Human Skeleton Analysis and Kinematics

The team focuses on the mathematical modeling of human movement and the automated extraction of biometric data from skeletal sequences, primarily utilizing depth sensors (e.g., Microsoft Kinect).

Key Research Focus

• Kinetic Motion Analysis: Development of algorithms for real-time tracking of joint trajectories. This includes evaluating gait stability, limb range of motion, and detecting motor anomalies.
• Robust Data Filtering: Utilizing advanced statistical methods and filters (e.g., Kalman filters) to mitigate sensor noise, ensuring accurate 3D skeletal reconstruction even in non-laboratory environments.
• Postural Assessment: Automated evaluation of posture to identify asymmetrical movement patterns that may indicate underlying neurological or orthopedic conditions.
• Activity Recognition: Implementing machine learning models to classify types of movement and daily activities (ADL), supporting applications in elderly care and Ambient Assisted Living.