provide guidance for hardware and interaction designers seeking to create foldable touchscreen devices and their accompanying software.

著者
Graeme Zinck
University of Waterloo, Waterloo, Ontario, Canada
Roya A. Cody
Huawei Technologies, Markham, Ontario, Canada
Che Yan
Huawei Technologies, Markham, Ontario, Canada
Da-Yuan Huang
Huawei Canada, Markham, Ontario, Canada
Wei Li
Huawei Canada, Markham, Ontario, Canada
Daniel Vogel
University of Waterloo, Waterloo, Ontario, Canada
論文URL

https://doi.org/10.1145/3544548.3580825

動画
Generating Real-Time, Selective, and Multimodal Haptic Effects from Sound for Gaming Experience Enhancement
要旨

We propose an algorithm that generates a vibration, an impact, or a vibration+impact haptic effect by processing a sound signal in real time. Our algorithm is selective in that it matches the most appropriate type of haptic effects to the sound using a machinelearning classifier (random forest) that is built on expert-labeled datasets. Our algorithm is tailored to enhance user experiences for video game play, and we present two examples for the RPG (roleplaying game) and FPS (first-person shooter) genres. We demonstrate the effectiveness of our algorithm by a user study in comparison to other state-of-the-art (SOTA) methods for the same crossmodal conversion. Our system elicits better multisensory user experiences than the SOTA algorithms for both game genres.

著者
Gyeore Yun
POSTECH, Pohang, Korea, Republic of
Minjae Mun
POSTECH, Pohang, Korea, Republic of
Jungeun Lee
Pohang University of Science and Technology (POSTECH), Pohang, Gyeongsangbuk, Korea, Republic of
Dong-Geun Kim
Pohang University of Science and Technology, Pohang, Gyungsangbuk, Korea, Republic of
Hong Z. Tan
Purdue University, West Lafayette, Indiana, United States
Seungmoon Choi
Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk, Korea, Republic of
論文URL

https://doi.org/10.1145/3544548.3580787

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Varying Subjective Speed-accuracy Biases to Evaluate the Generalizability of Experimental Findings on Pointing-facilitation Techniques
要旨

In 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.

著者
Shota Yamanaka
Yahoo Japan Corporation, Tokyo, Japan
Taiki Kinoshita
Meiji University, Tokyo, Japan
Yosuke Oba
Meiji University, Tokyo, Japan
Ryuto Tomihari
Meiji University, Tokyo, Japan
Homei Miyashita
Meiji University, Tokyo, Japan
論文URL

https://doi.org/10.1145/3544548.3580740

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