Markerless motion analysis for early detection of infantile movement disorders

The analysis of spontaneous movements provides valuable information for diagnosing infantile movement disorders. However, analysis is time-consuming and interpretation requires well-trained experts. We present an automated system that captures 3D joint positions and head rotation of infants without attached markers or sensors. We introduce motion parameters of head, trunk, upper and lower limbs of both body sides that are related to range, variability, and symmetry of motions and offer objective diagnostic information for assessment of motor behavior. We analyze 6 recordings of 5 infants who are at high-risk of impaired motor development, and show how the system highlights movement characteristics that hint at disorders.