EDBT 2026 Demo / reviewers in the wild / expert
Yuefang Jiang
dblp:228/5953
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0007-0417-8673ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2Graphics, computer vision, multimedia, augmented reality and games · 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 |
Interaction techniques and input · 50% Wearable and physiological sensing · 50% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input › input device
wearable input device |
0.3 | 1 | 2018 | Wearable-based Human-Computer Interaction with LimbMotion · SenSys 2018 |
Methods — techniques the papers use, named apart from their topics
inertial sensing · 0.3acoustic sensing · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | A parallel state-space and attention-based multimodal framework for Alzheimer's disease diagnosis
Xin Sha, Shengxuan Wang, Xianrui Sun, Yuefang Jiang, Xinye Song |
Multim. Syst. | 5 |
| 2020 | Posture Tracking Meets Fitness Coaching: A Two-Phase Optimization Approach with Wearable DevicesabstractFitness training is becoming an increasingly popular way of maintaining overall health and preventing illness. However, in some cases the training could be risky and fitness-related injuries have increased by 48% in the USA. The training itself will not cause hurt, but if it is performed in a crucial-improper form (using the wrong technique), it will injure the exerciser. Research has explored the potential of using wearables to monitor fitness training, but the consideration of proper/improper form is not included. In this paper, we propose WearCoach, a wearable based fitness training assistant, which acquires the user's fitness form information and generates real-time feedback during training. WearCoach differs from previous work of training assistant in 1) it employs a two-phase tracking algorithm to achieve accurate and real-time tracking of body motion, 2) it analyzes the captured arm posture and generates training guidance based on the user's form, 3) it uses joint orientation as an exercise classification feature to improve recognition accuracy. We conducted experiments with eight participants and nine exercises. Three kinds of feedback are generated, including injury alert, movement correction and symmetry analysis. Yi Gao 0001, Yuefang Jiang, Wei Dong 0001 |
MASS | 4 |
| 2018 | Wearable-based Human-Computer Interaction with LimbMotionabstractLimbMotion is a limb tracking system which enables accurate and real-time tracking with one wearable device on the wrist/ankle of a user. By integrating inertial sensing and acoustic sensing, LimbMotion significantly reduces the search space of a moving limb, and provides accurate limb tracking for further human computer interaction (HCI). Objectives of this demo are to show how LimbMotion works and two HCI applications supported by LimbMotion. Yi Gao 0001, Xinyi Song, Wei Dong 0001, Yuefang Jiang |
SenSys | 6 |