Demo Data from SIGIR 2026 / reviewers in the wild / expert
Chia-Yu Cheng
dblp:344/8768
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2024
0000-0002-5908-0477ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 3 · 1 first-author · 3 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
3 papers |
Haptics and multimodal interaction · 72% Immersive interaction · 28% |
Topics — the 4 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Haptics and multimodal interaction › electrical stimulation
electrical muscle stimulation |
0.8 | 1 | 2024 | Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic Pairs · CHI 2024 |
Haptics and multimodal interaction › haptic feedback
force feedback |
0.8 | 1 | 2024 | SpinShot: Optimizing Both Physical and Perceived Force Feedback of Flywheel-Based, Directional Impact Handheld Devices · UIST 2024 |
Immersive interaction
virtual reality |
0.8 | 1 | 2024 | SpinShot: Optimizing Both Physical and Perceived Force Feedback of Flywheel-Based, Directional Impact Handheld Devices · UIST 2024 |
Haptics and multimodal interaction › haptic feedback
wearable haptic feedback |
0.2 | 1 | 2024 | Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic Pairs · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
user experience study · 1.5formative study · 1.4perceptual study · 0.8user experience evaluation · 0.7perception study · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic PairsabstractElectrical Muscle Stimulation (EMS) has emerged as a key wearable haptic feedback technology capable of simulating a wide range of force feedback, such as the impact force of boxing punches, the weight of virtual objects, and the reaction force from pushing on a wall. To simulate these external forces, EMS stimulates the muscles that oppose (i.e. antagonistic to) the actual muscles that users activate, causing involuntary muscle contraction and haptic sensations that differ from real-world experiences. In this work, we propose Paired-EMS which simultaneously stimulates both the muscles that users activate and that prior EMS stimulates (i.e. antagonistic muscle pairs) to enhance the external force feedback experience. We first conducted a small formative study (n=8) to help design the stimulation intensity of muscle pairs, then conducted a user experience study to evaluate Paired-EMS vs. prior EMS approaches for both isometric and isotonic user actions. Study results (n=32) showed that Paired-EMS significantly improved realism, harmony, and entertainment (p<.05) with similar comfort (p>.36), and was overall preferred by 78% of participants (p<.01). Chia-Yu Cheng, Yu Chen 0078, Sitaresmi Wahyu Handani, Avijit Balabantaray, Mike Y. Chen |
CHI | 1 |
| 2024 | SpinShot: Optimizing Both Physical and Perceived Force Feedback of Flywheel-Based, Directional Impact Handheld DevicesabstractReal-world impact, such as hitting a tennis ball and a baseball, generates instantaneous, directional impact forces. However, current ungrounded force feedback technologies, such as air jets and propellers, can only generate directional impulses that are 10x-10,000x weaker. We present SpinShot, a flywheel-based device with a solenoid-actuated stopper capable of generating directional impulse of 22Nm in 1ms, which is more than 10x stronger than prior ungrounded directional technologies. Furthermore, we present a novel force design that reverses the flywheel immediately after the initial impact, to significantly increase the perceived magnitude. We conducted a series of two formative, perceptual studies (n=16, 18), followed by a summative user experience study (n=16) that compared SpinShot vs. moving mass (solenoid) and vs. air jets in a VR baseball hitting game. Results showed that SpinShot significantly improved realism, immersion, magnitude (p < .01) compared to both baselines, but significantly reduced comfort vs. air jets primarily due to the 2.9x device weight. Overall, SpinShot was preferred by 63-75% of the participants. Chia-An Fan, En-Huei Wu, Chia-Yu Cheng, Alvaro Lopez, Yu Chen 0078, Chia-Chen Chi, Yi-Sheng Chan, Ching-Yi Tsai, Mike Y. Chen |
UIST | 3 |
| 2023 | TurnAhead: Designing 3-DoF Rotational Haptic Cues to Improve First-person Viewing (FPV) ExperiencesabstractFirst-Person View (FPV) drone is a recently developed category of drones designed for precision flying and for capturing exhilarating experiences that could not be captured before, such as navigating through tight indoor spaces and flying extremely close to subjects of interest. FPV viewing experiences, while exhilarating, typically have frequent rotations that can lead to visually induced discomfort. We present TurnAhead, which uses 3-DoF rotational haptic cues that correspond to camera rotations to improve the comfort, immersion, and enjoyment of FPV experiences. It uses headset-mounted air jets to provide ungrounded rotational forces and is the first device to support rotation around all 3 axes: yaw, pitch, and roll. We conducted a series of perception and formative studies to explore the design space of timing and intensity of haptic cues, followed by user experience evaluation, for a combined total of 44 participants (n=12, 8, 6, 18). Results showed that TurnAhead significantly improved overall comfort, immersion, and enjoyment, and was preferred by 89% of participants. Bo-Cheng Ke, Min-Han Li, Yu Chen 0078, Chia-Yu Cheng, Chiao-Ju Chang, Yun-Fang Li, Shun-Yu Wang, Chiao Fang, Mike Y. Chen |
CHI | 4 |