BLAB Roboshoulder: Cadaveric Shoulder Kinematics from Robotic Manipulation

University of Geneva researcher Florent Moissenet collected kinematics data from 10 shoulders using 5 cadaveric specimens. The dataset contains thorax, clavicle, scapula, and humerus motion during abduction, flexion, rotation, and other movements, induced by a robotic manipulator. Three-dimensional trajectories were tracked at 100 Hz using an optoelectronic system and bone-pinned markers.

Use Cases

• Validate biomechanical shoulder models based on 6-DoF kinematics data.
• Train machine learning models for motion prediction based on 3D marker trajectories.
• Analyze joint kinematics patterns during specific motions like scapular plane abduction.
• Benchmark robotic manipulation algorithms against precise cadaveric motion data.

Strengths

• Data originates from 5 cadaveric specimens, providing 10 shoulder measurements.
• Kinematics were captured at a high sampling rate of 100 Hz.
• Includes 6-DoF kinematics computed for all joints of the shoulder girdle.
• Three repetitions of each motion were performed, suggesting controlled experimental conditions.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Geneva

Collection Method

Motion induced by a robotic manipulator on cadaveric specimens, with 3D trajectories tracked by an optoelectronic system and markers fixed on bone pins.