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

1 citations · 2 across the 10 of their papers we have counts for

collaborators

11 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

Generating Personalized Lower-Limb Kinematics Across Walking Speeds Using Subject-Conditioned Diffusion

Diya Dinesh, Adrian Krieger, Changseob Song +3

Personalizing exoskeleton assistance requires user-specific gait data across many locomotor tasks, yet collecting this data demands repeated motion capture sessions that are costly…

cs.RO2026

Continual Online Personalization of Exoskeleton Control via Manifold-Aware Experience Replay

Changseob Song, Inseung Kang

Personalizing exoskeleton control remains a critical challenge for clinical users with gait disabilities. Online adaptation (OA) offers an effective solution by adapting in real ti…

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…

cs.RO2026★ 1 cited

Learning Hip Exoskeleton Control Policy via Predictive Neuromusculoskeletal Simulation

Ilseung Park, Changseob Song, Inseung Kang

Developing exoskeleton controllers that generalize across diverse locomotor conditions typically requires extensive motion-capture data and biomechanical labeling, limiting scalabi…

eess.SY2026

Soft Semi-active Back Support Device with Adaptive Force Profiles using Variable-elastic Actuation and Weight Feedback

Rohan Khatavkar, The Bach Nguyen, Inseung Kang +2

Portable active back support devices (BSDs) offer tunable assistance but are often bulky and heavy, limiting their usability. In contrast, passive BSDs are lightweight and compact…

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-…

cs.RO2024

Learning Speed-Adaptive Walking Agent Using Imitation Learning with Physics-Informed Simulation

Yi-Hung Chiu, Ung Hee Lee, Changseob Song +2

Virtual models of human gait, or digital twins, offer a promising solution for studying mobility without the need for labor-intensive data collection. However, challenges such as t…

cs.RO2024

Ground Perturbation Detection via Lower-Limb Kinematic States During Locomotion

Maria T. Tagliaferri, Leonardo Campeggi, Owen N. Beck +1

Falls during daily ambulation activities are a leading cause of injury in older adults due to delayed physiological responses to disturbances of balance. Lower-limb exoskeletons ha…

cs.RO2024

Personalization of Wearable Sensor-Based Joint Kinematic Estimation Using Computer Vision for Hip Exoskeleton Applications

Changseob Song, Bogdan Ivanyuk-Skulskyi, Adrian Krieger +2

Accurate lower-limb joint kinematic estimation is critical for applications such as patient monitoring, rehabilitation, and exoskeleton control. While previous studies have employe…