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Nima Jamalian

dblp:336/4318 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 2 · 2 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 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
Interaction techniques and input · 61% Immersive interaction · 30% Haptics and multimodal interaction · 9%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input › input sensing › tracking
hand tracking
0.612022
The Effects of Hand Tracking on User Performance: an experimental study of an object selection based memory game · ISMAR 2022
Interaction techniques and input › selection techniques
object selection
0.612022
The Effects of Hand Tracking on User Performance: an experimental study of an object selection based memory game · ISMAR 2022
Immersive interaction
virtual reality
0.612022
The Effects of Hand Tracking on User Performance: an experimental study of an object selection based memory game · ISMAR 2022
Haptics and multimodal interaction
haptic feedback
0.212022
The Effects of Hand Tracking on User Performance: an experimental study of an object selection based memory game · ISMAR 2022

Methods — techniques the papers use, named apart from their topics

within-subjects experiment · 0.6in-game analytics · 0.6
YearPublicationVenuePosition
2023 Our Nudges, Our Selves: Tailoring Mobile User Engagement Using Personality
Nima Jamalian, Marios Constantinides, Sagar Joglekar 0001, Sylvia Xueni Pan, Daniele Quercia
INTERACT (4)1
2022 The Effects of Hand Tracking on User Performance: an experimental study of an object selection based memory game
abstract
Until recently, Virtual Reality (VR) applications relied on controllers to enable user interaction in virtual environments. With advances in tracking technology, HMDs are now able to track the movements of users’ hands in real-time with significantly greater accuracy, allowing us to interact with the digital world directly with our hands. However, it is not entirely clear how hand tracking affects users’ performance. In this study, we investigate user performance using an in-game analytics-based assessment methodology for a VR memory puzzle task. We conducted a within-subjects experiment with 30 participants in three conditions: 1- Hand-tracking, 2-Controller Without Haptics, and 3- Controller With Haptics. In all our measurements (correct order and pattern, correct pattern only, and trial completion) except for the initial selection time, participants performed best with hand tracking. The use of controllers with haptics did not outperform controllers without haptics in most measures, possibly because other feedback cues compensated for the lack of haptics. This study helps us better understand the three selected interactivity methods when used in VR, as well as the importance of naturalistic experience in interaction design.
Nima Jamalian, Marco Gillies, Frederic Fol Leymarie, Sylvia Xueni Pan
ISMAR1