Extraction of motion strength and motor activity signals from video recordings of neonatal seizures

Presents two methods developed to extract quantitative information from video recordings of neonatal seizures in the form of temporal motion strength and motor activity signals. Motion strength signals are extracted by measuring the area of the body parts that move during the seizure and the relative speed of motion using a combination of spatiotemporal subband decomposition of video, nonlinear filtering, and segmentation. Motor activity signals are extracted by tracking selected anatomical sites during the seizure using a modified version of a feature-tracking procedure developed for video, known as the Kanade-Lucas-Tomasi (KLT) algorithm. The experiments indicate that the temporal signals produced by the proposed methods provide the basis for differentiating myoclonic from focal clonic seizures and distinguishing these types of neonatal seizures from normal infant behaviors.