Early Detection of Infant Cerebral Palsy Risk based on Pose Estimation using OpenPose and Advanced Algorithms from Limited and Imbalance Dataset-Reference-Cited by-同舟云学术

Early Detection of Infant Cerebral Palsy Risk based on Pose Estimation using OpenPose and Advanced Algorithms from Limited and Imbalance Dataset

Published:2023-06-14 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
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Author:

Ningrum Endah Suryawati¹,Yuniarno Eko Mulyanto²,Purnomo Mauridhi Hery²

Affiliation:

1. Institut Teknologi Sepuluh Nopember,Dept. of Electrical Engineering Dept. of Computer Engineering,Surabaya,Indonesia

2. University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Institut Teknologi Sepuluh Nopember,Dept. of Electrical Engineering Dept. of Computer Engineering,Surabaya,Indonesia

Funder

Ministry of Education

Lembaga Pengelola Dana Pendidikan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10171833/10171851/10171951.pdf?arnumber=10171951

Reference27 articles.

1. Automated movement analysis to predict motor impairment in preterm infants: a retrospective study

2. Deep learning-based quantitative analyses of spontaneous movements and their association with early neurological development in preterm infants;shin,2021

3. Semi-supervised body parsing and pose estimation for enhancing infant general movement assessment

4. Towards early prediction of neurodevelopment disorders: Computational model for Face Touch and Self-adaptors in Infants;tafur;arXiv preprint arXiv 2301 07898,2023

5. Automated movement analysis to predict motor impairment in preterm infants: a retrospective study

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