Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Avijit Balabantaray

dblp:353/6781 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Haptics and multimodal interaction › electrical stimulation
electrical muscle stimulation
0.812024
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
0.212024
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
YearPublicationVenuePosition
2024 Paired-EMS: Enhancing Electrical Muscle Stimulation (EMS)-based Force Feedback Experience by Stimulating Both Muscles in Antagonistic Pairs
abstract
Electrical 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
CHI4
2023 MFEMANet: an effective disaster image classification approach for practical risk assessment
Payal Bhadra, Avijit Balabantaray, Ajit Kumar Pasayat
Mach. Vis. Appl.2