Demo Data from SIGIR 2026 / reviewers in the wild / expert
Avijit Balabantaray
dblp:353/6781
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0001-3376-9786ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 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
1 paper |
Haptics and multimodal interaction · 100% |
Topics — the 2 heaviest of 2, 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
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 · 0.8formative study · 0.8
| 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 | 4 |
| 2023 | MFEMANet: an effective disaster image classification approach for practical risk assessment
Payal Bhadra, Avijit Balabantaray, Ajit Kumar Pasayat |
Mach. Vis. Appl. | 2 |