activity
20172026
most citedMulti-view Human Pose and Shape Estimation Using Learnable Volumetric Aggregation

13 citations · 22 across the 11 of their papers we have counts for

collaborators

12 papers

cs.RO2026

A Unified Kinematic Representation Enables Reusable Biological Joint Moment Estimation

Jinwoo Hwang, Ilseung Park, Changseob Song +3

Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However, these estimators are often…

cs.RO2026

Effects of Assistance Delay on Joint Mechanics and Energetics in Biological Torque Control of a Hip Exoskeleton

Jimin An, Ryan Lee, Jingshu Peng +2

Biological torque control directly maps an estimated human joint moment to exoskeleton assistance, providing a task-agnostic strategy for supporting diverse locomotor activities. H…

cs.RO2026

Musculoskeletal Motion Imitation for Learning Personalized Exoskeleton Control Policy in Impaired Gait

Itak Choi, Ilseung Park, Eni Halilaj +1

Designing generalizable control policies for lower-limb exoskeletons remains fundamentally constrained by exhaustive data collection or iterative optimization procedures, which lim…

physics.med-ph2025

Contactless Monitoring of Muscle Vibrations During Exercise with a Chaos-Inspired Radar

Jiangyifei Zhu, Yuzhe Wang, Tao Qiang +6

In this paper, our goal is to enable quantitative feedback on muscle fatigue during exercise to optimize exercise effectiveness while minimizing injury risk. We seek to capture fat…

cs.CV2025

MAMMA: Markerless & Automatic Multi-Person Motion Action Capture

Hanz Cuevas-Velasquez, Anastasios Yiannakidis, Soyong Shin +7

We present MAMMA, a markerless motion-capture pipeline that accurately recovers SMPL-X parameters from multi-view video of two-person interaction sequences. Traditional motion-capt…

cs.RO2024★ 1 cited

Optimizing Locomotor Task Sets in Biological Joint Moment Estimation for Hip Exoskeleton Applications

Jimin An, Changseob Song, Eni Halilaj +1

Accurate estimation of a user's biological joint moment from wearable sensor data is vital for improving exoskeleton control during real-world locomotor tasks. However, most state-…