Application of Adaptive Block Matching in the Extraction of Temporal Motor Activity Signals from Video Recordings of Neonatal Seizures

relatively expensive, are generally used for only a few hours of monitoring, and may not be routinely available in many centers. Automated processing and analysis of video recordings of neonatal seizures can generate novel methods for extracting quantitative information that is relevant only to the seizure. The extraction of quantitative information from video recordings of neonatal seizures can be accomplished by two complementary procedures designed to extract temporal motion strength and motor activity signals from video [5], [6]. In principle, motor activity signals are obtained by projecting to the horizontal and vertical axes an anatomical site located at the body part affected by the seizure. The extraction of motor activity signals from video recordings of neonatal seizures relies on a procedure that can track the anatomical site of interest throughout the frame sequence. This paper presents the results of a study that relied on adaptive block matching to extract motor activity signals from the video recordings of neonatal seizures and other clinical events associated with high motor activity. This paper presents a procedure developed to extract quantitative information from video recordings of neonatal seizures in the form of temporal motor activity signals. The motor activity signals are extracted by tracking selected anatomical sites during the seizure using adaptive block matching. The motion of a block of pixels is quantified by searching for the most similar block of pixels in subsequent frames; this search is facilitated by employing various update strategies to account for the changing appearance of the block. The experiments indicate that the temporal motor activity signals extracted by the proposed procedure constitute an effective representation of videotaped clinical events and can be used for seizure recognition and characterization.