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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15712
Title: Autonomous vision-guided approach for the analysis and grading of vertical suspension tests during Hammersmith Infant Neurological Examination (HINE)
Authors: Dey P.
Dogra D.P.
Pratim Roy, Partha
Bhaskar H.
Published in: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Abstract: Computer vision assisted diagnostic systems are gaining popularity in different healthcare applications. This paper presents a video analysis and pattern recognition framework for the automatic grading of vertical suspension tests on infants during the Hammersmith Infant Neurological Examination (HINE). The proposed vision-guided pipeline applies a color-based skin region segmentation procedure followed by the localization of body parts before feature extraction and classification. After constrained localization of lower body parts, a stick-diagram representation is used for extracting novel features that correspond to the motion dynamic characteristics of the infant's leg movements during HINE. This set of pose features generated from such a representation includes knee angles and distances between knees and hills. Finally, a time-series representation of the feature vector is used to train a Hidden Markov Model (HMM) for classifying the grades of the HINE tests into three predefined categories. Experiments are carried out by testing the proposed framework on a large number of vertical suspension test videos recorded at a Neuro-development clinic. The automatic grading results obtained from the proposed method matches the scores of experts at an accuracy of 74%. © 2016 IEEE.
Citation: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, (2016), 863- 866
URI: https://doi.org/10.1109/EMBC.2016.7590837
http://repository.iitr.ac.in/handle/123456789/15712
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Examination automation
HINE
Infant neurological examinations
Limb tracking
Pattern analysis
ISBN: 9.78146E+12
ISSN: 1557170X
Author Scopus IDs: 56868240500
35408975400
56880478500
8942447300
Author Affiliations: Dey, P., Department of CSE, IIT Kharagpur721302, India
Dogra, D.P., School of Electrical Sciences, IIT Bhubaneswar751013, India
Roy, P.P., Department of CSE, IIT Kharagpur721302, India
Bhaskar, H., Department of ECE, Khalifa University, P.O. Box 127788, Abu Dhabi, United Arab Emirates
Appears in Collections:Conference Publications [CS]

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