Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
The current reference point for multi-institution, multi-robot video–kinematics data in healthcare robotics.
Not a paper dump. Each work is read through the same clinical-action lens: what the system observes, what it can do, how the patient responds, and which outcome matters.
The current reference point for multi-institution, multi-robot video–kinematics data in healthcare robotics.
Shows how heterogeneous healthcare robot demonstrations can be normalized into a shared action representation.
A useful example of task-segmented video, kinematics, successful demonstrations, and recovery maneuvers.
A platform-agnostic way to capture hand, foot, video, and interaction signals without proprietary telemetry.
An early attempt to connect robotic kinematic indicators with patient-reported postoperative outcomes.
Learns when assistance is needed from therapist demonstrations and adapts that judgment to new users.
Frames patient-specific treatment policies around longitudinal models, constraints, and human collaboration.
A clear physical-action problem: infer probe motion from image state to autonomously acquire a target view.