Improving the accuracy and reliability of motion tracking methods used for extracting temporal motor activity signals from video recordings of neonatal seizures

• Published in: IEEE transactions on biomedical engineering Vol. 52; no. 4; pp. 747 - 749
• Main Authors: Karayiannis, N.B., Yaohua Xiong, Frost, J.D., Wise, M.S., Mizrahi, E.M.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.04.2005; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial Intelligence; Biomedical engineering; Cluster Analysis; Data mining; Feedback; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Infant, Newborn; Infant, Newborn, Diseases - diagnosis; Infant, Newborn, Diseases - physiopathology; Information Storage and Retrieval - methods; Intensive Care, Neonatal - methods; Karhunen-Loeve transforms; Models, Biological; Monitoring, Physiologic - methods; Motion model; motion tracking; Motor Activity; motor activity signal; neonatal seizure; Nervous system; Neurophysiology; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated - methods; Pediatrics; Reproducibility of Results; Seizures - diagnosis; Seizures - physiopathology; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; Taylor series; Tracking; Video Recording - methods; Video surveillance
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2005.844047

This paper presents an approach for improving the accuracy and reliability of motion tracking methods developed for video based on block motion models. This approach estimates the displacement of a block of pixels between two successive frames by minimizing an error function defined in terms of the pixel intensities at these frames. The minimization problem is made analytically tractable by approximating the error function using a second-order Taylor expansion. The improved reliability of the proposed method is illustrated by its application in the extraction of temporal motor activity signals from video recordings of neonatal seizures.