CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy

Haozheng Zhang, Edmond S. L. Ho and Hubert P. H. Shum
Software Impacts (SIMPAC), 2022

 Impact Factor: 1.3

CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy

Abstract

Early prediction is clinically considered one of the essential parts of cerebral palsy (CP) treatment. We propose to implement a low-cost and interpretable classification system for supporting CP prediction based on General Movement Assessment (GMA). We design a Pytorch-based attention-informed graph convolutional network to early identify infants at risk of CP from skeletal data extracted from RGB videos. We also design a frequency-binning module for learning the CP movements in the frequency domain while filtering noise. Our system only requires consumer-grade RGB videos for training to support interactive-time CP prediction by providing an interpretable CP classification result.


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Plain Text

Haozheng Zhang, Edmond S. L. Ho and Hubert P. H. Shum, "CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy," Software Impacts, vol. 14, pp. 100419, Elsevier, 2022.

BibTeX

@article{zhang22cpagcn,
 author={Zhang, Haozheng and Ho, Edmond S. L. and Shum, Hubert P. H.},
 journal={Software Impacts},
 series={SIMPAC '24},
 title={CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy},
 year={2022},
 volume={14},
 pages={100419},
 numpages={4},
 doi={10.1016/j.simpa.2022.100419},
 issn={2665-9638},
 publisher={Elsevier},
}

RIS

TY  - JOUR
AU  - Zhang, Haozheng
AU  - Ho, Edmond S. L.
AU  - Shum, Hubert P. H.
T2  - Software Impacts
TI  - CP-AGCN: Pytorch-Based Attention Informed Graph Convolutional Network for Identifying Infants at Risk of Cerebral Palsy
PY  - 2022
VL  - 14
SP  - 100419
EP  - 100419
DO  - 10.1016/j.simpa.2022.100419
SN  - 2665-9638
PB  - Elsevier
ER  - 


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Last updated on 6 October 2024
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